From 2880421e373957e44ff38d1ff6bf751b41011da7 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 8 Mar 2024 10:38:22 +0100
Subject: [PATCH 001/273] .

---
 domainlab/algos/msels/a_model_sel.py   | 12 ++++++------
 domainlab/algos/msels/c_msel_oracle.py | 10 +++++-----
 domainlab/algos/msels/c_msel_val.py    | 16 ++++++++--------
 3 files changed, 19 insertions(+), 19 deletions(-)

diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index e2e63c993..0902733ab 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -15,7 +15,7 @@ def __init__(self):
         trainer and tr_observer
         """
         self.trainer = None
-        self._tr_obs = None
+        self._observer = None
         self.msel = None
         self._max_es = None
 
@@ -27,11 +27,11 @@ def reset(self):
             self.msel.reset()
 
     @property
-    def tr_obs(self):
+    def observer4msel(self):
         """
         the observer from trainer
         """
-        return self._tr_obs
+        return self._observer
 
     @property
     def max_es(self):
@@ -44,15 +44,15 @@ def max_es(self):
             return self.msel.max_es
         return self._max_es
 
-    def accept(self, trainer, tr_obs):
+    def accept(self, trainer, observer4msel):
         """
         Visitor pattern to trainer
         accept trainer and tr_observer
         """
         self.trainer = trainer
-        self._tr_obs = tr_obs
+        self._observer = observer4msel
         if self.msel is not None:
-            self.msel.accept(trainer, tr_obs)
+            self.msel.accept(trainer, observer4msel)
 
     @abc.abstractmethod
     def update(self, clear_counter=False):
diff --git a/domainlab/algos/msels/c_msel_oracle.py b/domainlab/algos/msels/c_msel_oracle.py
index e232b1e78..95be69f38 100644
--- a/domainlab/algos/msels/c_msel_oracle.py
+++ b/domainlab/algos/msels/c_msel_oracle.py
@@ -36,9 +36,9 @@ def update(self, clear_counter=False):
         """
         self.trainer.model.save("epoch")
         flag = False
-        if self.tr_obs.metric_val is None:
+        if self.observer4msel.metric_val is None:
             return super().update(clear_counter)
-        metric = self.tr_obs.metric_te[self.tr_obs.str_metric4msel]
+        metric = self.observer4msel.metric_te[self.observer4msel.str_metric4msel]
         if metric > self.best_oracle_acc:
             self.best_oracle_acc = metric
             if self.msel is not None:
@@ -62,7 +62,7 @@ def if_stop(self):
             return self.msel.if_stop()
         return False
 
-    def accept(self, trainer, tr_obs):
+    def accept(self, trainer, observer4msel):
         if self.msel is not None:
-            self.msel.accept(trainer, tr_obs)
-        super().accept(trainer, tr_obs)
+            self.msel.accept(trainer, observer4msel)
+        super().accept(trainer, observer4msel)
diff --git a/domainlab/algos/msels/c_msel_val.py b/domainlab/algos/msels/c_msel_val.py
index c1f2f5561..054ca56ad 100644
--- a/domainlab/algos/msels/c_msel_val.py
+++ b/domainlab/algos/msels/c_msel_val.py
@@ -12,7 +12,7 @@ class MSelValPerf(MSelTrLoss):
     """
 
     def __init__(self, max_es):
-        super().__init__(max_es)  # construct self.tr_obs (observer)
+        super().__init__(max_es)  # construct self.observer4msel (observer)
         self.reset()
 
     def reset(self):
@@ -44,11 +44,11 @@ def update(self, clear_counter=False):
         if the best model should be updated
         """
         flag = True
-        if self.tr_obs.metric_val is None:
+        if self.observer4msel.metric_val is None:
             return super().update(clear_counter)
-        metric = self.tr_obs.metric_val[self.tr_obs.str_metric4msel]
-        if self.tr_obs.metric_te is not None:
-            metric_te_current = self.tr_obs.metric_te[self.tr_obs.str_metric4msel]
+        metric = self.observer4msel.metric_val[self.observer4msel.str_metric4msel]
+        if self.observer4msel.metric_te is not None:
+            metric_te_current = self.observer4msel.metric_te[self.observer4msel.str_metric4msel]
             self._best_te_metric = max(self._best_te_metric, metric_te_current)
 
         if metric > self._best_val_acc:  # update hat{model}
@@ -56,8 +56,8 @@ def update(self, clear_counter=False):
             # the bigger the better
             self._best_val_acc = metric
             self.es_c = 0  # restore counter
-            if self.tr_obs.metric_te is not None:
-                metric_te_current = self.tr_obs.metric_te[self.tr_obs.str_metric4msel]
+            if self.observer4msel.metric_te is not None:
+                metric_te_current = self.observer4msel.metric_te[self.observer4msel.str_metric4msel]
                 self._sel_model_te_acc = metric_te_current
 
         else:
@@ -65,7 +65,7 @@ def update(self, clear_counter=False):
             logger = Logger.get_logger()
             logger.info(f"early stop counter: {self.es_c}")
             logger.info(
-                f"val acc:{self.tr_obs.metric_val['acc']}, "
+                f"val acc:{self.observer4msel.metric_val['acc']}, "
                 + f"best validation acc: {self.best_val_acc}, "
                 + f"corresponding to test acc: \
                         {self.sel_model_te_acc} / {self.best_te_metric}"

From cbabfebf9df3d1f4688b834165ee692a4345dfbf Mon Sep 17 00:00:00 2001
From: sidulova <sidul001@gwu.edu>
Date: Fri, 8 Mar 2024 12:08:28 -0500
Subject: [PATCH 002/273] new argument in arg parser that is bassed to b task.

---
 domainlab/arg_parser.py   | 5 ++++-
 domainlab/tasks/b_task.py | 4 +++-
 2 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index f8f78c28b..62e002350 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -294,7 +294,10 @@ def mk_parser_main():
     arg_group_task.add_argument(
         "--loglevel", type=str, default="DEBUG", help="sets the loglevel of the logger"
     )
-
+    arg_group_task.add_argument(
+        "--shuffling_off", action="store_true", default=False,
+        help="disable shuffling of the training dataloader for the dataset"
+    )
     # args for variational auto encoder
     arg_group_vae = parser.add_argument_group("vae")
     arg_group_vae = add_args2parser_vae(arg_group_vae)
diff --git a/domainlab/tasks/b_task.py b/domainlab/tasks/b_task.py
index d8b778689..56ac4cd79 100644
--- a/domainlab/tasks/b_task.py
+++ b/domainlab/tasks/b_task.py
@@ -54,7 +54,9 @@ def init_business(self, args, trainer=None):
             self.dict_loader_tr.update({na_domain: mk_loader(ddset_tr, args.bs)})
             self.dict_dset_val.update({na_domain: ddset_val})
         ddset_mix = ConcatDataset(tuple(self.dict_dset_tr.values()))
-        self._loader_tr = mk_loader(ddset_mix, args.bs)
+        flag_shuffling = not args.shuffling_off
+        # args.shuffling_off default is False -> not False -> True
+        self._loader_tr = mk_loader(ddset_mix, args.bs, shuffle=flag_shuffling)
 
         ddset_mix_val = ConcatDataset(tuple(self.dict_dset_val.values()))
         self._loader_val = mk_loader(

From 88ff88bb8e4355434bc8db16680d946d291fb777 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sun, 17 Mar 2024 14:59:14 +0100
Subject: [PATCH 003/273] Update benchmark_pacs_resnet_model.yaml

---
 examples/benchmark/benchmark_pacs_resnet_model.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/benchmark/benchmark_pacs_resnet_model.yaml b/examples/benchmark/benchmark_pacs_resnet_model.yaml
index 7c9b9dbd7..c3bfde043 100644
--- a/examples/benchmark/benchmark_pacs_resnet_model.yaml
+++ b/examples/benchmark/benchmark_pacs_resnet_model.yaml
@@ -33,13 +33,13 @@ domainlab_args:
 Shared params:
   num_shared_param_samples: 9
   gamma_y:
-    min: 1e4
+    min: 1
     max: 1e8
     step: 1000
     distribution: loguniform
 
   gamma_d:
-    min: 1e4
+    min: 1
     max: 1e8
     step: 1000
     distribution: loguniform

From 51fe0bdaf8b7939e7706da7508c3ef6f01e4d798 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 22 Mar 2024 11:59:19 +0100
Subject: [PATCH 004/273] Added functionality to log in which epoch the model
 was selected to the results file. Integrated in the model selection process

---
 domainlab/algos/msels/a_model_sel.py     | 22 +++++++++++++++++++++-
 domainlab/algos/msels/c_msel_oracle.py   |  6 +++---
 domainlab/algos/msels/c_msel_tr_loss.py  |  2 +-
 domainlab/algos/msels/c_msel_val.py      |  4 ++--
 domainlab/algos/observers/b_obvisitor.py |  4 +++-
 domainlab/exp/exp_utils.py               |  1 +
 6 files changed, 31 insertions(+), 8 deletions(-)

diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index 0902733ab..a177ebd1d 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -18,6 +18,7 @@ def __init__(self):
         self._observer = None
         self.msel = None
         self._max_es = None
+        self._model_selection_epoch = None
 
     def reset(self):
         """
@@ -54,8 +55,18 @@ def accept(self, trainer, observer4msel):
         if self.msel is not None:
             self.msel.accept(trainer, observer4msel)
 
+    def update(self, epoch, clear_counter=False):
+        """
+        level above the observer + visitor pattern to get information about the epoch
+        """
+        update = self._update(clear_counter)
+        if update: 
+            self._model_selection_epoch = epoch
+
+        return update
+
     @abc.abstractmethod
-    def update(self, clear_counter=False):
+    def _update(self, clear_counter=False): 
         """
         observer + visitor pattern to trainer
         if the best model should be updated
@@ -101,3 +112,12 @@ def sel_model_te_acc(self):
         if self.msel is not None:
             return self.msel.sel_model_te_acc
         return -1
+    
+    @property
+    def model_selection_epoch(self):
+        """
+        the epoch when the model was selected
+        """
+        if self._model_selection_epoch is not None:
+            return self._model_selection_epoch
+        return -1
\ No newline at end of file
diff --git a/domainlab/algos/msels/c_msel_oracle.py b/domainlab/algos/msels/c_msel_oracle.py
index 95be69f38..21d51fc54 100644
--- a/domainlab/algos/msels/c_msel_oracle.py
+++ b/domainlab/algos/msels/c_msel_oracle.py
@@ -30,14 +30,14 @@ def oracle_last_setpoint_sel_te_acc(self):
             return self.msel.oracle_last_setpoint_sel_te_acc
         return -1
 
-    def update(self, clear_counter=False):
+    def _update(self, clear_counter=False):
         """
         if the best model should be updated
         """
         self.trainer.model.save("epoch")
         flag = False
         if self.observer4msel.metric_val is None:
-            return super().update(clear_counter)
+            return super()._update(clear_counter)
         metric = self.observer4msel.metric_te[self.observer4msel.str_metric4msel]
         if metric > self.best_oracle_acc:
             self.best_oracle_acc = metric
@@ -49,7 +49,7 @@ def update(self, clear_counter=False):
             logger.info("new oracle model saved")
             flag = True
         if self.msel is not None:
-            return self.msel.update(clear_counter)
+            return self.msel._update(clear_counter)
         return flag
 
     def if_stop(self):
diff --git a/domainlab/algos/msels/c_msel_tr_loss.py b/domainlab/algos/msels/c_msel_tr_loss.py
index 58ca03e21..13e3e0085 100644
--- a/domainlab/algos/msels/c_msel_tr_loss.py
+++ b/domainlab/algos/msels/c_msel_tr_loss.py
@@ -28,7 +28,7 @@ def reset(self):
     def max_es(self):
         return self._max_es
 
-    def update(self, clear_counter=False):
+    def _update(self, clear_counter=False):
         """
         if the best model should be updated
         """
diff --git a/domainlab/algos/msels/c_msel_val.py b/domainlab/algos/msels/c_msel_val.py
index 054ca56ad..7f25a782c 100644
--- a/domainlab/algos/msels/c_msel_val.py
+++ b/domainlab/algos/msels/c_msel_val.py
@@ -39,13 +39,13 @@ def best_te_metric(self):
         """
         return self._best_te_metric
 
-    def update(self, clear_counter=False):
+    def _update(self, clear_counter=False):
         """
         if the best model should be updated
         """
         flag = True
         if self.observer4msel.metric_val is None:
-            return super().update(clear_counter)
+            return super()._update(clear_counter)
         metric = self.observer4msel.metric_val[self.observer4msel.str_metric4msel]
         if self.observer4msel.metric_te is not None:
             metric_te_current = self.observer4msel.metric_te[self.observer4msel.str_metric4msel]
diff --git a/domainlab/algos/observers/b_obvisitor.py b/domainlab/algos/observers/b_obvisitor.py
index 04231a917..68ef82632 100644
--- a/domainlab/algos/observers/b_obvisitor.py
+++ b/domainlab/algos/observers/b_obvisitor.py
@@ -53,7 +53,7 @@ def update(self, epoch):
                     self.loader_te, self.device
                 )
                 self.metric_te = metric_te
-        if self.model_sel.update():
+        if self.model_sel.update(epoch):
             logger.info("better model found")
             self.host_trainer.model.save()
             logger.info("persisted")
@@ -102,8 +102,10 @@ def after_all(self):
             metric_te.update({"acc_oracle": -1})
         if hasattr(self, "model_sel"):
             metric_te.update({"acc_val": self.model_sel.best_val_acc})
+            metric_te.update({"model_selection_epoch": self.model_sel.model_selection_epoch})
         else:
             metric_te.update({"acc_val": -1})
+            metric_te.update({"model_selection_epoch": -1})
         self.dump_prediction(model_ld, metric_te)
         # save metric to one line in csv result file
         self.host_trainer.model.visitor(metric_te)
diff --git a/domainlab/exp/exp_utils.py b/domainlab/exp/exp_utils.py
index 2af681731..d467285d6 100644
--- a/domainlab/exp/exp_utils.py
+++ b/domainlab/exp/exp_utils.py
@@ -169,6 +169,7 @@ def get_cols(self):
             # algorithm configuration for instance
             "mname": "mname_" + self.model_name,
             "commit": "commit_" + self.git_tag,
+            "model_selection_epoch" : None
         }
         return dict_cols, epos_name
 

From 2cb53811a52e071fbf2be1727c554ad0f26e17ab Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 22 Mar 2024 14:58:19 +0100
Subject: [PATCH 005/273] Logging the duration through an additional attribute
 in the experiment class

---
 domainlab/exp/exp_main.py  | 2 +-
 domainlab/exp/exp_utils.py | 5 +++++
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/domainlab/exp/exp_main.py b/domainlab/exp/exp_main.py
index 51397131b..e6339bdbb 100755
--- a/domainlab/exp/exp_main.py
+++ b/domainlab/exp/exp_main.py
@@ -10,7 +10,6 @@
 from domainlab.tasks.zoo_tasks import TaskChainNodeGetter
 from domainlab.utils.logger import Logger
 from domainlab.utils.sanity_check import SanityCheck
-
 os.environ["CUDA_LAUNCH_BLOCKING"] = "1"  # debug
 
 
@@ -96,6 +95,7 @@ def execute(self, num_epochs=None):
             f"Experiment finished at epoch: {self.epoch_counter} "
             f"with time: {t_c - t_0} at {t_c}"
         )
+        self.experiment_duration = t_c - t_0
         self.trainer.post_tr()
 
     def clean_up(self):
diff --git a/domainlab/exp/exp_utils.py b/domainlab/exp/exp_utils.py
index 2af681731..95c130553 100644
--- a/domainlab/exp/exp_utils.py
+++ b/domainlab/exp/exp_utils.py
@@ -179,6 +179,11 @@ def _gen_line(self, dict_metric):
         confmat_filename = dict_cols.get("mname", None)  # return None if not found
         # @FIXME: strong dependency on host attribute name
         dict_cols.update({epos_name: self.host.epoch_counter})
+        if hasattr(self.host, "experiment_duration"): 
+            dict_cols.update({"experiment_duration": self.host.experiment_duration})
+        else: 
+            print("Does not have attribute")
+            print(self.host)
         if not self.has_first_line:
             self.first_line(dict_cols)
         list_str = [str(dict_cols[key]) for key in self.list_cols]

From 2c7901d40f9295865c9b10da7e1a0aa7c0fa49e9 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 22 Mar 2024 17:18:11 +0100
Subject: [PATCH 006/273] removed unnesseary line for the dictionary columns,
 because it is already contained in the dictionary beeing passed to the writer

---
 domainlab/exp/exp_utils.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/domainlab/exp/exp_utils.py b/domainlab/exp/exp_utils.py
index d467285d6..2af681731 100644
--- a/domainlab/exp/exp_utils.py
+++ b/domainlab/exp/exp_utils.py
@@ -169,7 +169,6 @@ def get_cols(self):
             # algorithm configuration for instance
             "mname": "mname_" + self.model_name,
             "commit": "commit_" + self.git_tag,
-            "model_selection_epoch" : None
         }
         return dict_cols, epos_name
 

From b4698309ba765270719f1f5e503b7897f4757622 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 22 Mar 2024 17:36:59 +0100
Subject: [PATCH 007/273] Moved declaration of attribute to constructor

---
 domainlab/exp/exp_main.py  | 1 +
 domainlab/exp/exp_utils.py | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/domainlab/exp/exp_main.py b/domainlab/exp/exp_main.py
index e6339bdbb..28f8ce40a 100755
--- a/domainlab/exp/exp_main.py
+++ b/domainlab/exp/exp_main.py
@@ -56,6 +56,7 @@ def __init__(self, args, task=None, model=None, observer=None, visitor=AggWriter
             self.trainer.init_business(self.model, self.task, observer, device, args)
         self.visitor = visitor(self)  # visitor depends on task initialization first
         # visitor must be initialized last after trainer is initialized
+        self.experiment_duration = None
         self.model.set_saver(self.visitor)
 
     def execute(self, num_epochs=None):
diff --git a/domainlab/exp/exp_utils.py b/domainlab/exp/exp_utils.py
index 95c130553..256a8be68 100644
--- a/domainlab/exp/exp_utils.py
+++ b/domainlab/exp/exp_utils.py
@@ -179,7 +179,7 @@ def _gen_line(self, dict_metric):
         confmat_filename = dict_cols.get("mname", None)  # return None if not found
         # @FIXME: strong dependency on host attribute name
         dict_cols.update({epos_name: self.host.epoch_counter})
-        if hasattr(self.host, "experiment_duration"): 
+        if self.host.experiment_duration is not None: 
             dict_cols.update({"experiment_duration": self.host.experiment_duration})
         else: 
             print("Does not have attribute")

From 82d6b5cdcad164ccdd0447d01e01f83ea1fbae53 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 22 Mar 2024 18:00:43 +0100
Subject: [PATCH 008/273] renamed method to not conflict with protected
 declaration

---
 domainlab/algos/msels/a_model_sel.py    | 4 ++--
 domainlab/algos/msels/c_msel_oracle.py  | 6 +++---
 domainlab/algos/msels/c_msel_tr_loss.py | 2 +-
 domainlab/algos/msels/c_msel_val.py     | 4 ++--
 4 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index a177ebd1d..1830ff5fd 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -59,14 +59,14 @@ def update(self, epoch, clear_counter=False):
         """
         level above the observer + visitor pattern to get information about the epoch
         """
-        update = self._update(clear_counter)
+        update = self.base_update(clear_counter)
         if update: 
             self._model_selection_epoch = epoch
 
         return update
 
     @abc.abstractmethod
-    def _update(self, clear_counter=False): 
+    def base_update(self, clear_counter=False): 
         """
         observer + visitor pattern to trainer
         if the best model should be updated
diff --git a/domainlab/algos/msels/c_msel_oracle.py b/domainlab/algos/msels/c_msel_oracle.py
index 21d51fc54..35943c295 100644
--- a/domainlab/algos/msels/c_msel_oracle.py
+++ b/domainlab/algos/msels/c_msel_oracle.py
@@ -30,14 +30,14 @@ def oracle_last_setpoint_sel_te_acc(self):
             return self.msel.oracle_last_setpoint_sel_te_acc
         return -1
 
-    def _update(self, clear_counter=False):
+    def base_update(self, clear_counter=False):
         """
         if the best model should be updated
         """
         self.trainer.model.save("epoch")
         flag = False
         if self.observer4msel.metric_val is None:
-            return super()._update(clear_counter)
+            return super().base_update(clear_counter)
         metric = self.observer4msel.metric_te[self.observer4msel.str_metric4msel]
         if metric > self.best_oracle_acc:
             self.best_oracle_acc = metric
@@ -49,7 +49,7 @@ def _update(self, clear_counter=False):
             logger.info("new oracle model saved")
             flag = True
         if self.msel is not None:
-            return self.msel._update(clear_counter)
+            return self.msel.base_update(clear_counter)
         return flag
 
     def if_stop(self):
diff --git a/domainlab/algos/msels/c_msel_tr_loss.py b/domainlab/algos/msels/c_msel_tr_loss.py
index 13e3e0085..9c4ee2c54 100644
--- a/domainlab/algos/msels/c_msel_tr_loss.py
+++ b/domainlab/algos/msels/c_msel_tr_loss.py
@@ -28,7 +28,7 @@ def reset(self):
     def max_es(self):
         return self._max_es
 
-    def _update(self, clear_counter=False):
+    def base_update(self, clear_counter=False):
         """
         if the best model should be updated
         """
diff --git a/domainlab/algos/msels/c_msel_val.py b/domainlab/algos/msels/c_msel_val.py
index 7f25a782c..581f3a9b6 100644
--- a/domainlab/algos/msels/c_msel_val.py
+++ b/domainlab/algos/msels/c_msel_val.py
@@ -39,13 +39,13 @@ def best_te_metric(self):
         """
         return self._best_te_metric
 
-    def _update(self, clear_counter=False):
+    def base_update(self, clear_counter=False):
         """
         if the best model should be updated
         """
         flag = True
         if self.observer4msel.metric_val is None:
-            return super()._update(clear_counter)
+            return super().base_update(clear_counter)
         metric = self.observer4msel.metric_val[self.observer4msel.str_metric4msel]
         if self.observer4msel.metric_te is not None:
             metric_te_current = self.observer4msel.metric_te[self.observer4msel.str_metric4msel]

From 1da5f885c242752118cb831d5da4d7d3d3da8bd2 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 22 Mar 2024 18:21:12 +0100
Subject: [PATCH 009/273] adjusted test to fit new signature

---
 tests/test_msel_oracle.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/test_msel_oracle.py b/tests/test_msel_oracle.py
index 3dfdd6fbe..8819d59f0 100644
--- a/tests/test_msel_oracle.py
+++ b/tests/test_msel_oracle.py
@@ -142,7 +142,7 @@ def test_msel_oracle1():
     )
 
     exp.execute(num_epochs=2)
-    exp.trainer.observer.model_sel.msel.update(clear_counter=True)
+    exp.trainer.observer.model_sel.msel.update(epoch=1, clear_counter=True)
     del exp
 
 
@@ -261,5 +261,5 @@ def test_msel_oracle4():
     )
     exp.execute(num_epochs=2)
     exp.trainer.observer.model_sel.msel.best_loss = 0
-    exp.trainer.observer.model_sel.msel.update(clear_counter=True)
+    exp.trainer.observer.model_sel.msel.update(epoch = 1, clear_counter=True)
     del exp

From ec5ead8e91fe28dfafe547d490e9ce62bf2086be Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sat, 23 Mar 2024 07:48:35 +0100
Subject: [PATCH 010/273] fix codacy

---
 domainlab/exp/exp_utils.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/domainlab/exp/exp_utils.py b/domainlab/exp/exp_utils.py
index 256a8be68..22a609b2c 100644
--- a/domainlab/exp/exp_utils.py
+++ b/domainlab/exp/exp_utils.py
@@ -179,9 +179,9 @@ def _gen_line(self, dict_metric):
         confmat_filename = dict_cols.get("mname", None)  # return None if not found
         # @FIXME: strong dependency on host attribute name
         dict_cols.update({epos_name: self.host.epoch_counter})
-        if self.host.experiment_duration is not None: 
+        if self.host.experiment_duration is not None:
             dict_cols.update({"experiment_duration": self.host.experiment_duration})
-        else: 
+        else:
             print("Does not have attribute")
             print(self.host)
         if not self.has_first_line:

From d5c03c891a84c824d87019500e61cfbfa44a0c91 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Mon, 25 Mar 2024 14:01:34 +0100
Subject: [PATCH 011/273] Added epoch to update to fix method

---
 tests/test_msel_oracle.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_msel_oracle.py b/tests/test_msel_oracle.py
index 8819d59f0..8a28567b0 100644
--- a/tests/test_msel_oracle.py
+++ b/tests/test_msel_oracle.py
@@ -66,7 +66,7 @@ def mk_exp(
             model_sel.msel._best_val_acc = 1.0
     observer = ObVisitor(model_sel)
     exp = Exp(conf, task, model=model, observer=observer)
-    model_sel.update(clear_counter=True)
+    model_sel.update(epoch=1, clear_counter=True)
     return exp
 
 

From 3eb42dc846824d820ae7ee285ccad230924415f3 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Mon, 25 Mar 2024 15:22:33 +0100
Subject: [PATCH 012/273] Update README.md

---
 README.md | 14 ++++++--------
 1 file changed, 6 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index 6a561269f..786ea4a9d 100644
--- a/README.md
+++ b/README.md
@@ -94,15 +94,13 @@ For example,  the following result (without any augmentation like flip) is for P
 </div>
 
 
-### Temporary citation
+### Citation
 
 ```bibtex
-@manual{domainlab,
-  title={{DomainLab: modular python package for training domain invariant neural networks}},
-  author={{Xudong Sun, et.al.}},
-  organization={{Institute of AI for Health}},
-  year={2023},
-  url={https://github.com/marrlab/DomainLab},
-  note={temporary citation for domainlab}
+@misc{sun2024domainlab,
+  title={DomainLab: A modular Python package for domain generalization in deep learning},
+  author={Sun, Xudong and Feistner, Carla and Gossmann, Alexej and Schwarz, George and Umer, Rao Muhammad and Beer, Lisa and Rockenschaub, Patrick and Shrestha, Rahul Babu and Gruber, Armin and Chen, Nutan and others},
+  journal={https://arxiv.org/pdf/2403.14356.pdf},
+  year={2024}
 }
 ```

From 6126ddeb2df0fe3a07de458cac68e4ad02da3c66 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Mon, 25 Mar 2024 15:32:41 +0100
Subject: [PATCH 013/273] Update README.md

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index 786ea4a9d..e4b22dbe7 100644
--- a/README.md
+++ b/README.md
@@ -96,6 +96,8 @@ For example,  the following result (without any augmentation like flip) is for P
 
 ### Citation
 
+Source: https://arxiv.org/pdf/2403.14356.pdf
+
 ```bibtex
 @misc{sun2024domainlab,
   title={DomainLab: A modular Python package for domain generalization in deep learning},

From 2405e21cb67f8468f665dcbc09cbb69d90400949 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Wed, 27 Mar 2024 12:50:06 +0100
Subject: [PATCH 014/273] Added functionality to only stop after certain
 validation threshold is reached.

---
 domainlab/algos/builder_api_model.py     |  2 +-
 domainlab/algos/builder_custom.py        |  2 +-
 domainlab/algos/builder_dann.py          |  2 +-
 domainlab/algos/builder_diva.py          |  2 +-
 domainlab/algos/builder_erm.py           |  2 +-
 domainlab/algos/builder_hduva.py         |  2 +-
 domainlab/algos/builder_jigen1.py        |  2 +-
 domainlab/algos/msels/a_model_sel.py     | 26 +++++++++++++++++++-----
 domainlab/algos/msels/c_msel_oracle.py   |  8 ++++----
 domainlab/algos/msels/c_msel_tr_loss.py  |  6 +++---
 domainlab/algos/msels/c_msel_val.py      |  4 ++--
 domainlab/algos/observers/b_obvisitor.py |  2 +-
 domainlab/arg_parser.py                  |  7 +++++++
 domainlab/exp/exp_main.py                |  1 +
 examples/conf/vlcs_diva_mldg_dial.yaml   |  1 +
 15 files changed, 47 insertions(+), 22 deletions(-)

diff --git a/domainlab/algos/builder_api_model.py b/domainlab/algos/builder_api_model.py
index 07c087e3b..9bfb66fc2 100644
--- a/domainlab/algos/builder_api_model.py
+++ b/domainlab/algos/builder_api_model.py
@@ -20,7 +20,7 @@ def init_business(self, exp):
         """
         args = exp.args
         device = get_device(args)
-        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
         observer = ObVisitor(model_sel)
         trainer = TrainerChainNodeGetter(args.trainer)(default="hyperscheduler")
         return trainer, None, observer, device
diff --git a/domainlab/algos/builder_custom.py b/domainlab/algos/builder_custom.py
index 9c50110b7..1732a072a 100644
--- a/domainlab/algos/builder_custom.py
+++ b/domainlab/algos/builder_custom.py
@@ -104,7 +104,7 @@ def init_business(self, exp):
             task = exp.task
             args = exp.args
             device = get_device(args)
-            model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+            model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
             observer = ObVisitor(model_sel)
             model = class_name_model(net_classifier=None, list_str_y=task.list_str_y)
             model = self.init_next_model(model, exp)
diff --git a/domainlab/algos/builder_dann.py b/domainlab/algos/builder_dann.py
index d026a5bb1..65b26a62a 100644
--- a/domainlab/algos/builder_dann.py
+++ b/domainlab/algos/builder_dann.py
@@ -29,7 +29,7 @@ def init_business(self, exp):
         args = exp.args
         task.get_list_domains_tr_te(args.tr_d, args.te_d)
         device = get_device(args)
-        msel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+        msel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
         observer = ObVisitor(msel)
         observer = ObVisitorCleanUp(observer)
 
diff --git a/domainlab/algos/builder_diva.py b/domainlab/algos/builder_diva.py
index 38ceb6e9e..5e33826ec 100644
--- a/domainlab/algos/builder_diva.py
+++ b/domainlab/algos/builder_diva.py
@@ -48,7 +48,7 @@ def init_business(self, exp):
             beta_d=args.beta_d,
         )
         device = get_device(args)
-        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
         if not args.gen:
             observer = ObVisitor(model_sel)
         else:
diff --git a/domainlab/algos/builder_erm.py b/domainlab/algos/builder_erm.py
index 4e76670c0..1221cb209 100644
--- a/domainlab/algos/builder_erm.py
+++ b/domainlab/algos/builder_erm.py
@@ -24,7 +24,7 @@ def init_business(self, exp):
         task = exp.task
         args = exp.args
         device = get_device(args)
-        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
         observer = ObVisitor(model_sel)
 
         builder = FeatExtractNNBuilderChainNodeGetter(
diff --git a/domainlab/algos/builder_hduva.py b/domainlab/algos/builder_hduva.py
index 80e4526cb..1a752e47f 100644
--- a/domainlab/algos/builder_hduva.py
+++ b/domainlab/algos/builder_hduva.py
@@ -43,7 +43,7 @@ def init_business(self, exp):
             beta_d=args.beta_d,
         )
         model = self.init_next_model(model, exp)
-        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
         observer = ObVisitorCleanUp(ObVisitor(model_sel))
         trainer = TrainerChainNodeGetter(args.trainer)(default="hyperscheduler")
         trainer.init_business(model, task, observer, device, args)
diff --git a/domainlab/algos/builder_jigen1.py b/domainlab/algos/builder_jigen1.py
index 4f402c128..e899e32f2 100644
--- a/domainlab/algos/builder_jigen1.py
+++ b/domainlab/algos/builder_jigen1.py
@@ -29,7 +29,7 @@ def init_business(self, exp):
         task = exp.task
         args = exp.args
         device = get_device(args)
-        msel = MSelOracleVisitor(msel=MSelValPerf(max_es=args.es))
+        msel = MSelOracleVisitor(msel=MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
         observer = ObVisitor(msel)
         observer = ObVisitorCleanUp(observer)
 
diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index 1830ff5fd..b49a3a3da 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -10,7 +10,7 @@ class AMSel(metaclass=abc.ABCMeta):
     Abstract Model Selection
     """
 
-    def __init__(self):
+    def __init__(self, val_threshold = None):
         """
         trainer and tr_observer
         """
@@ -19,6 +19,7 @@ def __init__(self):
         self.msel = None
         self._max_es = None
         self._model_selection_epoch = None
+        self._val_threshold = val_threshold
 
     def reset(self):
         """
@@ -73,9 +74,9 @@ def base_update(self, clear_counter=False):
         return boolean
         """
 
-    def if_stop(self):
+    def if_stop(self, acc_val):
         """
-        check if trainer should stop
+        check if trainer should stop and additionally tests for validation threshold
         return boolean
         """
         # NOTE: since if_stop is not abstract, one has to
@@ -83,7 +84,17 @@ def if_stop(self):
         # only if the child class has a decorator which will
         # dispatched.
         if self.msel is not None:
-            return self.msel.if_stop()
+            if self._val_threshold is not None and acc_val < self._val_threshold:
+                return False
+        return self.early_stop()
+    
+    def early_stop(self):
+        """
+        check if trainer should stop
+        return boolean
+        """
+        if self.msel is not None:
+            return self.msel.early_stop()
         raise NotImplementedError
 
     @property
@@ -120,4 +131,9 @@ def model_selection_epoch(self):
         """
         if self._model_selection_epoch is not None:
             return self._model_selection_epoch
-        return -1
\ No newline at end of file
+        return -1
+    
+    @property
+    def val_threshold(self):
+        return self._val_threshold
+    
\ No newline at end of file
diff --git a/domainlab/algos/msels/c_msel_oracle.py b/domainlab/algos/msels/c_msel_oracle.py
index 35943c295..d61047c75 100644
--- a/domainlab/algos/msels/c_msel_oracle.py
+++ b/domainlab/algos/msels/c_msel_oracle.py
@@ -11,11 +11,11 @@ class MSelOracleVisitor(AMSel):
     how the final model is selected
     """
 
-    def __init__(self, msel=None):
+    def __init__(self, msel=None, val_threshold = None):
         """
         Decorator pattern
         """
-        super().__init__()
+        super().__init__(val_threshold)
         self.best_oracle_acc = 0
         self.msel = msel
 
@@ -52,14 +52,14 @@ def base_update(self, clear_counter=False):
             return self.msel.base_update(clear_counter)
         return flag
 
-    def if_stop(self):
+    def early_stop(self):
         """
         if should early stop
         oracle model selection does not intervene how models get selected
         by the innermost model selection
         """
         if self.msel is not None:
-            return self.msel.if_stop()
+            return self.msel.early_stop()
         return False
 
     def accept(self, trainer, observer4msel):
diff --git a/domainlab/algos/msels/c_msel_tr_loss.py b/domainlab/algos/msels/c_msel_tr_loss.py
index 9c4ee2c54..609550a9a 100644
--- a/domainlab/algos/msels/c_msel_tr_loss.py
+++ b/domainlab/algos/msels/c_msel_tr_loss.py
@@ -13,8 +13,8 @@ class MSelTrLoss(AMSel):
     2. Visitor pattern to trainer
     """
 
-    def __init__(self, max_es):
-        super().__init__()
+    def __init__(self, max_es, val_threshold = None):
+        super().__init__(val_threshold)
         # NOTE: super() must come first otherwise it will overwrite existing
         # values!
         self.reset()
@@ -50,7 +50,7 @@ def base_update(self, clear_counter=False):
                 self.es_c = 0
         return flag
 
-    def if_stop(self):
+    def early_stop(self):
         """
         if should early stop
         """
diff --git a/domainlab/algos/msels/c_msel_val.py b/domainlab/algos/msels/c_msel_val.py
index 581f3a9b6..38c91ad58 100644
--- a/domainlab/algos/msels/c_msel_val.py
+++ b/domainlab/algos/msels/c_msel_val.py
@@ -11,8 +11,8 @@ class MSelValPerf(MSelTrLoss):
     2. Visitor pattern to trainer
     """
 
-    def __init__(self, max_es):
-        super().__init__(max_es)  # construct self.observer4msel (observer)
+    def __init__(self, max_es, val_threshold = None):
+        super().__init__(max_es, val_threshold)  # construct self.observer4msel (observer)
         self.reset()
 
     def reset(self):
diff --git a/domainlab/algos/observers/b_obvisitor.py b/domainlab/algos/observers/b_obvisitor.py
index 68ef82632..d746dbf1a 100644
--- a/domainlab/algos/observers/b_obvisitor.py
+++ b/domainlab/algos/observers/b_obvisitor.py
@@ -57,7 +57,7 @@ def update(self, epoch):
             logger.info("better model found")
             self.host_trainer.model.save()
             logger.info("persisted")
-        flag_stop = self.model_sel.if_stop()
+        flag_stop = self.model_sel.if_stop(self.metric_val["acc"])
         flag_enough = epoch >= self.host_trainer.aconf.epos_min
         return flag_stop & flag_enough
 
diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index 62e002350..2a44c0ba4 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -244,6 +244,13 @@ def mk_parser_main():
 
     parser.add_argument("--task", metavar="ta", type=str, help="task name")
 
+    parser.add_argument(
+        "--val_threshold",
+        type=float,
+        default=None, 
+        help="Accuracy threshold before early stopping can be applied"
+    )
+
     arg_group_task = parser.add_argument_group("task args")
 
     arg_group_task.add_argument(
diff --git a/domainlab/exp/exp_main.py b/domainlab/exp/exp_main.py
index 28f8ce40a..95eaef316 100755
--- a/domainlab/exp/exp_main.py
+++ b/domainlab/exp/exp_main.py
@@ -50,6 +50,7 @@ def __init__(self, args, task=None, model=None, observer=None, visitor=AggWriter
             self.model = model
         self.epochs = self.args.epos
         self.epoch_counter = 1
+        self.val_threshold = args.val_threshold 
         if observer is None:
             observer = observer_default
         if not self.trainer.flag_initialized:
diff --git a/examples/conf/vlcs_diva_mldg_dial.yaml b/examples/conf/vlcs_diva_mldg_dial.yaml
index 0701766ff..ac2d83337 100644
--- a/examples/conf/vlcs_diva_mldg_dial.yaml
+++ b/examples/conf/vlcs_diva_mldg_dial.yaml
@@ -1,6 +1,7 @@
 te_d: caltech                       # domain name of test domain
 tpath: examples/tasks/task_vlcs.py  # python file path to specify the task
 bs: 2                               # batch size
+val_threshold: 0.8
 model: dann_diva                    # combine model DANN with DIVA
 epos: 1                             # number of epochs
 trainer: mldg_dial                  # combine trainer MLDG and DIAL

From 1ec8891d493ec80808931f6a7008f462bb3b1aeb Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Wed, 27 Mar 2024 12:53:33 +0100
Subject: [PATCH 015/273] codacity fix

---
 domainlab/algos/msels/a_model_sel.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index 1830ff5fd..1f56811ce 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -60,13 +60,13 @@ def update(self, epoch, clear_counter=False):
         level above the observer + visitor pattern to get information about the epoch
         """
         update = self.base_update(clear_counter)
-        if update: 
+        if update:
             self._model_selection_epoch = epoch
 
         return update
 
     @abc.abstractmethod
-    def base_update(self, clear_counter=False): 
+    def base_update(self, clear_counter=False):
         """
         observer + visitor pattern to trainer
         if the best model should be updated
@@ -112,7 +112,7 @@ def sel_model_te_acc(self):
         if self.msel is not None:
             return self.msel.sel_model_te_acc
         return -1
-    
+
     @property
     def model_selection_epoch(self):
         """
@@ -120,4 +120,4 @@ def model_selection_epoch(self):
         """
         if self._model_selection_epoch is not None:
             return self._model_selection_epoch
-        return -1
\ No newline at end of file
+        return -1

From 56eea7d02c9f44184c1497dd31da8b2f6aae190e Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Wed, 27 Mar 2024 13:03:31 +0100
Subject: [PATCH 016/273] fix codacity

---
 domainlab/algos/builder_custom.py    | 3 ++-
 domainlab/algos/msels/a_model_sel.py | 9 ++++++---
 domainlab/arg_parser.py              | 2 +-
 domainlab/exp/exp_main.py            | 2 +-
 4 files changed, 10 insertions(+), 6 deletions(-)

diff --git a/domainlab/algos/builder_custom.py b/domainlab/algos/builder_custom.py
index 1732a072a..014118746 100644
--- a/domainlab/algos/builder_custom.py
+++ b/domainlab/algos/builder_custom.py
@@ -104,7 +104,8 @@ def init_business(self, exp):
             task = exp.task
             args = exp.args
             device = get_device(args)
-            model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
+            model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), 
+                                          val_threshold=args.val_threshold)
             observer = ObVisitor(model_sel)
             model = class_name_model(net_classifier=None, list_str_y=task.list_str_y)
             model = self.init_next_model(model, exp)
diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index b49a3a3da..be296a6ae 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -61,13 +61,13 @@ def update(self, epoch, clear_counter=False):
         level above the observer + visitor pattern to get information about the epoch
         """
         update = self.base_update(clear_counter)
-        if update: 
+        if update:
             self._model_selection_epoch = epoch
 
         return update
 
     @abc.abstractmethod
-    def base_update(self, clear_counter=False): 
+    def base_update(self, clear_counter=False):
         """
         observer + visitor pattern to trainer
         if the best model should be updated
@@ -87,7 +87,7 @@ def if_stop(self, acc_val):
             if self._val_threshold is not None and acc_val < self._val_threshold:
                 return False
         return self.early_stop()
-    
+
     def early_stop(self):
         """
         check if trainer should stop
@@ -135,5 +135,8 @@ def model_selection_epoch(self):
     
     @property
     def val_threshold(self):
+        """
+        the treshold below which we don't stop early
+        """
         return self._val_threshold
     
\ No newline at end of file
diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index 2a44c0ba4..7c7e004e7 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -247,7 +247,7 @@ def mk_parser_main():
     parser.add_argument(
         "--val_threshold",
         type=float,
-        default=None, 
+        default=None,
         help="Accuracy threshold before early stopping can be applied"
     )
 
diff --git a/domainlab/exp/exp_main.py b/domainlab/exp/exp_main.py
index 95eaef316..12ecea5f5 100755
--- a/domainlab/exp/exp_main.py
+++ b/domainlab/exp/exp_main.py
@@ -50,7 +50,7 @@ def __init__(self, args, task=None, model=None, observer=None, visitor=AggWriter
             self.model = model
         self.epochs = self.args.epos
         self.epoch_counter = 1
-        self.val_threshold = args.val_threshold 
+        self.val_threshold = args.val_threshold
         if observer is None:
             observer = observer_default
         if not self.trainer.flag_initialized:

From 22622662f9cb74946c2170808035f79442588f28 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Wed, 27 Mar 2024 13:08:18 +0100
Subject: [PATCH 017/273] fix codacity

---
 domainlab/algos/builder_custom.py    | 2 +-
 domainlab/algos/msels/a_model_sel.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/domainlab/algos/builder_custom.py b/domainlab/algos/builder_custom.py
index 014118746..166f34018 100644
--- a/domainlab/algos/builder_custom.py
+++ b/domainlab/algos/builder_custom.py
@@ -104,7 +104,7 @@ def init_business(self, exp):
             task = exp.task
             args = exp.args
             device = get_device(args)
-            model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), 
+            model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es),
                                           val_threshold=args.val_threshold)
             observer = ObVisitor(model_sel)
             model = class_name_model(net_classifier=None, list_str_y=task.list_str_y)
diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index be296a6ae..b40cca8c6 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -123,7 +123,7 @@ def sel_model_te_acc(self):
         if self.msel is not None:
             return self.msel.sel_model_te_acc
         return -1
-    
+
     @property
     def model_selection_epoch(self):
         """

From 2ac9281c3b54dd2aadcd5e1c5109aa44566a592f Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Wed, 27 Mar 2024 13:11:07 +0100
Subject: [PATCH 018/273] fix codacity

---
 domainlab/algos/msels/a_model_sel.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index b40cca8c6..17455511f 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -132,7 +132,7 @@ def model_selection_epoch(self):
         if self._model_selection_epoch is not None:
             return self._model_selection_epoch
         return -1
-    
+  
     @property
     def val_threshold(self):
         """

From e0c5afbd624871f2180e1c3a1fd5a49c311dce49 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Wed, 27 Mar 2024 13:16:29 +0100
Subject: [PATCH 019/273] fix codacity

---
 domainlab/algos/msels/a_model_sel.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index 17455511f..75edbcd74 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -132,7 +132,7 @@ def model_selection_epoch(self):
         if self._model_selection_epoch is not None:
             return self._model_selection_epoch
         return -1
-  
+
     @property
     def val_threshold(self):
         """

From 43d1cda636ba59ed9f2237836aeabf4e0eeb25f0 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 28 Mar 2024 08:28:18 +0100
Subject: [PATCH 020/273] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index e4b22dbe7..731959890 100644
--- a/README.md
+++ b/README.md
@@ -82,7 +82,7 @@ One could simply run
 `bash run_benchmark_slurm.sh your_benchmark_configuration.yaml` to launch different experiments with specified configuraiton.
 
 
-For example,  the following result (without any augmentation like flip) is for PACS dataset using ResNet. 
+For example,  the following result (without any augmentation like flip) is for PACS dataset using ResNet. The reader should note that using different neural network, whether pre-trained or not, what kind of preprocessinga and augmentation to use can lead to very different result distributions, which is one of the features DomainLab provide: the above factors get decoupled in DomainLab. 
 
 <div style="align: center; text-align:center;">
 <figure>  

From 1fc469b51ec6be07d5d3f13849b0b05a7a3e4071 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 28 Mar 2024 15:48:06 +0100
Subject: [PATCH 021/273] Update README.md

---
 README.md | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/README.md b/README.md
index 731959890..c912b51e6 100644
--- a/README.md
+++ b/README.md
@@ -45,6 +45,19 @@ We offer various ways for the user to specify a scenario to evaluate the general
 [Task Specification](./docs/doc_tasks.md) 
 
 ### Example and usage
+#### Available arguments
+
+The following command tells which arguments/hyperparameters/multipliers are available to be set by the user and which model they are associated with
+
+```shell
+python main_out.py --help
+```
+
+or 
+
+```shell
+domainlab --help
+```
 
 #### Command line
 

From efa469110c20acf2d7779da18f32112d7d135049 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 28 Mar 2024 15:48:46 +0100
Subject: [PATCH 022/273] Update README.md

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index c912b51e6..fdf78faf5 100644
--- a/README.md
+++ b/README.md
@@ -45,7 +45,7 @@ We offer various ways for the user to specify a scenario to evaluate the general
 [Task Specification](./docs/doc_tasks.md) 
 
 ### Example and usage
-#### Available arguments
+#### Available arguments for commandline
 
 The following command tells which arguments/hyperparameters/multipliers are available to be set by the user and which model they are associated with
 
@@ -59,7 +59,7 @@ or
 domainlab --help
 ```
 
-#### Command line
+#### Command line configuration file
 
 `domainlab -c ./examples/conf/vlcs_diva_mldg_dial.yaml` (if you install via pip)
 

From 2d17de491b02a212d1ce79d939ad61f9f1ce75e1 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 28 Mar 2024 17:22:20 +0100
Subject: [PATCH 023/273] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index fdf78faf5..ed031c0b4 100644
--- a/README.md
+++ b/README.md
@@ -55,7 +55,7 @@ python main_out.py --help
 
 or 
 
-```shell
+```
 domainlab --help
 ```
 

From ea20f91f30bc62755dc12d6413b5562bac7cedac Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Wed, 3 Apr 2024 11:28:50 +0200
Subject: [PATCH 024/273] extended usage guide to give a better overview

---
 docs/doc_usage_cmd.md | 119 ++++++++++++++++++++++++++++++++++--------
 1 file changed, 97 insertions(+), 22 deletions(-)

diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index b6320328b..069fcee1f 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -1,17 +1,103 @@
-### Basic usage
-DomainLab comes with some minimal toy-dataset to test its basis functionality, see [A minimal subsample of the VLCS dataset](../data/vlcs_mini) and [an example configuration file for vlcs_mini](../examples/tasks/task_vlcs.py)
+# DomainLab Usage Guide
 
-Suppose you have cloned the repository and have the dependencies ready, change directory to this repository:
+Given the repository and the dependencies are set up, here is how can use DomainLab: 
 
-To train a domain invariant model on the vlcs_mini task
+
+## Essential Commands
+
+To run DomainLab, the minimum necessary parameters are:
+
+1. **Task Specification (```--tpath``` or ```--task```):** This is to specify a task. You can eiter give a path to as Python file which specifies the task, or use a predfined set. You can find more about specifying tasks [here](./doc_tasks.md). 
+2. **Test Domain (```--te_d```):** Specifies the domain(s) used for testing. Can be a single domain or multiple domains.
+3. **Model Selection (```--model```):** Chooses the algorithm or model for the training (e.g., erm, diva). This also includes hyperparameters for the model, e.g., ```--gamma_d``` and ```--gamma_y``` for diva.
+4. **Neural Network (```--nname``` or ```--npath```):** Specifies which neural network is used for feature extraction, either through a path or predefined options. 
+
+### Example Command
+```python3 main_out.py --te_d 0 1 2  --task=mnistcolor10 --model=diva --nname=conv_bn_pool_2  --gamma_y=7e5 --gamma_d=1e5```
+
+
+## Optional Commands
+
+### Advanced Configuration
+
+- **Learning Rate (`--lr`):** Set the training learning rate.
+- **Regularization (`--gamma_reg`):** Weight of regularization loss.
+- **Early Stopping (`--es`):** Steps for early stopping.
+- **Random Seed (`--seed`):** Seed for reproducibility.
+- **CUDA Options (`--nocu`, `--device`):** Configure CUDA usage and device settings.
+- **Generated Images (`--gen`):** Option to save generated images.
+- **Model Preservation (`--keep_model`):** Choose not to delete the model at the end of training.
+- **Epochs (`--epos`, `--epos_min`):** Configure maximum and minimum numbers of epochs.
+- **Test Interval (`--epo_te`):** Set intervals for testing performance.
+- **Hyperparameter Warm-Up (`-w` or `--warmup`):** Epochs for hyperparameter warm-up.
+- **Debugging (`--debug`):** Enable debug mode for verbose output.
+- **Memory Debugging (`--dmem`):** Memory usage debugging.
+- **Output Suppression (`--no_dump`):** Suppress saving the confusion matrix.
+- **Trainer Selection (`--trainer`):** Specify which trainer to use.
+- **Output Directory (`--out`):** Directory to store outputs.
+- **Data Path (`--dpath`):** Path for storing the downloaded dataset.
+- **Additional Neural Network Options:**
+    - Custom Argument Values (`--npath_argna2val`, `--nname_argna2val`)
+    - Domain Feature Extraction Network (`--npath_dom`, `--nname_dom`)
+    - Custom Algorithm Path (`--apath`)
+- **Experiment and Aggregation Tags (`--exptag`, `--aggtag`):** Tags for experiment tracking and result aggregation.
+- **Benchmarking and Plotting:**
+    - Partial Benchmark Aggregation (`--agg_partial_bm`)
+    - Plot Generation (`--gen_plots`, `--outp_dir`, `--param_idx`)
+
+### Task-Specific Arguments
+
+- **Batch Size (`--bs`):** Loader batch size for mixed domains.
+- **Training-Validation Split (`--split`):** Proportion of training, a value between 0 and 1.
+- **Training Domain (`--tr_d`):** Specify training domain names.
+- **Sanity Check (`--san_check`):** Save images from the dataset as a sanity check.
+- **Sanity Check Image Count (`--san_num`):** Number of images for the sanity check.
+- **Logging Level (`--loglevel`):** Set the log level of the logger.
+- **Shuffling (`--shuffling_off`):** Disable shuffling of the training dataloader for the dataset.
+
+### Model-Specific Hyperparameters
+
+#### VAE Model Parameters
+
+- **Latent Space Dimensions (`--zd_dim`, `--zx_dim`, `--zy_dim`):** Set the size of latent spaces for domain, unobserved, and class features.
+- **Topic Dimension (`--topic_dim`):** Number of topics for HDUVA.
+- **Networks for HDUVA Model:**
+    - Image to Topic Distribution (`--nname_encoder_x2topic_h`, `--npath_encoder_x2topic_h`)
+    - Image and Topic to ZD (`--nname_encoder_sandwich_x2h4zd`, `--npath_encoder_sandwich_x2h4zd`)
+- **Hyperparameters for DIVA and HDUVA (`--gamma_y`, `--gamma_d`, `--beta_t`, `--beta_d`, `--beta_x`, `--beta_y`):** Multipliers for various classifiers and loss components.
+
+#### MatchDG Parameters
+
+- **Cosine Similarity Factor (`--tau`):** Magnify cosine similarity.
+- **Match Tensor Update Frequency (`--epos_per_match_update`):** Epochs before updating the match tensor.
+- **Epochs for CTR (`--epochs_ctr`):** Total epochs for CTR.
+
+#### Jigen Parameters
+
+- **Permutation Settings (`--nperm`, `--pperm`, `--jigen_ppath`):** Configure image tile permutations.
+- **Grid Length (`--grid_len`):** Length of image in tile units.
+
+#### DIAL Parameters
+
+- **Adversarial Image Generation (`--dial_steps_perturb`, `--dial_noise_scale`, `--dial_lr`, `--dial_epsilon`):** Configure parameters for generating adversarial images.
+
+
+For a comprehensive understanding of all available commands, use:
+```shell
+python main_out.py --help
+```
+
+## Example
+DomainLab comes with some minimal toy-dataset to test its basis functionality, see [a minimal subsample of the VLCS dataset](../data/vlcs_mini) and [an example configuration file for vlcs_mini](../examples/tasks/task_vlcs.py).
+
+To train a domain invariant model on the vlcs_mini task:
 
 ```shell
 python main_out.py --te_d=caltech --tpath=examples/tasks/task_vlcs.py --config=examples/yaml/demo_config_single_run_diva.yaml
 ```
 where `--tpath` specifies the path of a user specified python file which defines the domain generalization task [see here](../examples/tasks/task_vlcs.py), `--te_d` specifies the test domain name (or index starting from 0), `--config` specifies the configurations of the domain generalization algorithms, [see here](../examples/yaml/demo_config_single_run_diva.yaml)
 
-#### Further usage
-Alternatively, in a verbose mode without using the algorithm configuration file:
+In more detail, in a verbose mode without using the algorithm configuration file:
 
 ```shell
 python main_out.py --te_d=caltech --tpath=examples/tasks/task_vlcs.py --debug --bs=2 --model=diva --gamma_y=7e5 --gamma_d=1e5 --nname=alexnet --nname_dom=conv_bn_pool_2
@@ -19,22 +105,11 @@ python main_out.py --te_d=caltech --tpath=examples/tasks/task_vlcs.py --debug --
 
 where `--model` specifies which algorithm to use, `--bs` specifies the batch size, `--debug` restrain only running for 2 epochs and save results with prefix 'debug'. For DIVA, the hyper-parameters include `--gamma_y=7e5` which is the relative weight of ERM loss compared to ELBO loss, and `--gamma_d=1e5`, which is the relative weight of domain classification loss compared to ELBO loss.
 `--nname` is to specify which neural network to use for feature extraction for classification, `--nname_dom` is to specify which neural network to use for feature extraction of domains.
-For usage of other arguments, check with
-
-```shell
-python main_out.py --help
-```
-
-See also [Examples](./doc_examples.md).
-
-### Custom Neural network
-
-where the user could plugin different neural network architectures for the same algorithm. See
-[Specify Custom Neural Networks for an algorithm](./doc_custom_nn.md)
 
-### Output structure (results storage) and Performance Measure
-[Output structure and Performance Measure](./doc_output.md)
+See [more examples](./doc_examples.md).
 
+## Further Resources
 
-## Software Design Pattern, Extend or Contribution
-[Extend or Contibute](./doc_extend_contribute.md)
+- **Custom Neural Networks:** [Guide on specifying custom neural networks](./doc_custom_nn.md)
+- **Output and Performance:** [Understanding the output structure and performance measures](./doc_output.md)
+- **Extending DomainLab:** [Guide for extending or contributing to DomainLab](./doc_extend_contribute.md)
\ No newline at end of file

From 43aa6ba92902955c147563ac31ee5aceed9e6193 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Wed, 3 Apr 2024 11:58:07 +0200
Subject: [PATCH 025/273] Update doc_usage_cmd.md

---
 docs/doc_usage_cmd.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index 069fcee1f..0dbb16a0f 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -9,7 +9,7 @@ To run DomainLab, the minimum necessary parameters are:
 
 1. **Task Specification (```--tpath``` or ```--task```):** This is to specify a task. You can eiter give a path to as Python file which specifies the task, or use a predfined set. You can find more about specifying tasks [here](./doc_tasks.md). 
 2. **Test Domain (```--te_d```):** Specifies the domain(s) used for testing. Can be a single domain or multiple domains.
-3. **Model Selection (```--model```):** Chooses the algorithm or model for the training (e.g., erm, diva). This also includes hyperparameters for the model, e.g., ```--gamma_d``` and ```--gamma_y``` for diva.
+3. **Model Choice (```--model```):** Chooses the algorithm or model for the training (e.g., erm, diva). This also includes hyperparameters for the model, e.g., ```--gamma_d``` and ```--gamma_y``` for diva.
 4. **Neural Network (```--nname``` or ```--npath```):** Specifies which neural network is used for feature extraction, either through a path or predefined options. 
 
 ### Example Command
@@ -112,4 +112,4 @@ See [more examples](./doc_examples.md).
 
 - **Custom Neural Networks:** [Guide on specifying custom neural networks](./doc_custom_nn.md)
 - **Output and Performance:** [Understanding the output structure and performance measures](./doc_output.md)
-- **Extending DomainLab:** [Guide for extending or contributing to DomainLab](./doc_extend_contribute.md)
\ No newline at end of file
+- **Extending DomainLab:** [Guide for extending or contributing to DomainLab](./doc_extend_contribute.md)

From 7baea73853334c0e3a0d0c7f52588f09664f9a65 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Mon, 15 Apr 2024 12:57:41 +0200
Subject: [PATCH 026/273] fixed issue where hyperparameters are colliding

---
 domainlab/models/a_model.py     |  1 +
 domainlab/models/model_dann.py  |  6 ++++--
 domainlab/models/model_diva.py  | 12 ++++++++----
 domainlab/models/model_hduva.py | 20 +++++++++++---------
 4 files changed, 24 insertions(+), 15 deletions(-)

diff --git a/domainlab/models/a_model.py b/domainlab/models/a_model.py
index beb867167..fdc1c1299 100644
--- a/domainlab/models/a_model.py
+++ b/domainlab/models/a_model.py
@@ -20,6 +20,7 @@ def __init__(self):
         self.list_d_tr = None
         self.visitor = None
         self._net_invar_feat = None
+        self.id = str(id(self)) + "_model"
 
     def extend(self, model):
         """
diff --git a/domainlab/models/model_dann.py b/domainlab/models/model_dann.py
index 2abd3feda..8c74a16bc 100644
--- a/domainlab/models/model_dann.py
+++ b/domainlab/models/model_dann.py
@@ -85,13 +85,15 @@ def hyper_update(self, epoch, fun_scheduler):
             dict_rst = fun_scheduler(
                 epoch
             )  # the __call__ method of hyperparameter scheduler
-            self.alpha = dict_rst["alpha"]
+            self.alpha = dict_rst[self.id + "_alpha"]
 
         def hyper_init(self, functor_scheduler):
             """hyper_init.
             :param functor_scheduler:
             """
-            return functor_scheduler(trainer=None, alpha=self.alpha)
+            parameters = {}
+            parameters[self.id + "_alpha"] = self.alpha
+            return functor_scheduler(trainer=None, **parameters)
 
         def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others):
             _ = others
diff --git a/domainlab/models/model_diva.py b/domainlab/models/model_diva.py
index b67272784..1be0d2613 100644
--- a/domainlab/models/model_diva.py
+++ b/domainlab/models/model_diva.py
@@ -98,9 +98,9 @@ def hyper_update(self, epoch, fun_scheduler):
             :param fun_scheduler:
             """
             dict_rst = fun_scheduler(epoch)
-            self.beta_d = dict_rst["beta_d"]
-            self.beta_y = dict_rst["beta_y"]
-            self.beta_x = dict_rst["beta_x"]
+            self.beta_d = dict_rst[self.id + "_beta_d"]
+            self.beta_y = dict_rst[self.id + "_beta_x"]
+            self.beta_x = dict_rst[self.id + "_beta_y"]
 
         def hyper_init(self, functor_scheduler):
             """
@@ -108,8 +108,12 @@ def hyper_init(self, functor_scheduler):
 
             :param functor_scheduler: the class name of the scheduler
             """
+            parameters = {}
+            parameters[self.id + "_beta_d"] = self.beta_d
+            parameters[self.id + "_beta_y"] = self.beta_y
+            parameters[self.id + "_beta_x"] = self.beta_x
             return functor_scheduler(
-                trainer=None, beta_d=self.beta_d, beta_y=self.beta_y, beta_x=self.beta_x
+                trainer=None, **parameters
             )
 
         def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
diff --git a/domainlab/models/model_hduva.py b/domainlab/models/model_hduva.py
index 61411982e..2a3edd7cb 100644
--- a/domainlab/models/model_hduva.py
+++ b/domainlab/models/model_hduva.py
@@ -66,10 +66,10 @@ def hyper_update(self, epoch, fun_scheduler):
             dict_rst = fun_scheduler(
                 epoch
             )  # the __call__ function of hyper-para-scheduler object
-            self.beta_d = dict_rst["beta_d"]
-            self.beta_y = dict_rst["beta_y"]
-            self.beta_x = dict_rst["beta_x"]
-            self.beta_t = dict_rst["beta_t"]
+            self.beta_d = dict_rst[self.id + "_beta_d"]
+            self.beta_y = dict_rst[self.id + "_beta_y"]
+            self.beta_x = dict_rst[self.id + "_beta_x"]
+            self.beta_t = dict_rst[self.id + "_beta_t"]
 
         def hyper_init(self, functor_scheduler):
             """hyper_init.
@@ -78,12 +78,14 @@ def hyper_init(self, functor_scheduler):
             # calling the constructor of the hyper-parameter-scheduler class, so that this scheduler
             # class build a dictionary {"beta_d":self.beta_d, "beta_y":self.beta_y}
             # constructor signature is def __init__(self, **kwargs):
+            
+            parameters = {}
+            parameters[self.id + "_beta_d"] = self.beta_d
+            parameters[self.id + "_beta_y"] = self.beta_y
+            parameters[self.id + "_beta_x"] = self.beta_x
+            parameters[self.id + "_beta_t"] = self.beta_t
             return functor_scheduler(
-                trainer=None,
-                beta_d=self.beta_d,
-                beta_y=self.beta_y,
-                beta_x=self.beta_x,
-                beta_t=self.beta_t,
+                trainer=None, **parameters
             )
 
         @store_args

From 9690fb460923c353bf1d5f9b069e333cbaaca883 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 16 Apr 2024 13:25:59 +0200
Subject: [PATCH 027/273] new task file and yaml file for mll dataset

---
 .../benchmark/benchmark_blood3_resnet.yaml    | 129 ++++++++++++++++++
 examples/tasks/task_blood3.py                 | 107 +++++++++++++++
 2 files changed, 236 insertions(+)
 create mode 100644 examples/benchmark/benchmark_blood3_resnet.yaml
 create mode 100644 examples/tasks/task_blood3.py

diff --git a/examples/benchmark/benchmark_blood3_resnet.yaml b/examples/benchmark/benchmark_blood3_resnet.yaml
new file mode 100644
index 000000000..a9a1cf0ed
--- /dev/null
+++ b/examples/benchmark/benchmark_blood3_resnet.yaml
@@ -0,0 +1,129 @@
+# test benchmark config.
+
+test_domains:
+  - acevedo
+#- mll
+#- matek
+
+output_dir: zoutput/benchmarks/blood
+# number of hyperparameter samples per task.
+# Thus, the total runs of each task are given
+# by len(domains) * num_param_samples * num_seeds (see below)
+num_param_samples: 8
+sampling_seed: 0
+
+startseed: 0
+endseed: 5  # currently included
+
+
+
+domainlab_args:
+  # Domainlab arguments passed to each task.
+  # task specific arguments take precedence.
+  ## dataset
+  tpath: examples/tasks/task_blood3.py
+  dmem: False
+  lr: 5e-5
+  epos: 500
+  epos_min: 20
+  es: 1
+  bs: 32
+  npath: examples/nets/resnet50domainbed.py
+  san_check: True
+
+Shared params:
+  num_shared_param_samples: 8
+  gamma_y:
+    min: 1e4
+    max: 2e5
+    step: 100
+    distribution: loguniform
+
+  zx_dim:
+    min: 0
+    max: 96
+    step: 32
+    distribution: uniform
+    datatype: int
+
+  zy_dim:
+    min: 32
+    max: 96
+    step: 32
+    distribution: uniform
+    datatype: int
+
+  zd_dim:
+    reference: zy_dim
+
+  gamma_reg:
+    min: 0.01
+    max: 10
+    distribution: loguniform
+
+
+
+diva:  # name
+  model: diva
+  # set nname_dom = nname when changing nname
+  npath_dom: examples/nets/resnet50domainbed.py
+  shared:
+    - gamma_y
+    - zx_dim
+    - zy_dim
+    - zd_dim
+
+  hyperparameters:
+    gamma_d:
+      min: 1e4
+      max: 1e6
+      step: 10_000
+      distribution: loguniform
+
+hduva:  # name
+  model: hduva
+
+  npath_encoder_x2topic_h: examples/nets/resnet50domainbed.py
+  npath_encoder_sandwich_x2h4zd: examples/nets/resnet50domainbed.py
+  shared:
+    - gamma_y
+    - zx_dim
+    - zy_dim
+    - zd_dim
+
+erm:  # name
+  model: erm
+
+mldg:
+  model: erm
+  trainer: mldg
+  shared:
+    - gamma_reg
+
+dann:
+  model: dann
+  shared:
+    - gamma_reg
+
+
+dial: # name
+  model: erm
+  trainer: dial
+  shared:
+    - gamma_reg
+  hyperparameters:
+    dial_steps_perturb:
+      min: 1
+      max: 10
+      step: 1
+      distribution: uniform
+
+    dial_noise_scale:
+      min: 0.00001
+      max: 0.1
+      distribution: loguniform
+
+    dial_epsilon:
+      min: 0.001
+      max: 0.01
+      distribution: loguniform
diff --git a/examples/tasks/task_blood3.py b/examples/tasks/task_blood3.py
new file mode 100644
index 000000000..a1d03b78d
--- /dev/null
+++ b/examples/tasks/task_blood3.py
@@ -0,0 +1,107 @@
+"""
+difference than task_blood2.py:
+
+"mll": "/lustre/groups/labs/marr/qscd01/datasets/240416_MLL23",
+
+"""
+from torchvision import transforms
+
+from domainlab.tasks.task_folder_mk import mk_task_folder
+from domainlab.tasks.utils_task import ImSize
+
+IMG_SIZE = 224
+
+trans = transforms.Compose(
+    [
+        transforms.Resize((IMG_SIZE, IMG_SIZE)),
+        transforms.RandomResizedCrop(IMG_SIZE, scale=(0.7, 1.0)),
+        transforms.RandomHorizontalFlip(),
+        transforms.ColorJitter(0.3, 0.3, 0.3, 0.3),
+        transforms.RandomGrayscale(),
+        transforms.ToTensor(),
+        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
+    ]
+)
+
+trans_te = transforms.Compose(
+    [
+        transforms.Resize((IMG_SIZE, IMG_SIZE)),
+        transforms.ToTensor(),
+        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
+    ]
+)
+
+
+TASK = mk_task_folder(
+    extensions={"acevedo": "jpg", "matek": "tiff", "mll": "tif"},
+    list_str_y=[
+        "basophil",
+        "erythroblast",
+        "metamyelocyte",
+        "myeloblast",
+        "neutrophil_band",
+        "promyelocyte",
+        "eosinophil",
+        "lymphocyte_typical",
+        "monocyte",
+        "myelocyte",
+        "neutrophil_segmented",
+    ],
+    dict_domain_folder_name2class={
+        "acevedo": {
+            "basophil": "basophil",
+            "erythroblast": "erythroblast",
+            "metamyelocyte": "metamyelocyte",
+            "neutrophil_band": "neutrophil_band",
+            "promyelocyte": "promyelocyte",
+            "eosinophil": "eosinophil",
+            "lymphocyte_typical": "lymphocyte_typical",
+            "monocyte": "monocyte",
+            "myelocyte": "myelocyte",
+            "neutrophil_segmented": "neutrophil_segmented",
+        },
+        "matek": {
+            "basophil": "basophil",
+            "erythroblast": "erythroblast",
+            "metamyelocyte": "metamyelocyte",
+            "myeloblast": "myeloblast",
+            "neutrophil_band": "neutrophil_band",
+            "promyelocyte": "promyelocyte",
+            "eosinophil": "eosinophil",
+            "lymphocyte_typical": "lymphocyte_typical",
+            "monocyte": "monocyte",
+            "myelocyte": "myelocyte",
+            "neutrophil_segmented": "neutrophil_segmented",
+        },
+        "mll": {
+            "basophil": "basophil",
+            "erythroblast": "erythroblast",
+            "metamyelocyte": "metamyelocyte",
+            "myeloblast": "myeloblast",
+            "neutrophil_band": "neutrophil_band",
+            "promyelocyte": "promyelocyte",
+            "eosinophil": "eosinophil",
+            "lymphocyte_typical": "lymphocyte_typical",
+            "monocyte": "monocyte",
+            "myelocyte": "myelocyte",
+            "neutrophil_segmented": "neutrophil_segmented",
+        },
+    },
+    dict_domain_img_trans={
+        "acevedo": trans,
+        "mll": trans,
+        "matek": trans,
+    },
+    img_trans_te=trans_te,
+    isize=ImSize(3, IMG_SIZE, IMG_SIZE),
+    dict_domain2imgroot={
+        "matek": "/lustre/groups/labs/marr/qscd01/datasets/armingruber/_Domains/Matek_cropped",
+        "mll": "/lustre/groups/labs/marr/qscd01/datasets/240416_MLL23",
+        "acevedo": "/lustre/groups/labs/marr/qscd01/datasets/armingruber/_Domains/Acevedo_cropped",
+    },
+    taskna="blood_mon_eos_bas",
+)
+
+
+def get_task(na=None):
+    return TASK

From 07086a2389ff6e90a14e13dbd25d4dd7921fa317 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 16 Apr 2024 17:01:53 +0200
Subject: [PATCH 028/273] changed id to name for model identification

---
 domainlab/models/a_model.py     | 25 ++++++++++++++++++++++++-
 domainlab/models/model_dann.py  |  4 ++--
 domainlab/models/model_diva.py  | 12 ++++++------
 domainlab/models/model_hduva.py | 17 ++++++++---------
 4 files changed, 40 insertions(+), 18 deletions(-)

diff --git a/domainlab/models/a_model.py b/domainlab/models/a_model.py
index fdc1c1299..b53800b8e 100644
--- a/domainlab/models/a_model.py
+++ b/domainlab/models/a_model.py
@@ -20,7 +20,6 @@ def __init__(self):
         self.list_d_tr = None
         self.visitor = None
         self._net_invar_feat = None
-        self.id = str(id(self)) + "_model"
 
     def extend(self, model):
         """
@@ -179,3 +178,27 @@ def dset_decoration_args_algo(self, args, ddset):
         if self._decoratee is not None:
             return self._decoratee.dset_decoration_args_algo(args, ddset)
         return ddset
+    
+    @property
+    def p_na_prefix(self):
+        """
+        common prefix for Models
+        """
+        return "Model"
+
+    @property
+    def name(self):
+        """
+        get the name of the algorithm
+        """
+        na_prefix = self.p_na_prefix
+        len_prefix = len(na_prefix)
+        na_class = type(self).__name__
+        if na_class[:len_prefix] != na_prefix:
+            raise RuntimeError(
+                "Trainer builder node class must start with ",
+                na_prefix,
+                "the current class is named: ",
+                na_class,
+            )
+        return type(self).__name__[len_prefix:].lower()
diff --git a/domainlab/models/model_dann.py b/domainlab/models/model_dann.py
index 8c74a16bc..59a619e7e 100644
--- a/domainlab/models/model_dann.py
+++ b/domainlab/models/model_dann.py
@@ -85,14 +85,14 @@ def hyper_update(self, epoch, fun_scheduler):
             dict_rst = fun_scheduler(
                 epoch
             )  # the __call__ method of hyperparameter scheduler
-            self.alpha = dict_rst[self.id + "_alpha"]
+            self.alpha = dict_rst[self.name + "_alpha"]
 
         def hyper_init(self, functor_scheduler):
             """hyper_init.
             :param functor_scheduler:
             """
             parameters = {}
-            parameters[self.id + "_alpha"] = self.alpha
+            parameters[self.name + "_alpha"] = self.alpha
             return functor_scheduler(trainer=None, **parameters)
 
         def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others):
diff --git a/domainlab/models/model_diva.py b/domainlab/models/model_diva.py
index 1be0d2613..362c14518 100644
--- a/domainlab/models/model_diva.py
+++ b/domainlab/models/model_diva.py
@@ -98,9 +98,9 @@ def hyper_update(self, epoch, fun_scheduler):
             :param fun_scheduler:
             """
             dict_rst = fun_scheduler(epoch)
-            self.beta_d = dict_rst[self.id + "_beta_d"]
-            self.beta_y = dict_rst[self.id + "_beta_x"]
-            self.beta_x = dict_rst[self.id + "_beta_y"]
+            self.beta_d = dict_rst[self.name + "_beta_d"]
+            self.beta_y = dict_rst[self.name + "_beta_x"]
+            self.beta_x = dict_rst[self.name + "_beta_y"]
 
         def hyper_init(self, functor_scheduler):
             """
@@ -109,9 +109,9 @@ def hyper_init(self, functor_scheduler):
             :param functor_scheduler: the class name of the scheduler
             """
             parameters = {}
-            parameters[self.id + "_beta_d"] = self.beta_d
-            parameters[self.id + "_beta_y"] = self.beta_y
-            parameters[self.id + "_beta_x"] = self.beta_x
+            parameters[self.name + "_beta_d"] = self.beta_d
+            parameters[self.name + "_beta_y"] = self.beta_y
+            parameters[self.name + "_beta_x"] = self.beta_x
             return functor_scheduler(
                 trainer=None, **parameters
             )
diff --git a/domainlab/models/model_hduva.py b/domainlab/models/model_hduva.py
index 2a3edd7cb..5c7bb290d 100644
--- a/domainlab/models/model_hduva.py
+++ b/domainlab/models/model_hduva.py
@@ -66,10 +66,10 @@ def hyper_update(self, epoch, fun_scheduler):
             dict_rst = fun_scheduler(
                 epoch
             )  # the __call__ function of hyper-para-scheduler object
-            self.beta_d = dict_rst[self.id + "_beta_d"]
-            self.beta_y = dict_rst[self.id + "_beta_y"]
-            self.beta_x = dict_rst[self.id + "_beta_x"]
-            self.beta_t = dict_rst[self.id + "_beta_t"]
+            self.beta_d = dict_rst[self.name + "_beta_d"]
+            self.beta_y = dict_rst[self.name + "_beta_y"]
+            self.beta_x = dict_rst[self.name + "_beta_x"]
+            self.beta_t = dict_rst[self.name + "_beta_t"]
 
         def hyper_init(self, functor_scheduler):
             """hyper_init.
@@ -78,12 +78,11 @@ def hyper_init(self, functor_scheduler):
             # calling the constructor of the hyper-parameter-scheduler class, so that this scheduler
             # class build a dictionary {"beta_d":self.beta_d, "beta_y":self.beta_y}
             # constructor signature is def __init__(self, **kwargs):
-            
             parameters = {}
-            parameters[self.id + "_beta_d"] = self.beta_d
-            parameters[self.id + "_beta_y"] = self.beta_y
-            parameters[self.id + "_beta_x"] = self.beta_x
-            parameters[self.id + "_beta_t"] = self.beta_t
+            parameters[self.name + "_beta_d"] = self.beta_d
+            parameters[self.name + "_beta_y"] = self.beta_y
+            parameters[self.name + "_beta_x"] = self.beta_x
+            parameters[self.name + "_beta_t"] = self.beta_t
             return functor_scheduler(
                 trainer=None, **parameters
             )

From 566ee2c5f609cbb651c897d2edbcc84160a788fa Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 17 Apr 2024 09:38:37 +0200
Subject: [PATCH 029/273] new mll dataset

---
 examples/tasks/task_blood3.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/tasks/task_blood3.py b/examples/tasks/task_blood3.py
index a1d03b78d..e14505197 100644
--- a/examples/tasks/task_blood3.py
+++ b/examples/tasks/task_blood3.py
@@ -75,13 +75,13 @@
         },
         "mll": {
             "basophil": "basophil",
-            "erythroblast": "erythroblast",
+            "erythroblast": "nomoblast",
             "metamyelocyte": "metamyelocyte",
             "myeloblast": "myeloblast",
             "neutrophil_band": "neutrophil_band",
             "promyelocyte": "promyelocyte",
             "eosinophil": "eosinophil",
-            "lymphocyte_typical": "lymphocyte_typical",
+            "lymphocyte_typical": "lymphocyte",
             "monocyte": "monocyte",
             "myelocyte": "myelocyte",
             "neutrophil_segmented": "neutrophil_segmented",

From d9c8a623131e3c68871a36883b3294c93c2f5a45 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Wed, 17 Apr 2024 15:53:36 +0200
Subject: [PATCH 030/273] Update task_blood3.py

---
 examples/tasks/task_blood3.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/tasks/task_blood3.py b/examples/tasks/task_blood3.py
index e14505197..416eb893e 100644
--- a/examples/tasks/task_blood3.py
+++ b/examples/tasks/task_blood3.py
@@ -75,7 +75,7 @@
         },
         "mll": {
             "basophil": "basophil",
-            "erythroblast": "nomoblast",
+            "erythroblast": "normoblast",
             "metamyelocyte": "metamyelocyte",
             "myeloblast": "myeloblast",
             "neutrophil_band": "neutrophil_band",

From 871374a407b0e75d5dba28478b1eab0a3cdf2b61 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Mon, 22 Apr 2024 11:34:25 +0200
Subject: [PATCH 031/273] Solved gamma_reg naming collision by introducing
 functionality to pass different gamma values for different trainers and
 models based on the naming of the class. Also added parameter printing

---
 docs/doc_usage_cmd.md                       | 20 +++++++++++++--
 domainlab/algos/builder_dann.py             |  3 ++-
 domainlab/algos/builder_jigen1.py           |  3 ++-
 domainlab/algos/trainers/a_trainer.py       |  7 ++++++
 domainlab/algos/trainers/train_dial.py      |  3 ++-
 domainlab/algos/trainers/train_fishr.py     |  3 ++-
 domainlab/algos/trainers/train_matchdg.py   |  3 ++-
 domainlab/algos/trainers/train_mldg.py      |  3 ++-
 domainlab/arg_parser.py                     | 18 +++++++++++++-
 domainlab/models/a_model.py                 |  7 ++++++
 domainlab/utils/hyperparameter_retrieval.py | 20 +++++++++++++++
 examples/conf/vlcs_diva_mldg_dial.yaml      |  5 +++-
 tests/test_hyperparameter_retrieval.py      | 27 +++++++++++++++++++++
 13 files changed, 112 insertions(+), 10 deletions(-)
 create mode 100644 domainlab/utils/hyperparameter_retrieval.py
 create mode 100644 tests/test_hyperparameter_retrieval.py

diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index 0dbb16a0f..e8e2f2480 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -21,8 +21,24 @@ To run DomainLab, the minimum necessary parameters are:
 ### Advanced Configuration
 
 - **Learning Rate (`--lr`):** Set the training learning rate.
-- **Regularization (`--gamma_reg`):** Weight of regularization loss.
-- **Early Stopping (`--es`):** Steps for early stopping.
+- **Regularization (`--gamma_reg`):** Sets the weight of the regularization loss. This parameter can be configured either as a single value applied to individual classes, or using a dictionary to specify different weights for different models and trainers.
+
+  - **Command Line Usage:**
+    - For a single value: `python script.py --gamma_reg=0.1`
+    - For multiple values: `python script.py --gamma_reg='default=0.1,dann=0.05,diva=0.2'`
+
+  - **YAML Configuration:**
+    - For a single value:
+      ```yaml
+      gamma_reg: 0.1
+      ```
+    - For different values:
+      ```yaml
+      gamma_reg:
+        default: 0.1 # every other instance that is not listed below will get this value assigned
+        dann: 0.05
+        diva: 0.2
+      ```- **Early Stopping (`--es`):** Steps for early stopping.
 - **Random Seed (`--seed`):** Seed for reproducibility.
 - **CUDA Options (`--nocu`, `--device`):** Configure CUDA usage and device settings.
 - **Generated Images (`--gen`):** Option to save generated images.
diff --git a/domainlab/algos/builder_dann.py b/domainlab/algos/builder_dann.py
index 65b26a62a..73b373c15 100644
--- a/domainlab/algos/builder_dann.py
+++ b/domainlab/algos/builder_dann.py
@@ -13,6 +13,7 @@
 from domainlab.compos.zoo_nn import FeatExtractNNBuilderChainNodeGetter
 from domainlab.models.model_dann import mk_dann
 from domainlab.utils.utils_cuda import get_device
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class NodeAlgoBuilderDANN(NodeAlgoBuilder):
@@ -55,7 +56,7 @@ def init_business(self, exp):
         model = mk_dann(list_str_y=task.list_str_y,
                         net_classifier=net_classifier)(
             list_d_tr=task.list_domain_tr,
-            alpha=args.gamma_reg,
+            alpha=get_gamma_reg(args, 'dann'),
             net_encoder=net_encoder,
             net_discriminator=net_discriminator,
             builder=self)
diff --git a/domainlab/algos/builder_jigen1.py b/domainlab/algos/builder_jigen1.py
index e899e32f2..de671affe 100644
--- a/domainlab/algos/builder_jigen1.py
+++ b/domainlab/algos/builder_jigen1.py
@@ -15,6 +15,7 @@
 from domainlab.dsets.utils_wrapdset_patches import WrapDsetPatches
 from domainlab.models.model_jigen import mk_jigen
 from domainlab.utils.utils_cuda import get_device
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class NodeAlgoBuilderJiGen(NodeAlgoBuilder):
@@ -56,7 +57,7 @@ def init_business(self, exp):
         model = mk_jigen(
             list_str_y=task.list_str_y,
             net_classifier=net_classifier)(
-            coeff_reg=args.gamma_reg,
+            coeff_reg=get_gamma_reg(args, 'jigen'),
             net_encoder=net_encoder,
             net_classifier_permutation=net_classifier_perm,
             n_perm=args.nperm,
diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 9bc126705..8d06a448e 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -256,3 +256,10 @@ def dset_decoration_args_algo(self, args, ddset):
         if self._decoratee is not None:
             return self._decoratee.dset_decoration_args_algo(args, ddset)
         return ddset
+    
+    def print_parameters(self):
+        """
+        Function to print all parameters of the object. Can also be used to print the parameters of the child classes
+        """
+        params = vars(self)
+        print(f"Parameters of {type(self).__name__}: {params}")
diff --git a/domainlab/algos/trainers/train_dial.py b/domainlab/algos/trainers/train_dial.py
index 75a5e34f0..4fe700f45 100644
--- a/domainlab/algos/trainers/train_dial.py
+++ b/domainlab/algos/trainers/train_dial.py
@@ -5,6 +5,7 @@
 from torch.autograd import Variable
 
 from domainlab.algos.trainers.train_basic import TrainerBasic
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class TrainerDIAL(TrainerBasic):
@@ -49,4 +50,4 @@ def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         tensor_x_adv = self.gen_adversarial(self.device, tensor_x, tensor_y)
         tensor_x_batch_adv_no_grad = Variable(tensor_x_adv, requires_grad=False)
         loss_dial = self.model.cal_task_loss(tensor_x_batch_adv_no_grad, tensor_y)
-        return [loss_dial], [self.aconf.gamma_reg]
+        return [loss_dial], [get_gamma_reg(self.aconf, self.name)]
diff --git a/domainlab/algos/trainers/train_fishr.py b/domainlab/algos/trainers/train_fishr.py
index 1a11e3780..3580a0721 100644
--- a/domainlab/algos/trainers/train_fishr.py
+++ b/domainlab/algos/trainers/train_fishr.py
@@ -13,6 +13,7 @@
     backpack = None
 
 from domainlab.algos.trainers.train_basic import TrainerBasic
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class TrainerFishr(TrainerBasic):
@@ -39,7 +40,7 @@ def tr_epoch(self, epoch):
             dict_layerwise_var_var_grads_sum = \
                 {key: val.sum() for key, val in dict_layerwise_var_var_grads.items()}
             loss_fishr = sum(dict_layerwise_var_var_grads_sum.values())
-            loss = sum(list_loss_erm) + self.aconf.gamma_reg * loss_fishr
+            loss = sum(list_loss_erm) + get_gamma_reg(self.aconf, self.name) * loss_fishr
             loss.backward()
             self.optimizer.step()
             self.epo_loss_tr += loss.detach().item()
diff --git a/domainlab/algos/trainers/train_matchdg.py b/domainlab/algos/trainers/train_matchdg.py
index 6a3edd996..72c14ab83 100644
--- a/domainlab/algos/trainers/train_matchdg.py
+++ b/domainlab/algos/trainers/train_matchdg.py
@@ -13,6 +13,7 @@
 )
 from domainlab.tasks.utils_task_dset import DsetIndDecorator4XYD
 from domainlab.utils.logger import Logger
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class TrainerMatchDG(AbstractTrainer):
@@ -36,7 +37,7 @@ def init_business(
         self.base_domain_size = get_base_domain_size4match_dg(self.task)
         self.epo_loss_tr = 0
         self.flag_erm = flag_erm
-        self.lambda_ctr = self.aconf.gamma_reg
+        self.lambda_ctr = get_gamma_reg(aconf, self.name)
         self.mk_match_tensor(epoch=0)
         self.flag_match_tensor_sweep_over = False
         self.tuple_tensor_ref_domain2each_y = None
diff --git a/domainlab/algos/trainers/train_mldg.py b/domainlab/algos/trainers/train_mldg.py
index 90318286c..e91310adf 100644
--- a/domainlab/algos/trainers/train_mldg.py
+++ b/domainlab/algos/trainers/train_mldg.py
@@ -10,6 +10,7 @@
 from domainlab.algos.trainers.train_basic import TrainerBasic
 from domainlab.tasks.utils_task import mk_loader
 from domainlab.tasks.utils_task_dset import DsetZip
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class TrainerMLDG(AbstractTrainer):
@@ -108,7 +109,7 @@ def tr_epoch(self, epoch):
             loss = (
                 loss_source_task.sum()
                 + source_reg_tr.sum()
-                + self.aconf.gamma_reg * loss_look_forward.sum()
+                + get_gamma_reg(self.aconf, self.name) * loss_look_forward.sum()
             )
             #
             loss.backward()
diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index 7c7e004e7..eb8c6836c 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -12,6 +12,19 @@
 from domainlab.models.args_vae import add_args2parser_vae
 from domainlab.utils.logger import Logger
 
+class StoreDictKeyPair(argparse.Action):
+    def __call__(self, parser, namespace, values, option_string=None):
+        try:
+            if "=" in values:
+                my_dict = {}
+                for kv in values.split(","):
+                    k, v = kv.split("=")
+                    my_dict[k.strip()] = float(v.strip())  # Assuming values are floats
+                setattr(namespace, self.dest, my_dict)
+            else:
+                setattr(namespace, self.dest, float(values))  # Single float value
+        except ValueError:
+            raise argparse.ArgumentError(self, f"Invalid value for {self.dest}: {values}")
 
 def mk_parser_main():
     """
@@ -31,7 +44,10 @@ def mk_parser_main():
     parser.add_argument("--lr", type=float, default=1e-4, help="learning rate")
 
     parser.add_argument(
-        "--gamma_reg", type=float, default=0.1, help="weight of regularization loss"
+        "--gamma_reg",
+        default=0.1,
+        help="weight of regularization loss, can specify per model as 'dann=1.0,diva=2.0'",
+        action=StoreDictKeyPair
     )
 
     parser.add_argument("--es", type=int, default=1, help="early stop steps")
diff --git a/domainlab/models/a_model.py b/domainlab/models/a_model.py
index b53800b8e..6ea45747f 100644
--- a/domainlab/models/a_model.py
+++ b/domainlab/models/a_model.py
@@ -202,3 +202,10 @@ def name(self):
                 na_class,
             )
         return type(self).__name__[len_prefix:].lower()
+    
+    def print_parameters(self):
+        """
+        Function to print all parameters of the object. Can also be used to print the parameters of the child classes
+        """
+        params = vars(self)
+        print(f"Parameters of {type(self).__name__}: {params}")
diff --git a/domainlab/utils/hyperparameter_retrieval.py b/domainlab/utils/hyperparameter_retrieval.py
new file mode 100644
index 000000000..8e49c356c
--- /dev/null
+++ b/domainlab/utils/hyperparameter_retrieval.py
@@ -0,0 +1,20 @@
+"""
+retrieval for hyperparameters
+"""
+
+def get_gamma_reg(args, model_name):
+    """
+    Retrieves either a shared gamma regularization, or individual ones for each specified object
+    """
+    gamma_reg = args.gamma_reg
+    print(gamma_reg)
+    if isinstance(gamma_reg, dict):
+        print("is instance dict")
+        if model_name in gamma_reg: 
+            return gamma_reg[model_name]  
+        elif 'default' in gamma_reg: 
+            return gamma_reg['default']
+        else: 
+            raise ValueError("If a gamma_reg dict is specified, but no value set for every model and trainer, a default value must be specified.")
+    else: 
+        return gamma_reg  # Return the single value if it's not a dictionary
diff --git a/examples/conf/vlcs_diva_mldg_dial.yaml b/examples/conf/vlcs_diva_mldg_dial.yaml
index ac2d83337..5cf1a8041 100644
--- a/examples/conf/vlcs_diva_mldg_dial.yaml
+++ b/examples/conf/vlcs_diva_mldg_dial.yaml
@@ -5,7 +5,10 @@ val_threshold: 0.8
 model: dann_diva                    # combine model DANN with DIVA
 epos: 1                             # number of epochs
 trainer: mldg_dial                  # combine trainer MLDG and DIAL
-gamma_reg: 1.0                      # hyperparameter of DANN
+gamma_reg: 
+  default: 1.0
+  dann: 1.5                        
+  diva: 2.0
 gamma_y: 700000.0                   # hyperparameter of diva
 gamma_d: 100000.0                   # hyperparameter of diva
 npath: examples/nets/resnet.py      # neural network for class classification
diff --git a/tests/test_hyperparameter_retrieval.py b/tests/test_hyperparameter_retrieval.py
new file mode 100644
index 000000000..192343617
--- /dev/null
+++ b/tests/test_hyperparameter_retrieval.py
@@ -0,0 +1,27 @@
+# Assume imports and any necessary setup are already done
+import argparse
+from domainlab.arg_parser import StoreDictKeyPair, mk_parser_main
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
+
+def test_store_dict_key_pair_single_value():
+    parser = mk_parser_main()
+    args = parser.parse_args(['--gamma_reg', '0.5'])
+    assert args.gamma_reg == 0.5
+
+def test_store_dict_key_pair_dict_value():
+    parser = mk_parser_main()
+    args = parser.parse_args(['--gamma_reg', 'dann=1.0,diva=2.0'])
+    assert args.gamma_reg == {'dann': 1.0, 'diva': 2.0}
+
+def test_get_gamma_reg_single_value():
+    parser = mk_parser_main()
+    args = parser.parse_args(['--gamma_reg', '0.5'])
+    assert get_gamma_reg(args, 'dann') == 0.5
+
+def test_get_gamma_reg_dict_value():
+    parser = mk_parser_main()
+    args = parser.parse_args(['--gamma_reg', 'default=5.0,dann=1.0,diva=2.0'])
+    print(args)
+    assert get_gamma_reg(args, 'dann') == 1.0
+    assert get_gamma_reg(args, 'diva') == 2.0
+    assert get_gamma_reg(args, 'nonexistent') == 5.0

From cf1d834fe0a578b8dec1f187345fdf2c0df3c3be Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Mon, 22 Apr 2024 16:29:18 +0200
Subject: [PATCH 032/273] changed path from data to domainlab/zdata

---
 .gitignore                                    |  2 +-
 docs/doc_tasks.md                             |  2 +-
 docs/doc_usage_cmd.md                         |  2 +-
 .../ztest_files/test_parameter_samples.csv    |  2 +-
 examples/tasks/demo_task_path_list_small.py   | 32 +++++++++----------
 examples/tasks/task_pacs_aug.py               | 28 ++++++++--------
 .../tasks/task_pacs_aug_noflip_no_zoom.py     | 28 ++++++++--------
 examples/tasks/task_pacs_no_aug_norm_only.py  | 28 ++++++++--------
 examples/tasks/task_pacs_path_list.py         | 28 ++++++++--------
 examples/tasks/task_vlcs.py                   |  6 ++--
 scripts/sh_link_pacs_dataset.sh               |  4 +--
 sh_download_pacs.sh                           |  6 ++--
 tests/dset_subfolder_test.py                  | 12 +++----
 tests/dset_utils_data_test.py                 |  2 +-
 tests/test_benchmark_plots.py                 |  4 +--
 tests/test_exp_protocol.py                    |  2 +-
 tests/test_git_tag.py                         |  6 ++--
 tests/test_run_experiment.py                  |  6 ++--
 tests/test_task_folder.py                     | 30 ++++++++---------
 19 files changed, 115 insertions(+), 115 deletions(-)
 mode change 100644 => 100755 sh_download_pacs.sh

diff --git a/.gitignore b/.gitignore
index edfe19c37..2e1aa7a74 100644
--- a/.gitignore
+++ b/.gitignore
@@ -4,4 +4,4 @@
 tests/__pycache__/
 *.pyc
 .vscode/
-data/pacs
+domainlab/zdata/pacs
diff --git a/docs/doc_tasks.md b/docs/doc_tasks.md
index 3d3f0d73d..1d37bc385 100644
--- a/docs/doc_tasks.md
+++ b/docs/doc_tasks.md
@@ -17,7 +17,7 @@ here in the example, 3 domains are defined to be named "domain1", "domain2", "do
 ## Possibility 2: TaskPathList
 The user need to provide a python file indicating the root directories where images (data) from  each domain are located, and for each domain, the user shall provide a plain text file indicating the file names.
 
-An example python file can be found in the [examples directory of the repository](https://github.com/marrlab/DomainLab/blob/master/examples/tasks/demo_task_path_list_small.py) with the corresponding data be found at [the data directory of the repository](https://github.com/marrlab/DomainLab/tree/master/data), where the text file indicating which file correspond to which class label (starting from 1) can be found at [example text file](https://github.com/marrlab/DomainLab/blob/master/data/pacs_split/art_painting_10.txt).
+An example python file can be found in the [examples directory of the repository](https://github.com/marrlab/DomainLab/blob/master/examples/tasks/demo_task_path_list_small.py) with the corresponding data be found at [the data directory of the repository](https://github.com/marrlab/DomainLab/tree/master/domainlab/zdata), where the text file indicating which file correspond to which class label (starting from 1) can be found at [example text file](https://github.com/marrlab/DomainLab/blob/master/domainlab/zdata/pacs_split/art_painting_10.txt).
 The user should specify the location of the python file via command line arguments `--tpath`
 
 ```shell
diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index 0dbb16a0f..7230fec25 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -88,7 +88,7 @@ python main_out.py --help
 ```
 
 ## Example
-DomainLab comes with some minimal toy-dataset to test its basis functionality, see [a minimal subsample of the VLCS dataset](../data/vlcs_mini) and [an example configuration file for vlcs_mini](../examples/tasks/task_vlcs.py).
+DomainLab comes with some minimal toy-dataset to test its basis functionality, see [a minimal subsample of the VLCS dataset](./zdata/vlcs_mini) and [an example configuration file for vlcs_mini](../examples/tasks/task_vlcs.py).
 
 To train a domain invariant model on the vlcs_mini task:
 
diff --git a/domainlab/zdata/ztest_files/test_parameter_samples.csv b/domainlab/zdata/ztest_files/test_parameter_samples.csv
index 609864f2f..e3ebdbf4a 100644
--- a/domainlab/zdata/ztest_files/test_parameter_samples.csv
+++ b/domainlab/zdata/ztest_files/test_parameter_samples.csv
@@ -1,2 +1,2 @@
-,task,algo,params
+,method,model,params
 0,diva,diva,"{'gamma_y': 10e5, 'gamma_d': 1e5}"
diff --git a/examples/tasks/demo_task_path_list_small.py b/examples/tasks/demo_task_path_list_small.py
index 92425774a..af8e469a4 100644
--- a/examples/tasks/demo_task_path_list_small.py
+++ b/examples/tasks/demo_task_path_list_small.py
@@ -31,31 +31,31 @@ def get_task(na=None):
         # ## the text file below only need to specify the relative path
         # ## training
         dict_d2filepath_list_img_tr={
-            "art_painting": "data/pacs_split/art_painting_10.txt",
-            "cartoon": "data/pacs_split/cartoon_10.txt",
-            "photo": "data/pacs_split/photo_10.txt",
-            "sketch": "data/pacs_split/sketch_10.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_10.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_10.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_10.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_10.txt",
         },
         # ## testing
         dict_d2filepath_list_img_te={
-            "art_painting": "data/pacs_split/art_painting_10.txt",
-            "cartoon": "data/pacs_split/cartoon_10.txt",
-            "photo": "data/pacs_split/photo_10.txt",
-            "sketch": "data/pacs_split/sketch_10.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_10.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_10.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_10.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_10.txt",
         },
         # ## validation
         dict_d2filepath_list_img_val={
-            "art_painting": "data/pacs_split/art_painting_10.txt",
-            "cartoon": "data/pacs_split/cartoon_10.txt",
-            "photo": "data/pacs_split/photo_10.txt",
-            "sketch": "data/pacs_split/sketch_10.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_10.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_10.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_10.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_10.txt",
         },
         # ## specify root folder storing the images of each domain:
         dict_domain2imgroot={
-            "art_painting": "data/pacs_mini_10",
-            "cartoon": "data/pacs_mini_10",
-            "photo": "data/pacs_mini_10",
-            "sketch": "data/pacs_mini_10",
+            "art_painting": "domainlab/zdata/pacs_mini_10",
+            "cartoon": "domainlab/zdata/pacs_mini_10",
+            "photo": "domainlab/zdata/pacs_mini_10",
+            "sketch": "domainlab/zdata/pacs_mini_10",
         },
         # ## specify the pytorch transformation you want to apply to the image
         img_trans_tr=transforms.Compose(
diff --git a/examples/tasks/task_pacs_aug.py b/examples/tasks/task_pacs_aug.py
index 6fc092dca..be6b84e27 100644
--- a/examples/tasks/task_pacs_aug.py
+++ b/examples/tasks/task_pacs_aug.py
@@ -11,8 +11,8 @@
 from domainlab.tasks.utils_task import ImSize
 
 # change this to absolute directory where you have the raw images from PACS,
-G_PACS_RAW_PATH = "data/pacs/PACS"
-# domainlab repository contain already the file names in data/pacs_split folder of domainlab
+G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
+# domainlab repository contain already the file names in domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
@@ -29,22 +29,22 @@ def get_task(na=None):
             "7": "person",
         },
         dict_d2filepath_list_img_tr={
-            "art_painting": "data/pacs_split/art_painting_train_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_train_kfold.txt",
-            "photo": "data/pacs_split/photo_train_kfold.txt",
-            "sketch": "data/pacs_split/sketch_train_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_train_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_train_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_train_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_train_kfold.txt",
         },
         dict_d2filepath_list_img_te={
-            "art_painting": "data/pacs_split/art_painting_test_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_test_kfold.txt",
-            "photo": "data/pacs_split/photo_test_kfold.txt",
-            "sketch": "data/pacs_split/sketch_test_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_test_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_test_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_test_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_test_kfold.txt",
         },
         dict_d2filepath_list_img_val={
-            "art_painting": "data/pacs_split/art_painting_crossval_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_crossval_kfold.txt",
-            "photo": "data/pacs_split/photo_crossval_kfold.txt",
-            "sketch": "data/pacs_split/sketch_crossval_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_crossval_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_crossval_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_crossval_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_crossval_kfold.txt",
         },
         dict_domain2imgroot={
             "art_painting": G_PACS_RAW_PATH,
diff --git a/examples/tasks/task_pacs_aug_noflip_no_zoom.py b/examples/tasks/task_pacs_aug_noflip_no_zoom.py
index c1f8b45a8..0151a38f2 100644
--- a/examples/tasks/task_pacs_aug_noflip_no_zoom.py
+++ b/examples/tasks/task_pacs_aug_noflip_no_zoom.py
@@ -11,8 +11,8 @@
 from domainlab.tasks.utils_task import ImSize
 
 # change this to absolute directory where you have the raw images from PACS,
-G_PACS_RAW_PATH = "data/pacs/PACS"
-# domainlab repository contain already the file names in data/pacs_split folder of domainlab
+G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
+# domainlab repository contain already the file names in domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
@@ -29,22 +29,22 @@ def get_task(na=None):
             "7": "person",
         },
         dict_d2filepath_list_img_tr={
-            "art_painting": "data/pacs_split/art_painting_train_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_train_kfold.txt",
-            "photo": "data/pacs_split/photo_train_kfold.txt",
-            "sketch": "data/pacs_split/sketch_train_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_train_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_train_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_train_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_train_kfold.txt",
         },
         dict_d2filepath_list_img_te={
-            "art_painting": "data/pacs_split/art_painting_test_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_test_kfold.txt",
-            "photo": "data/pacs_split/photo_test_kfold.txt",
-            "sketch": "data/pacs_split/sketch_test_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_test_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_test_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_test_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_test_kfold.txt",
         },
         dict_d2filepath_list_img_val={
-            "art_painting": "data/pacs_split/art_painting_crossval_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_crossval_kfold.txt",
-            "photo": "data/pacs_split/photo_crossval_kfold.txt",
-            "sketch": "data/pacs_split/sketch_crossval_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_crossval_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_crossval_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_crossval_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_crossval_kfold.txt",
         },
         dict_domain2imgroot={
             "art_painting": G_PACS_RAW_PATH,
diff --git a/examples/tasks/task_pacs_no_aug_norm_only.py b/examples/tasks/task_pacs_no_aug_norm_only.py
index 7a1897741..1dc616f2a 100644
--- a/examples/tasks/task_pacs_no_aug_norm_only.py
+++ b/examples/tasks/task_pacs_no_aug_norm_only.py
@@ -11,8 +11,8 @@
 from domainlab.tasks.utils_task import ImSize
 
 # change this to absolute directory where you have the raw images from PACS,
-G_PACS_RAW_PATH = "data/pacs/PACS"
-# domainlab repository contain already the file names in data/pacs_split folder of domainlab
+G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
+# domainlab repository contain already the file names in domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
@@ -29,22 +29,22 @@ def get_task(na=None):
             "7": "person",
         },
         dict_d2filepath_list_img_tr={
-            "art_painting": "data/pacs_split/art_painting_train_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_train_kfold.txt",
-            "photo": "data/pacs_split/photo_train_kfold.txt",
-            "sketch": "data/pacs_split/sketch_train_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_train_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_train_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_train_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_train_kfold.txt",
         },
         dict_d2filepath_list_img_te={
-            "art_painting": "data/pacs_split/art_painting_test_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_test_kfold.txt",
-            "photo": "data/pacs_split/photo_test_kfold.txt",
-            "sketch": "data/pacs_split/sketch_test_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_test_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_test_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_test_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_test_kfold.txt",
         },
         dict_d2filepath_list_img_val={
-            "art_painting": "data/pacs_split/art_painting_crossval_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_crossval_kfold.txt",
-            "photo": "data/pacs_split/photo_crossval_kfold.txt",
-            "sketch": "data/pacs_split/sketch_crossval_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_crossval_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_crossval_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_crossval_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_crossval_kfold.txt",
         },
         dict_domain2imgroot={
             "art_painting": G_PACS_RAW_PATH,
diff --git a/examples/tasks/task_pacs_path_list.py b/examples/tasks/task_pacs_path_list.py
index 045232b4a..a7dc1b828 100644
--- a/examples/tasks/task_pacs_path_list.py
+++ b/examples/tasks/task_pacs_path_list.py
@@ -11,8 +11,8 @@
 from domainlab.tasks.utils_task import ImSize
 
 # change this to absolute directory where you have the raw images from PACS,
-G_PACS_RAW_PATH = "data/pacs/PACS"
-# domainlab repository contain already the file names in data/pacs_split folder of domainlab
+G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
+# domainlab repository contain already the file names in domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
@@ -29,22 +29,22 @@ def get_task(na=None):
             "7": "person",
         },
         dict_d2filepath_list_img_tr={
-            "art_painting": "data/pacs_split/art_painting_train_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_train_kfold.txt",
-            "photo": "data/pacs_split/photo_train_kfold.txt",
-            "sketch": "data/pacs_split/sketch_train_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_train_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_train_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_train_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_train_kfold.txt",
         },
         dict_d2filepath_list_img_te={
-            "art_painting": "data/pacs_split/art_painting_test_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_test_kfold.txt",
-            "photo": "data/pacs_split/photo_test_kfold.txt",
-            "sketch": "data/pacs_split/sketch_test_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_test_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_test_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_test_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_test_kfold.txt",
         },
         dict_d2filepath_list_img_val={
-            "art_painting": "data/pacs_split/art_painting_crossval_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_crossval_kfold.txt",
-            "photo": "data/pacs_split/photo_crossval_kfold.txt",
-            "sketch": "data/pacs_split/sketch_crossval_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_crossval_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_crossval_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_crossval_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_crossval_kfold.txt",
         },
         dict_domain2imgroot={
             "art_painting": G_PACS_RAW_PATH,
diff --git a/examples/tasks/task_vlcs.py b/examples/tasks/task_vlcs.py
index 3deb6b2d6..41f1d8609 100644
--- a/examples/tasks/task_vlcs.py
+++ b/examples/tasks/task_vlcs.py
@@ -52,9 +52,9 @@
     ),
     isize=ImSize(3, 224, 224),
     dict_domain2imgroot={
-        "caltech": os.path.join(path_this_file, "../../data/vlcs_mini/caltech/"),
-        "sun": os.path.join(path_this_file, "../../data/vlcs_mini/sun/"),
-        "labelme": os.path.join(path_this_file, "../../data/vlcs_mini/labelme/"),
+        "caltech": os.path.join(path_this_file, "../zdata/vlcs_mini/caltech/"),
+        "sun": os.path.join(path_this_file, "../zdata/vlcs_mini/sun/"),
+        "labelme": os.path.join(path_this_file, "../zdata/vlcs_mini/labelme/"),
     },
     taskna="e_mini_vlcs",
 )
diff --git a/scripts/sh_link_pacs_dataset.sh b/scripts/sh_link_pacs_dataset.sh
index 742f256e5..f973db02b 100644
--- a/scripts/sh_link_pacs_dataset.sh
+++ b/scripts/sh_link_pacs_dataset.sh
@@ -1,2 +1,2 @@
-mkdir -p data/pacs
-ln -s ~/Documents/datasets/pacs/raw data/pacs/PACS
+mkdir -p domainlab/zdata/pacs
+ln -s ~/Documents/datasets/pacs/raw domainlab/zdata/pacs/PACS
diff --git a/sh_download_pacs.sh b/sh_download_pacs.sh
old mode 100644
new mode 100755
index e6b8b2020..d28473892
--- a/sh_download_pacs.sh
+++ b/sh_download_pacs.sh
@@ -1,3 +1,3 @@
-mkdir -p data/pacs
-cd data/script
-python download_pacs.py
+mkdir -p domainlab/zdata/pacs
+cd domainlab/zdata/script
+python3 download_pacs.py
diff --git a/tests/dset_subfolder_test.py b/tests/dset_subfolder_test.py
index ccf9bc575..9491bb47c 100644
--- a/tests/dset_subfolder_test.py
+++ b/tests/dset_subfolder_test.py
@@ -10,7 +10,7 @@
 
 def test_fun():
     dset = DsetSubFolder(
-        root="data/vlcs_mini/caltech",
+        root="domainlab/zdata/vlcs_mini/caltech",
         list_class_dir=["auto", "vogel"],
         loader=fun_img_path_loader_default,
         extensions="jpg",
@@ -23,7 +23,7 @@ def test_fun():
 def test_mixed_codec():
     """Check if only images with given extension are loaded."""
     dset = DsetSubFolder(
-        root="data/mixed_codec/caltech",
+        root="domainlab/zdata/mixed_codec/caltech",
         list_class_dir=["auto", "vogel"],
         loader=fun_img_path_loader_default,
         extensions=None,
@@ -33,7 +33,7 @@ def test_mixed_codec():
     assert len(dset.samples) == 6
 
     dset = DsetSubFolder(
-        root="data/mixed_codec/caltech",
+        root="domainlab/zdata/mixed_codec/caltech",
         list_class_dir=["auto", "vogel"],
         loader=fun_img_path_loader_default,
         extensions="jpg",
@@ -42,11 +42,11 @@ def test_mixed_codec():
     )
     assert (
         len(dset.samples) == 4
-    ), f"data/mixed_codec contains 4 jpg files, but {len(dset.samples)} were loaded."
+    ), f"domainlab/zdata/mixed_codec contains 4 jpg files, but {len(dset.samples)} were loaded."
 
     with pytest.raises(ValueError):
         DsetSubFolder(
-            root="data/mixed_codec/caltech",
+            root="domainlab/zdata/mixed_codec/caltech",
             list_class_dir=["auto", "vogel"],
             loader=fun_img_path_loader_default,
             extensions="jpg",
@@ -60,7 +60,7 @@ def test_wrong_class_names():
     """Check for error if list_class_dir does not match the subfolders."""
     with pytest.raises(RuntimeError):
         DsetSubFolder(
-            root="data/mixed_codec/caltech",
+            root="domainlab/zdata/mixed_codec/caltech",
             list_class_dir=["auto", "haus"],
             loader=fun_img_path_loader_default,
             extensions=None,
diff --git a/tests/dset_utils_data_test.py b/tests/dset_utils_data_test.py
index 3b618146c..f436c4ff9 100644
--- a/tests/dset_utils_data_test.py
+++ b/tests/dset_utils_data_test.py
@@ -3,7 +3,7 @@
 
 
 def test_dset_in_mem_decorator():
-    dset = DsetMNISTColorSoloDefault(path="../data", ind_color=1)
+    dset = DsetMNISTColorSoloDefault(path="zdata", ind_color=1)
     dset_in_memory = DsetInMemDecorator(dset=dset)
     dset_in_memory.__len__()
     dset_in_memory.__getitem__(0)
diff --git a/tests/test_benchmark_plots.py b/tests/test_benchmark_plots.py
index f8018dd5f..855157b7f 100644
--- a/tests/test_benchmark_plots.py
+++ b/tests/test_benchmark_plots.py
@@ -9,10 +9,10 @@ def test_benchm_plots():
     test benchmark plots
     """
     gen_benchmark_plots(
-        "data/ztest_files/aggret_res_test1",
+        "domainlab/zdata/ztest_files/aggret_res_test1",
         "zoutput/benchmark_plots_test/outp1",
         use_param_index=False,
     )
     gen_benchmark_plots(
-        "data/ztest_files/aggret_res_test2", "zoutput/benchmark_plots_test/outp2"
+        "domainlab/zdata/ztest_files/aggret_res_test2", "zoutput/benchmark_plots_test/outp2"
     )
diff --git a/tests/test_exp_protocol.py b/tests/test_exp_protocol.py
index 2f9ca03ea..bae262258 100644
--- a/tests/test_exp_protocol.py
+++ b/tests/test_exp_protocol.py
@@ -33,7 +33,7 @@ def utils_run_experiment(yaml_name, list_test_domains, no_run=True):
     config["startseed"] = 1
     config["endseed"] = 1
     config["test_domains"] = list_test_domains
-    param_file = "data/ztest_files/test_parameter_samples.csv"
+    param_file = "domainlab/zdata/ztest_files/test_parameter_samples.csv"
     param_index = 0
     out_file = "zoutput/benchmarks/demo_benchmark/rule_results/0.csv"
 
diff --git a/tests/test_git_tag.py b/tests/test_git_tag.py
index 2bd96e146..72616a2ed 100644
--- a/tests/test_git_tag.py
+++ b/tests/test_git_tag.py
@@ -19,14 +19,14 @@ def test_git_tag_error():
     test git_tag error
     """
     # add one line to the file
-    with open("data/ztest_files/dummy_file.py", "a") as f:
+    with open("domainlab/zdata/ztest_files/dummy_file.py", "a") as f:
         f.write("\n# I am a dummy command")
     get_git_tag(print_diff=True)
     # delete the last line on the file again
-    with open("data/ztest_files/dummy_file.py", "r") as f:
+    with open("domainlab/zdata/ztest_files/dummy_file.py", "r") as f:
         lines = f.readlines()
         lines = lines[:-1]
-    with open("data/ztest_files/dummy_file.py", "w") as f:
+    with open("domainlab/zdata/ztest_files/dummy_file.py", "w") as f:
         for num, line in enumerate(lines):
             if num == len(lines) - 1:
                 f.write(line[:-2])
diff --git a/tests/test_run_experiment.py b/tests/test_run_experiment.py
index b22593a91..98cc5201d 100644
--- a/tests/test_run_experiment.py
+++ b/tests/test_run_experiment.py
@@ -18,7 +18,7 @@ def test_run_experiment():
     config["startseed"] = 1
     config["endseed"] = 1
     config["test_domains"] = ["caltech"]
-    param_file = "data/ztest_files/test_parameter_samples.csv"
+    param_file = "domainlab/zdata/ztest_files/test_parameter_samples.csv"
     param_index = 0
     out_file = "zoutput/benchmarks/demo_benchmark/rule_results/0.csv"
 
@@ -41,7 +41,7 @@ def test_run_experiment_parameter_doubling_error():
     config["endseed"] = 1
     config["test_domains"] = ["caltech"]
     config["diva"]["gamma_y"] = 1e4
-    param_file = "data/ztest_files/test_parameter_samples.csv"
+    param_file = "domainlab/zdata/ztest_files/test_parameter_samples.csv"
     param_index = 0
     out_file = "zoutput/benchmarks/demo_benchmark/rule_results/0.csv"
 
@@ -58,7 +58,7 @@ def test_run_experiment_parameter_doubling_error():
     config["endseed"] = 1
     config["test_domains"] = ["caltech"]
     config["domainlab_args"]["gamma_y"] = 1e4
-    param_file = "data/ztest_files/test_parameter_samples.csv"
+    param_file = "domainlab/zdata/ztest_files/test_parameter_samples.csv"
     param_index = 0
     out_file = "zoutput/benchmarks/demo_benchmark/rule_results/0.csv"
 
diff --git a/tests/test_task_folder.py b/tests/test_task_folder.py
index 3b78b5f2c..ed2683a23 100644
--- a/tests/test_task_folder.py
+++ b/tests/test_task_folder.py
@@ -36,9 +36,9 @@ def test_fun():
         ),
         isize=ImSize(3, 224, 224),
         dict_domain2imgroot={
-            "caltech": "data/vlcs_mini/caltech/",
-            "sun": "data/vlcs_mini/sun/",
-            "labelme": "data/vlcs_mini/labelme/",
+            "caltech": "domainlab/zdata/vlcs_mini/caltech/",
+            "sun": "domainlab/zdata/vlcs_mini/sun/",
+            "labelme": "domainlab/zdata/vlcs_mini/labelme/",
         },
         taskna="mini_vlcs",
         succ=None,
@@ -99,9 +99,9 @@ def test_mk_task_folder():
         },
         isize=ImSize(3, 224, 224),
         dict_domain2imgroot={
-            "caltech": "data/vlcs_mini/caltech/",
-            "sun": "data/vlcs_mini/sun/",
-            "labelme": "data/vlcs_mini/labelme/",
+            "caltech": "domainlab/zdata/vlcs_mini/caltech/",
+            "sun": "domainlab/zdata/vlcs_mini/sun/",
+            "labelme": "domainlab/zdata/vlcs_mini/labelme/",
         },
         taskna="mini_vlcs",
     )
@@ -133,9 +133,9 @@ def test_none_extensions():
         ),
         isize=ImSize(3, 224, 224),
         dict_domain2imgroot={
-            "caltech": "data/vlcs_mini/caltech/",
-            "labelme": "data/vlcs_mini/labelme/",
-            "sun": "data/vlcs_mini/sun/",
+            "caltech": "domainlab/zdata/vlcs_mini/caltech/",
+            "labelme": "domainlab/zdata/vlcs_mini/labelme/",
+            "sun": "domainlab/zdata/vlcs_mini/sun/",
         },
         taskna="mini_vlcs",
         succ=None,
@@ -169,8 +169,8 @@ def test_none_extensions():
         ),
         isize=ImSize(3, 224, 224),
         dict_domain2imgroot={
-            "caltech": "data/mixed_codec/caltech/",
-            "sun": "data/mixed_codec/sun/",
+            "caltech": "domainlab/zdata/mixed_codec/caltech/",
+            "sun": "domainlab/zdata/mixed_codec/sun/",
         },
         taskna="mixed_codec",
         succ=None,
@@ -208,8 +208,8 @@ def test_none_extensions():
         ),
         isize=ImSize(3, 224, 224),
         dict_domain2imgroot={
-            "caltech": "data/mixed_codec/caltech/",
-            "sun": "data/mixed_codec/sun/",
+            "caltech": "domainlab/zdata/mixed_codec/caltech/",
+            "sun": "domainlab/zdata/mixed_codec/sun/",
         },
         taskna="mixed_codec",
         succ=None,
@@ -231,8 +231,8 @@ def pacs_node():
     node.extensions = ("jpg",)
     node.list_str_y = ["dog", "elephant"]
     node.dict_domain2imgroot = {
-        "cartoon": "data/pacs_mini_10/cartoon/",
-        "photo": "data/pacs_mini_10/photo/",
+        "cartoon": "domainlab/zdata/pacs_mini_10/cartoon/",
+        "photo": "domainlab/zdata/pacs_mini_10/photo/",
     }
     return node
 

From 489be447728ec398960eb24f991b6377e0932508 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 23 Apr 2024 15:55:44 +0200
Subject: [PATCH 033/273] testing paths for tasks

---
 examples/tasks/task_vlcs.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/examples/tasks/task_vlcs.py b/examples/tasks/task_vlcs.py
index 41f1d8609..498ee27f2 100644
--- a/examples/tasks/task_vlcs.py
+++ b/examples/tasks/task_vlcs.py
@@ -52,9 +52,9 @@
     ),
     isize=ImSize(3, 224, 224),
     dict_domain2imgroot={
-        "caltech": os.path.join(path_this_file, "../zdata/vlcs_mini/caltech/"),
-        "sun": os.path.join(path_this_file, "../zdata/vlcs_mini/sun/"),
-        "labelme": os.path.join(path_this_file, "../zdata/vlcs_mini/labelme/"),
+        "caltech": os.path.join(path_this_file, "../../domainlab/zdata/vlcs_mini/caltech/"),
+        "sun": os.path.join(path_this_file, "../../domainlab/zdata/vlcs_mini/sun/"),
+        "labelme": os.path.join(path_this_file, "../../domainlab/zdata/vlcs_mini/labelme/"),
     },
     taskna="e_mini_vlcs",
 )

From 4be4a021bdb35374372570b9f6d49a8a47c4b050 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 23 Apr 2024 17:43:30 +0200
Subject: [PATCH 034/273] fixed codacy

---
 domainlab/algos/trainers/a_trainer.py       |  5 +++--
 domainlab/arg_parser.py                     |  2 ++
 domainlab/models/a_model.py                 |  5 +++--
 domainlab/utils/hyperparameter_retrieval.py | 12 +++++++-----
 tests/test_hyperparameter_retrieval.py      | 11 ++++++++---
 5 files changed, 23 insertions(+), 12 deletions(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 8d06a448e..0e3d4a168 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -256,10 +256,11 @@ def dset_decoration_args_algo(self, args, ddset):
         if self._decoratee is not None:
             return self._decoratee.dset_decoration_args_algo(args, ddset)
         return ddset
-    
+
     def print_parameters(self):
         """
-        Function to print all parameters of the object. Can also be used to print the parameters of the child classes
+        Function to print all parameters of the object. 
+        Can be used to print the parameters of any child class
         """
         params = vars(self)
         print(f"Parameters of {type(self).__name__}: {params}")
diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index eb8c6836c..50ab707db 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -13,6 +13,8 @@
 from domainlab.utils.logger import Logger
 
 class StoreDictKeyPair(argparse.Action):
+    """Class used for arg parsing where values are provided in a key value format"""
+
     def __call__(self, parser, namespace, values, option_string=None):
         try:
             if "=" in values:
diff --git a/domainlab/models/a_model.py b/domainlab/models/a_model.py
index 6ea45747f..60571248d 100644
--- a/domainlab/models/a_model.py
+++ b/domainlab/models/a_model.py
@@ -178,7 +178,7 @@ def dset_decoration_args_algo(self, args, ddset):
         if self._decoratee is not None:
             return self._decoratee.dset_decoration_args_algo(args, ddset)
         return ddset
-    
+
     @property
     def p_na_prefix(self):
         """
@@ -205,7 +205,8 @@ def name(self):
     
     def print_parameters(self):
         """
-        Function to print all parameters of the object. Can also be used to print the parameters of the child classes
+        Function to print all parameters of the object. 
+        Can be used to print the parameters of every child class.
         """
         params = vars(self)
         print(f"Parameters of {type(self).__name__}: {params}")
diff --git a/domainlab/utils/hyperparameter_retrieval.py b/domainlab/utils/hyperparameter_retrieval.py
index 8e49c356c..c7882cb0b 100644
--- a/domainlab/utils/hyperparameter_retrieval.py
+++ b/domainlab/utils/hyperparameter_retrieval.py
@@ -10,11 +10,13 @@ def get_gamma_reg(args, model_name):
     print(gamma_reg)
     if isinstance(gamma_reg, dict):
         print("is instance dict")
-        if model_name in gamma_reg: 
-            return gamma_reg[model_name]  
-        elif 'default' in gamma_reg: 
+        if model_name in gamma_reg:
+            return gamma_reg[model_name]
+        if 'default' in gamma_reg:
             return gamma_reg['default']
-        else: 
-            raise ValueError("If a gamma_reg dict is specified, but no value set for every model and trainer, a default value must be specified.")
+        else:
+            raise ValueError("""If a gamma_reg dict is specified, 
+                             but no value set for every model and trainer,
+                              a default value must be specified.""")
     else: 
         return gamma_reg  # Return the single value if it's not a dictionary
diff --git a/tests/test_hyperparameter_retrieval.py b/tests/test_hyperparameter_retrieval.py
index 192343617..e166e320b 100644
--- a/tests/test_hyperparameter_retrieval.py
+++ b/tests/test_hyperparameter_retrieval.py
@@ -1,24 +1,29 @@
-# Assume imports and any necessary setup are already done
-import argparse
-from domainlab.arg_parser import StoreDictKeyPair, mk_parser_main
+"""
+unit test for hyperparameter parsing
+"""
+from domainlab.arg_parser import mk_parser_main
 from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 def test_store_dict_key_pair_single_value():
+    """Test to parse a single gamma_reg parameter"""
     parser = mk_parser_main()
     args = parser.parse_args(['--gamma_reg', '0.5'])
     assert args.gamma_reg == 0.5
 
 def test_store_dict_key_pair_dict_value():
+    """Test to parse a dict for the gamma_reg"""
     parser = mk_parser_main()
     args = parser.parse_args(['--gamma_reg', 'dann=1.0,diva=2.0'])
     assert args.gamma_reg == {'dann': 1.0, 'diva': 2.0}
 
 def test_get_gamma_reg_single_value():
+    """Test to retrieve a single gamma_reg parameter which is applied to all objects"""
     parser = mk_parser_main()
     args = parser.parse_args(['--gamma_reg', '0.5'])
     assert get_gamma_reg(args, 'dann') == 0.5
 
 def test_get_gamma_reg_dict_value():
+    """Test to retrieve a dict of gamma_reg parameters for different objects"""
     parser = mk_parser_main()
     args = parser.parse_args(['--gamma_reg', 'default=5.0,dann=1.0,diva=2.0'])
     print(args)

From 9b192ed12ec2806a2bbfc74717f9eed785887ea1 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 23 Apr 2024 17:46:53 +0200
Subject: [PATCH 035/273] fixed codacy

---
 examples/tasks/task_pacs_aug.py                | 3 ++-
 examples/tasks/task_pacs_aug_noflip_no_zoom.py | 3 ++-
 examples/tasks/task_pacs_no_aug_norm_only.py   | 3 ++-
 examples/tasks/task_pacs_path_list.py          | 3 ++-
 4 files changed, 8 insertions(+), 4 deletions(-)

diff --git a/examples/tasks/task_pacs_aug.py b/examples/tasks/task_pacs_aug.py
index be6b84e27..e971bea8c 100644
--- a/examples/tasks/task_pacs_aug.py
+++ b/examples/tasks/task_pacs_aug.py
@@ -12,7 +12,8 @@
 
 # change this to absolute directory where you have the raw images from PACS,
 G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
-# domainlab repository contain already the file names in domainlab/zdata/pacs_split folder of domainlab
+# domainlab repository contain already the file names in
+# domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
diff --git a/examples/tasks/task_pacs_aug_noflip_no_zoom.py b/examples/tasks/task_pacs_aug_noflip_no_zoom.py
index 0151a38f2..0b855d31e 100644
--- a/examples/tasks/task_pacs_aug_noflip_no_zoom.py
+++ b/examples/tasks/task_pacs_aug_noflip_no_zoom.py
@@ -12,7 +12,8 @@
 
 # change this to absolute directory where you have the raw images from PACS,
 G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
-# domainlab repository contain already the file names in domainlab/zdata/pacs_split folder of domainlab
+# domainlab repository contain already the file names in
+# domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
diff --git a/examples/tasks/task_pacs_no_aug_norm_only.py b/examples/tasks/task_pacs_no_aug_norm_only.py
index 1dc616f2a..07e6339c3 100644
--- a/examples/tasks/task_pacs_no_aug_norm_only.py
+++ b/examples/tasks/task_pacs_no_aug_norm_only.py
@@ -12,7 +12,8 @@
 
 # change this to absolute directory where you have the raw images from PACS,
 G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
-# domainlab repository contain already the file names in domainlab/zdata/pacs_split folder of domainlab
+# domainlab repository contain already the file names in
+# domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
diff --git a/examples/tasks/task_pacs_path_list.py b/examples/tasks/task_pacs_path_list.py
index a7dc1b828..53d97d640 100644
--- a/examples/tasks/task_pacs_path_list.py
+++ b/examples/tasks/task_pacs_path_list.py
@@ -12,7 +12,8 @@
 
 # change this to absolute directory where you have the raw images from PACS,
 G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
-# domainlab repository contain already the file names in domainlab/zdata/pacs_split folder of domainlab
+# domainlab repository contain already the file names in
+# domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):

From 394d23ab9cbfd4d4ab357d05722b4b4e8dc2296d Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 23 Apr 2024 18:00:58 +0200
Subject: [PATCH 036/273] fixed codacy

---
 domainlab/models/a_model.py                 | 2 +-
 domainlab/utils/hyperparameter_retrieval.py | 8 +++-----
 2 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/domainlab/models/a_model.py b/domainlab/models/a_model.py
index 60571248d..1b7e652f4 100644
--- a/domainlab/models/a_model.py
+++ b/domainlab/models/a_model.py
@@ -202,7 +202,7 @@ def name(self):
                 na_class,
             )
         return type(self).__name__[len_prefix:].lower()
-    
+
     def print_parameters(self):
         """
         Function to print all parameters of the object. 
diff --git a/domainlab/utils/hyperparameter_retrieval.py b/domainlab/utils/hyperparameter_retrieval.py
index c7882cb0b..d47135554 100644
--- a/domainlab/utils/hyperparameter_retrieval.py
+++ b/domainlab/utils/hyperparameter_retrieval.py
@@ -14,9 +14,7 @@ def get_gamma_reg(args, model_name):
             return gamma_reg[model_name]
         if 'default' in gamma_reg:
             return gamma_reg['default']
-        else:
-            raise ValueError("""If a gamma_reg dict is specified, 
-                             but no value set for every model and trainer,
+        raise ValueError("""If a gamma_reg dict is specified,
+                              but no value set for every model and trainer,
                               a default value must be specified.""")
-    else: 
-        return gamma_reg  # Return the single value if it's not a dictionary
+    return gamma_reg  # Return the single value if it's not a dictionary

From 64bf2e6e2a3396fdb4d363d34997f08ea0d50f88 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 23 Apr 2024 18:04:47 +0200
Subject: [PATCH 037/273] fixing one path to the dataset during tests

---
 tests/dset_utils_data_test.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/dset_utils_data_test.py b/tests/dset_utils_data_test.py
index f436c4ff9..41b580935 100644
--- a/tests/dset_utils_data_test.py
+++ b/tests/dset_utils_data_test.py
@@ -3,7 +3,7 @@
 
 
 def test_dset_in_mem_decorator():
-    dset = DsetMNISTColorSoloDefault(path="zdata", ind_color=1)
+    dset = DsetMNISTColorSoloDefault(path="../domainlab/zdata", ind_color=1)
     dset_in_memory = DsetInMemDecorator(dset=dset)
     dset_in_memory.__len__()
     dset_in_memory.__getitem__(0)

From 6f4799ff7a30acfa734df437cee59bef2fe99ff7 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 23 Apr 2024 18:06:26 +0200
Subject: [PATCH 038/273] remove data directory

---
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 data/pacs_split/art_painting_test_kfold.txt   | 2048 ---------
 data/pacs_split/art_painting_train_kfold.txt  | 1840 --------
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 delete mode 100644 data/ztest_files/aggret_res_test11
 delete mode 100644 data/ztest_files/aggret_res_test2
 delete mode 100644 data/ztest_files/aggret_res_test21
 delete mode 100644 data/ztest_files/dummy_file.py
 delete mode 100644 data/ztest_files/test_parameter_samples.csv

diff --git a/data/mixed_codec/caltech/auto/text.txt b/data/mixed_codec/caltech/auto/text.txt
deleted file mode 100644
index 557db03de..000000000
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+++ /dev/null
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diff --git a/data/mixed_codec/caltech/auto/train_imgs_150.jpg b/data/mixed_codec/caltech/auto/train_imgs_150.jpg
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diff --git a/data/pacs_mini_10/main.sh b/data/pacs_mini_10/main.sh
deleted file mode 100644
index 8e44c8183..000000000
--- a/data/pacs_mini_10/main.sh
+++ /dev/null
@@ -1,7 +0,0 @@
-#!/bin/bash
-# first argument is the file with pointers to image
-# s
-bash run_with_bash_copy_files_according2txt.sh ../pacs_split/art_painting_10.txt ~/Documents/dataset/PACS/raw .
-bash run_with_bash_copy_files_according2txt.sh ../pacs_split/cartoon_10.txt ~/Documents/dataset/PACS/raw .
-bash run_with_bash_copy_files_according2txt.sh ../pacs_split/photo_10.txt ~/Documents/dataset/PACS/raw .
-bash run_with_bash_copy_files_according2txt.sh ../pacs_split/sketch_10.txt ~/Documents/dataset/PACS/raw .
diff --git a/data/pacs_mini_10/photo/dog/n02103406_1011.jpg b/data/pacs_mini_10/photo/dog/n02103406_1011.jpg
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diff --git a/data/pacs_mini_10/run_with_bash_copy_files_according2txt.sh b/data/pacs_mini_10/run_with_bash_copy_files_according2txt.sh
deleted file mode 100644
index 695e46218..000000000
--- a/data/pacs_mini_10/run_with_bash_copy_files_according2txt.sh
+++ /dev/null
@@ -1,26 +0,0 @@
-#!/bin/bash
-input=$1
-path=$2
-
-# test string array works
-sentence="this is a story"
-stringarray=($sentence)
-echo "${stringarray[0]}"
-
-while IFS= read -r line
-do
-  echo "$line"
-  stringarray=($line)
-  echo "${stringarray[0]}"
-  relativepath=${stringarray[0]}
-  fullpath="$path/$relativepath"
-  echo "fullpath is $fullpath"
-  newpath="$3/$relativepath"
-  echo "newpath is $newpath"
-  newpath2=`dirname "$newpath"`
-  echo "newpath2 is $newpath2"
-  mkdir -p "$newpath2"
-  cp "$fullpath" "$newpath2"
-  # cp "$fullpath" --parent "$3"
-
-done < "$input"
diff --git a/data/pacs_mini_10/sketch/dog/5302.png b/data/pacs_mini_10/sketch/dog/5302.png
deleted file mode 100644
index 3ec54e87ba4a4633e2ded07274a0cea856cea41b..0000000000000000000000000000000000000000
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diff --git a/data/pacs_split/art_painting_10.txt b/data/pacs_split/art_painting_10.txt
deleted file mode 100644
index 77f7627a2..000000000
--- a/data/pacs_split/art_painting_10.txt
+++ /dev/null
@@ -1,10 +0,0 @@
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diff --git a/data/pacs_split/art_painting_100.txt b/data/pacs_split/art_painting_100.txt
deleted file mode 100644
index 7da95eda1..000000000
--- a/data/pacs_split/art_painting_100.txt
+++ /dev/null
@@ -1,100 +0,0 @@
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diff --git a/data/pacs_split/art_painting_crossval_kfold.txt b/data/pacs_split/art_painting_crossval_kfold.txt
deleted file mode 100644
index 61b3f44e1..000000000
--- a/data/pacs_split/art_painting_crossval_kfold.txt
+++ /dev/null
@@ -1,208 +0,0 @@
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diff --git a/data/pacs_split/art_painting_test_kfold.txt b/data/pacs_split/art_painting_test_kfold.txt
deleted file mode 100644
index 9a5728738..000000000
--- a/data/pacs_split/art_painting_test_kfold.txt
+++ /dev/null
@@ -1,2048 +0,0 @@
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diff --git a/data/pacs_split/art_painting_train_kfold.txt b/data/pacs_split/art_painting_train_kfold.txt
deleted file mode 100644
index 8b5405715..000000000
--- a/data/pacs_split/art_painting_train_kfold.txt
+++ /dev/null
@@ -1,1840 +0,0 @@
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diff --git a/data/pacs_split/cartoon_10.txt b/data/pacs_split/cartoon_10.txt
deleted file mode 100644
index 9c90dce46..000000000
--- a/data/pacs_split/cartoon_10.txt
+++ /dev/null
@@ -1,10 +0,0 @@
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diff --git a/data/pacs_split/cartoon_100.txt b/data/pacs_split/cartoon_100.txt
deleted file mode 100644
index 678652e4c..000000000
--- a/data/pacs_split/cartoon_100.txt
+++ /dev/null
@@ -1,100 +0,0 @@
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diff --git a/data/pacs_split/cartoon_crossval_kfold.txt b/data/pacs_split/cartoon_crossval_kfold.txt
deleted file mode 100644
index e8374913b..000000000
--- a/data/pacs_split/cartoon_crossval_kfold.txt
+++ /dev/null
@@ -1,237 +0,0 @@
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diff --git a/data/pacs_split/cartoon_test_kfold.txt b/data/pacs_split/cartoon_test_kfold.txt
deleted file mode 100644
index 5daf9281e..000000000
--- a/data/pacs_split/cartoon_test_kfold.txt
+++ /dev/null
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diff --git a/data/pacs_split/cartoon_train_kfold.txt b/data/pacs_split/cartoon_train_kfold.txt
deleted file mode 100644
index 48ceb2f88..000000000
--- a/data/pacs_split/cartoon_train_kfold.txt
+++ /dev/null
@@ -1,2107 +0,0 @@
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diff --git a/data/pacs_split/photo_10.txt b/data/pacs_split/photo_10.txt
deleted file mode 100644
index 59ba86d76..000000000
--- a/data/pacs_split/photo_10.txt
+++ /dev/null
@@ -1,10 +0,0 @@
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diff --git a/data/pacs_split/photo_100.txt b/data/pacs_split/photo_100.txt
deleted file mode 100644
index 9a0951918..000000000
--- a/data/pacs_split/photo_100.txt
+++ /dev/null
@@ -1,100 +0,0 @@
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diff --git a/data/pacs_split/photo_crossval_kfold.txt b/data/pacs_split/photo_crossval_kfold.txt
deleted file mode 100644
index e001ac79e..000000000
--- a/data/pacs_split/photo_crossval_kfold.txt
+++ /dev/null
@@ -1,171 +0,0 @@
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diff --git a/data/pacs_split/photo_test_kfold.txt b/data/pacs_split/photo_test_kfold.txt
deleted file mode 100644
index 643ed4aa8..000000000
--- a/data/pacs_split/photo_test_kfold.txt
+++ /dev/null
@@ -1,1670 +0,0 @@
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diff --git a/data/pacs_split/photo_train_kfold.txt b/data/pacs_split/photo_train_kfold.txt
deleted file mode 100644
index 5edd1d10a..000000000
--- a/data/pacs_split/photo_train_kfold.txt
+++ /dev/null
@@ -1,1499 +0,0 @@
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diff --git a/data/pacs_split/readme.txt b/data/pacs_split/readme.txt
deleted file mode 100644
index 36a00efc7..000000000
--- a/data/pacs_split/readme.txt
+++ /dev/null
@@ -1,10 +0,0 @@
-
-1. The h5py files was pre-read using cv2, so it is BGR channel order.
-2. This benckmark is sensitive to the different train val splits, so please use this train val splits for the fair comparisons.
-
-https://drive.google.com/uc?id=1JFr8f805nMUelQWWmfnJR3y4_SYoN5Pd
-
-[https://drive.google.com/uc?id=1JFr8f805nMUelQWWmfnJR3y4_SYoN5Pd](https://drive.google.com/uc?id=1JFr8f805nMUelQWWmfnJR3y4_SYoN5Pd)
-
-
-https://github.com/facebookresearch/DomainBed/blob/4294ec699df761b46a1505734f6be16ef009cad9/domainbed/scripts/download.py#L29
diff --git a/data/pacs_split/sketch_10.txt b/data/pacs_split/sketch_10.txt
deleted file mode 100644
index 79f855d52..000000000
--- a/data/pacs_split/sketch_10.txt
+++ /dev/null
@@ -1,10 +0,0 @@
-sketch/house/8873.png 6
-sketch/guitar/n03467517_6423-3.png 4
-sketch/elephant/5981.png 2
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-sketch/dog/5317.png 1
diff --git a/data/pacs_split/sketch_100.txt b/data/pacs_split/sketch_100.txt
deleted file mode 100644
index 2856e053f..000000000
--- a/data/pacs_split/sketch_100.txt
+++ /dev/null
@@ -1,100 +0,0 @@
-sketch/guitar/n02676566_6704-1.png 4
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diff --git a/data/pacs_split/sketch_crossval_kfold.txt b/data/pacs_split/sketch_crossval_kfold.txt
deleted file mode 100644
index 63c0f2050..000000000
--- a/data/pacs_split/sketch_crossval_kfold.txt
+++ /dev/null
@@ -1,398 +0,0 @@
-sketch/dog/n02103406_343-1.png 1
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diff --git a/data/pacs_split/sketch_test_kfold.txt b/data/pacs_split/sketch_test_kfold.txt
deleted file mode 100644
index c27970b06..000000000
--- a/data/pacs_split/sketch_test_kfold.txt
+++ /dev/null
@@ -1,3929 +0,0 @@
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diff --git a/data/pacs_split/sketch_train_kfold.txt b/data/pacs_split/sketch_train_kfold.txt
deleted file mode 100644
index a5088dca0..000000000
--- a/data/pacs_split/sketch_train_kfold.txt
+++ /dev/null
@@ -1,3531 +0,0 @@
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diff --git a/data/patches_permutation4jigsaw/permutations_100.npy b/data/patches_permutation4jigsaw/permutations_100.npy
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diff --git a/data/script/download_pacs.py b/data/script/download_pacs.py
deleted file mode 100644
index 51c346f24..000000000
--- a/data/script/download_pacs.py
+++ /dev/null
@@ -1,64 +0,0 @@
-"this script can be used to download the pacs dataset"
-import os
-import tarfile
-from zipfile import ZipFile
-
-import gdown
-
-
-def stage_path(data_dir, name):
-    """
-    creates the path to data_dir/name
-    if it does not exist already
-    """
-    full_path = os.path.join(data_dir, name)
-
-    if not os.path.exists(full_path):
-        os.makedirs(full_path)
-
-    return full_path
-
-
-def download_and_extract(url, dst, remove=True):
-    """
-    downloads and extracts the data behind the url
-    and saves it at dst
-    """
-    gdown.download(url, dst, quiet=False)
-
-    if dst.endswith(".tar.gz"):
-        with open(dst, "r:gz") as tar:
-            tar.extractall(os.path.dirname(dst))
-        tar.close()
-
-    if dst.endswith(".tar"):
-        with open(dst, "r:") as tar:
-            tar.extractall(os.path.dirname(dst))
-        tar.close()
-
-    if dst.endswith(".zip"):
-        zfile = ZipFile(dst, "r")
-        zfile.extractall(os.path.dirname(dst))
-        zfile.close()
-
-    if remove:
-        os.remove(dst)
-
-
-def download_pacs(data_dir):
-    """
-    download and extract dataset pacs.
-    Dataset is saved at location data_dir
-    """
-    full_path = stage_path(data_dir, "PACS")
-
-    download_and_extract(
-        "https://drive.google.com/uc?id=1JFr8f805nMUelQWWmfnJR3y4_SYoN5Pd",
-        os.path.join(data_dir, "PACS.zip"),
-    )
-
-    os.rename(os.path.join(data_dir, "kfold"), full_path)
-
-
-if __name__ == "__main__":
-    download_pacs("../pacs")
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diff --git a/data/ztest_files/aggret_res_test1 b/data/ztest_files/aggret_res_test1
deleted file mode 100644
index f53acf3ae..000000000
--- a/data/ztest_files/aggret_res_test1
+++ /dev/null
@@ -1,2 +0,0 @@
-param_index, method, algo, epos, te_d, seed, params, acc, precision, recall, specificity, f1, auroc
-0, Task1, diva, 2, caltech, 1, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8098495
diff --git a/data/ztest_files/aggret_res_test11 b/data/ztest_files/aggret_res_test11
deleted file mode 100644
index 797cc5055..000000000
--- a/data/ztest_files/aggret_res_test11
+++ /dev/null
@@ -1,9 +0,0 @@
-param_index, method, algo, epos, te_d, seed, params, acc, precision, recall, specificity, f1, auroc
-0, Task1, diva, 2, caltech, 1, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8098495
-0, Task1, diva, 2, caltech, 2, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.8111111, 0.8232258, 0.6903785, 0.6903785, 0.71645665, 0.89284086
-1, Task1, diva, 2, caltech, 1, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8095455
-1, Task1, diva, 2, caltech, 2, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.82222223, 0.8609804, 0.6981304, 0.6981304, 0.7278397, 0.9361605
-0, Task2, hduva, 2, caltech, 1, "{'a': 1, 'b': 3}", 0.76, 0.76, 0.49, 0.56, 0.57, 0.76
-0, Task2, hduva, 2, caltech, 2, "{'a': 1, 'b': 3}", 0.81, 0.75, 0.45, 0.64, 0.75, 0.89
-1, Task2, hduva, 2, caltech, 1, "{'a': 2, 'b': 4}", 0.75, 0.81, 0.45, 0.54, 0.39, 0.88
-1, Task2, hduva, 2, caltech, 2, "{'a': 2, 'b': 4}", 0.73, 0.72, 0.51, 0.51, 0.6, 0.88
diff --git a/data/ztest_files/aggret_res_test2 b/data/ztest_files/aggret_res_test2
deleted file mode 100644
index 93104ef85..000000000
--- a/data/ztest_files/aggret_res_test2
+++ /dev/null
@@ -1,5 +0,0 @@
-param_index, method, algo, epos, te_d, seed, params, acc, precision, recall, specificity, f1, auroc
-0, Task1, diva, 2, caltech, 1, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8098495
-0, Task1, diva, 2, caltech, 2, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.8111111, 0.8232258, 0.6903785, 0.6903785, 0.71645665, 0.89284086
-2, Task1, diva, 2, caltech, 3, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.77397263, 0.82765615, 0.59528303, 0.59528303, 0.5953641, 0.74150944
-0, Task2, diva, 2, caltech, 1, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8098495
diff --git a/data/ztest_files/aggret_res_test21 b/data/ztest_files/aggret_res_test21
deleted file mode 100644
index 5bb677ba7..000000000
--- a/data/ztest_files/aggret_res_test21
+++ /dev/null
@@ -1,23 +0,0 @@
-param_index, method, algo, epos, te_d, seed, params, acc, precision, recall, specificity, f1, auroc
-0, Task1, diva, 2, caltech, 1, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8098495
-0, Task1, diva, 2, caltech, 2, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.8111111, 0.8232258, 0.6903785, 0.6903785, 0.71645665, 0.89284086
-2, Task1, diva, 2, caltech, 3, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.77397263, 0.82765615, 0.59528303, 0.59528303, 0.5953641, 0.74150944
-2, Task1, diva, 2, caltech, 4, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.851917, 0.7569983, 0.8873113, 0.8173113, 0.7985473, 0.8769811
-2, Task1, diva, 2, caltech, 5, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.84, 0.85, 0.615, 0.62, 0.62, 0.74
-1, Task1, diva, 2, caltech, 1, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8095455
-1, Task1, diva, 2, caltech, 2, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.82222223, 0.8609804, 0.6981304, 0.6981304, 0.7278397, 0.9361605
-1, Task1, diva, 2, caltech, 3, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.85397263, 0.95765615, 0.67528303, 0.6728303, 0.6853641, 0.81150944
-1, Task1, diva, 2, caltech, 4, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.971917, 0.8869983, 0.9273113, 0.9273113, 0.8285473, 0.9369811
-1, Task1, diva, 2, caltech, 5, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.92, 0.91, 0.74, 0.75, 0.67, 0.8
-0, Task2, hduva, 2, caltech, 1, "{'gamma_y': 97228, 'zy_dim': 76}", 0.76, 0.76, 0.49, 0.56, 0.57, 0.76
-0, Task2, hduva, 2, caltech, 2, "{'gamma_y': 97228, 'zy_dim': 76}", 0.81, 0.75, 0.45, 0.64, 0.75, 0.89
-0, Task2, hduva, 2, caltech, 3, "{'gamma_y': 97228, 'zy_dim': 76}", 0.8251667, 0.104563385, 0.10817383, 0.90109926, 0.08242064, 0.519054
-0, Task2, hduva, 2, caltech, 4, "{'gamma_y': 97228, 'zy_dim': 76}", 0.97535366, 0.88569593, 0.87402904, 0.98618114, 0.87845683, 0.99118155
-0, Task2, hduva, 2, caltech, 5, "{'gamma_y': 97228, 'zy_dim': 76}", 0.82422227, 0.10658247, 0.1084048, 0.9009563, 0.08635866, 0.51927835
-1, Task2, hduva, 2, caltech, 1, "{'gamma_y': 196616, 'zy_dim': 68}", 0.75, 0.81, 0.45, 0.54, 0.39, 0.88
-1, Task2, hduva, 2, caltech, 2, "{'gamma_y': 196616, 'zy_dim': 68}", 0.73, 0.72, 0.51, 0.51, 0.6, 0.88
-1, Task2, hduva, 2, caltech, 1, "{'gamma_y': 113475, 'zy_dim': 48}", 0.8551667, 0.204563385, 0.20817383, 0.80109926, 0.15242064, 0.559054
-1, Task2, hduva, 2, caltech, 2, "{'gamma_y': 113475, 'zy_dim': 48}", 0.57535366, 0.52569593, 0.41402904, 0.68618114, 0.57845683, 0.89118155
-1, Task2, hduva, 2, caltech, 3, "{'gamma_y': 113475, 'zy_dim': 48}", 0.72422227, 0.20658247, 0.2084048, 0.7009563, 0.18635866, 0.61927835
-1, Task2, erm, 2, caltech, 1, "{}", 0.5, 0.5, 0.5, 0.5, 0.5, 0.5
-1, Task2, erm, 2, caltech, 2, "{}", 0.4, 0.4, 0.4, 0.4, 0.4, 0.4
diff --git a/data/ztest_files/dummy_file.py b/data/ztest_files/dummy_file.py
deleted file mode 100644
index e0c7faa27..000000000
--- a/data/ztest_files/dummy_file.py
+++ /dev/null
@@ -1,4 +0,0 @@
-"""
-I am a dummy file used in tests/test_git_tag.py
-to produce a file which is not commited
-"""
diff --git a/data/ztest_files/test_parameter_samples.csv b/data/ztest_files/test_parameter_samples.csv
deleted file mode 100644
index e3ebdbf4a..000000000
--- a/data/ztest_files/test_parameter_samples.csv
+++ /dev/null
@@ -1,2 +0,0 @@
-,method,model,params
-0,diva,diva,"{'gamma_y': 10e5, 'gamma_d': 1e5}"

From 4f0729bb7854677be039cbcda7193b812ee9af5d Mon Sep 17 00:00:00 2001
From: Amir_kd <4932099+Amirhk-dev@users.noreply.github.com>
Date: Mon, 29 Apr 2024 16:17:13 +0200
Subject: [PATCH 039/273] Update main_out.py

---
 main_out.py | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/main_out.py b/main_out.py
index 471702f9b..bdd4fdae8 100644
--- a/main_out.py
+++ b/main_out.py
@@ -1,9 +1,4 @@
-from domainlab.arg_parser import parse_cmd_args
 from domainlab.cli import domainlab_cli
-from domainlab.exp.exp_cuda_seed import set_seed  # reproducibility
-from domainlab.exp.exp_main import Exp
-from domainlab.exp_protocol import aggregate_results
-from domainlab.utils.generate_benchmark_plots import gen_benchmark_plots
 
 if __name__ == "__main__":
     domainlab_cli()

From 1aaa3ac401e07383eba253d3074f6d7e4493b90f Mon Sep 17 00:00:00 2001
From: Amir_kd <4932099+Amirhk-dev@users.noreply.github.com>
Date: Mon, 29 Apr 2024 16:21:24 +0200
Subject: [PATCH 040/273] Update README.md

---
 README.md | 29 +++++++++++++++++++++--------
 1 file changed, 21 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index ed031c0b4..6cecda105 100644
--- a/README.md
+++ b/README.md
@@ -8,24 +8,37 @@
 
 ## Distribution shifts, domain generalization and DomainLab
 
-Neural networks trained using data from a specific distribution (domain) usually fails to generalize to novel distributions (domains). Domain generalization aims at learning domain invariant features by utilizing data from multiple domains (data sites, corhorts, batches, vendors) so the learned feature can generalize to new unseen domains (distributions).
+Neural networks trained using data from a specific distribution (domain) usually fail to generalize to novel distributions (domains). Domain generalization aims at learning domain invariant features by utilizing data from multiple domains (data sites, cohorts, batches, vendors) so the learned feature can be generalized to new unseen domains (distributions).
 
-DomainLab is a software platform with state-of-the-art domain generalization algorithms implemented, designed by maximal decoupling of different software components thus enhances maximal code reuse.
+DomainLab is a software platform with state-of-the-art domain generalization algorithms implemented and designed by maximal decoupling of different software components thus enhancing maximal code reuse.
 
 ### DomainLab
 DomainLab decouples the following concepts or objects:
-- task $M$: In DomainLab, a task is a container for datasets from different domains. (e.g. from distribution $D_1$ and $D_2$). Task offer a static protocol to evaluate the generalization performance of a neural network: which dataset(s) is used for training, wich dataset(s) used for testing.  
-- neural network: a map $\phi$ from the input data to the feature space and a map $\varphi$ from feature space to output $\hat{y}$ (e.g. decision variable).
+- task $M$: In DomainLab, a task is a container for datasets from different domains. (e.g. from distribution $D_1$ and $D_2$). The task offers a static protocol to evaluate the generalization performance of a neural network: which dataset(s) is used for training, and which dataset(s) is used for testing.  
+- neural network: a map $\phi$ from the input data to the feature space and a map $\varphi$ from the feature space to output $\hat{y}$ (e.g. decision variable).
 - model: structural risk in the form of $\ell() + \mu R()$  where
-  - $\ell(Y, \hat{y}=\varphi(\phi(X)))$ is the task specific empirical loss (e.g. cross entropy for classification task).
+  - $\ell(Y, \hat{y}=\varphi(\phi(X)))$ is the task-specific empirical loss (e.g. cross entropy for classification task).
   - $R(\phi(X))$ is the penalty loss to boost domain invariant feature extraction using $\phi$.
   - $\mu$ is the corresponding multiplier to each penalty function factor.
 - trainer:  an object that guides the data flow to model and append further domain invariant losses
 like inter-domain feature alignment.
 
-We offer detailed documentation on how these models and trainers work in our documentation page: https://marrlab.github.io/DomainLab/
+We offer detailed documentation on how these models and trainers work on our documentation page: https://marrlab.github.io/DomainLab/
 
-DomainLab makes it possible to combine models with models, trainers with models, and trainers with trainers in a decorator pattern like line of code `Trainer A(Trainer B(Model C(Model D(network E), network E, network F)))` which correspond to $\ell() + \mu_a R_a() + \mu_b R_b + \mu_c R_c() + \mu_d R_d()$, where Model C and Model D share neural network E, but Model C has an extra neural network F. All models share the same neural network for feature extraction, but can have different auxilliary networks for $R()$.
+DomainLab makes it possible to combine models with models, trainers with models, and trainers with trainers in a decorator pattern like the line of code below
+
+```
+Trainer A(
+		  Trainer B(Model C(
+						    Model D(network E),
+							network E,
+							network F
+						   )
+				   )
+	     )
+```
+
+which correspond to $\ell() + \mu_a R_a() + \mu_b R_b + \mu_c R_c() + \mu_d R_d()$, where Model C and Model D share neural network E, but Model C has an extra neural network F. All models share the same neural network for feature extraction, but can have different auxiliary networks for $R()$.
 
 <div style="align: center; text-align:center;">
 <figure>  
@@ -36,7 +49,7 @@ DomainLab makes it possible to combine models with models, trainers with models,
 ## Getting started
 
 ### Installation
-For development version in Github, see [Installation and Dependencies handling](./docs/doc_install.md)
+For the development version in Github, see [Installation and Dependencies handling](./docs/doc_install.md)
 
 We also offer a PyPI version here https://pypi.org/project/domainlab/  which one could install via `pip install domainlab` and it is recommended to create a virtual environment for it.
 

From 0bac0c5d186a8363aaa7e0efaee213934133276c Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Mon, 29 Apr 2024 18:55:37 +0200
Subject: [PATCH 041/273] Added documentation for creating a model

---
 docs/doc_model.md | 29 +++++++++++++++++++++++++++++
 1 file changed, 29 insertions(+)
 create mode 100644 docs/doc_model.md

diff --git a/docs/doc_model.md b/docs/doc_model.md
new file mode 100644
index 000000000..bf83c0239
--- /dev/null
+++ b/docs/doc_model.md
@@ -0,0 +1,29 @@
+# Model Specification
+
+Domainlab is built to easily extend to other models. There exist two options. One is to implement a new model from scratch and add it to the existing models; the other is to extend the custom model abstract class. This guide outlines the necessary steps to add a new model to the domain generalization framework for both approaches mentioned above.
+
+## Option 1: Extend the Custom Model Class
+Create a new model by extending `AModelCustom`.
+
+
+Because `AModelCustom` extends `AModelClassif`, the only function a custom model needs to extend is `dict_net_module_na2arg_na`, which returns a dictionary with the key being the Pytorch module name and value being the command-line argument name. In addition, it is necessary to specify a function called `get_node_na` in the same Python file, which returns the custom algorithm builder as shown [here](../examples/models/demo_custom_model.py).  
+
+To run the custom model, follow the examples [here](./doc_examples.md) under 'Custom algorithm defined in external python file'. It also shows an example of using additional command line arguments. 
+
+
+## Option 2: Add alongside existing models
+If the repository is cloned and it is possible to add files to the source code, one can extend one of the other base classes: `AModel` or `AModelClassif`.
+
+### Step 1: Implement Required Abstract Methods
+Implement all abstract methods from the base class. For `AModel`, it is required to implement the following methods:
+
+`cal_task_loss(self, tensor_x, tensor_y)`: Computes the loss for the primary task, which for classification could be cross-entropy. <br>
+`_cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None)`: Calculates the task independent regularization loss. 
+
+### Step 2: Add Additional Arguments
+If additional arguments for the model are needed,  it is possible to specify a Python file with functionality for the argument parsing, as done [here](../domainlab/models/args_vae.py). The specified function needs to be applied in the  [arg_parser.py](../domainlab/arg_parser.py) in the domainlab root directory in order to add the parameters to the argument dictionary. 
+
+### Step 3: Create a Builder
+After specifying the model and retrieving the correct parameters, we can create functionality to create the model. To do so, we need to create a NodeAlgoBuilder. For that, we create a class that inherits from `NodeAlgoBuilder` and extend the `init_business(exp)` method. We must create the trainer, model, observer, and device in this method. See [here](../domainlab/algos/builder_dann.py) for an example. 
+
+After that, we can add the builder into the chain that creates all specified models [here](../domainlab/algos/zoo_algos.py). 
\ No newline at end of file

From a37a12f437e2133a389ea1f8820e7e531fdb7e40 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 30 Apr 2024 09:29:48 +0200
Subject: [PATCH 042/273] added print to specficy which subfolder names dont
 match

---
 domainlab/dsets/dset_subfolder.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/domainlab/dsets/dset_subfolder.py b/domainlab/dsets/dset_subfolder.py
index 0d29f18b6..0645297fe 100644
--- a/domainlab/dsets/dset_subfolder.py
+++ b/domainlab/dsets/dset_subfolder.py
@@ -152,6 +152,8 @@ def _find_classes(self, mdir):
         if not flag_user_input_classes_in_folder:
             logger.info(f"user provided class names: {self.list_class_dir}")
             logger.info(f"subfolder names from folder: {mdir} {classes}")
+            unmatched_names = set(self.list_class_dir) - set(classes)
+            logger.info(f"unmatched names: {unmatched_names}")
             raise RuntimeError(
                 "user provided class names does not match the subfolder names"
             )

From fc985280f5f04b8e4a4e3ac029648be861e0d94b Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 30 Apr 2024 09:32:41 +0200
Subject: [PATCH 043/273] changed wording

---
 domainlab/dsets/dset_subfolder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/domainlab/dsets/dset_subfolder.py b/domainlab/dsets/dset_subfolder.py
index 0645297fe..d9261c54f 100644
--- a/domainlab/dsets/dset_subfolder.py
+++ b/domainlab/dsets/dset_subfolder.py
@@ -153,7 +153,7 @@ def _find_classes(self, mdir):
             logger.info(f"user provided class names: {self.list_class_dir}")
             logger.info(f"subfolder names from folder: {mdir} {classes}")
             unmatched_names = set(self.list_class_dir) - set(classes)
-            logger.info(f"unmatched names: {unmatched_names}")
+            logger.info(f"unmatched class names provided by user: {unmatched_names}")
             raise RuntimeError(
                 "user provided class names does not match the subfolder names"
             )

From b80f2c91db98dd6afc19a3a79da6fad208c6176d Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 30 Apr 2024 10:20:53 +0200
Subject: [PATCH 044/273] made the validation accuracy optional for the if stop
 method, and accessing it in a safer way

---
 domainlab/algos/msels/a_model_sel.py     | 4 ++--
 domainlab/algos/observers/b_obvisitor.py | 3 ++-
 examples/conf/vlcs_diva_mldg_dial.yaml   | 2 +-
 3 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index ed7dbc418..6a593c9b3 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -74,7 +74,7 @@ def base_update(self, clear_counter=False):
         return boolean
         """
 
-    def if_stop(self, acc_val):
+    def if_stop(self, acc_val = None):
         """
         check if trainer should stop and additionally tests for validation threshold
         return boolean
@@ -83,7 +83,7 @@ def if_stop(self, acc_val):
         # be careful to always override it in child class
         # only if the child class has a decorator which will
         # dispatched.
-        if self.msel is not None:
+        if self.msel is not None and acc_val is not None:
             if self._val_threshold is not None and acc_val < self._val_threshold:
                 return False
         return self.early_stop()
diff --git a/domainlab/algos/observers/b_obvisitor.py b/domainlab/algos/observers/b_obvisitor.py
index d746dbf1a..432da9703 100644
--- a/domainlab/algos/observers/b_obvisitor.py
+++ b/domainlab/algos/observers/b_obvisitor.py
@@ -57,7 +57,8 @@ def update(self, epoch):
             logger.info("better model found")
             self.host_trainer.model.save()
             logger.info("persisted")
-        flag_stop = self.model_sel.if_stop(self.metric_val["acc"])
+        acc = self.metric_te.get("acc")
+        flag_stop = self.model_sel.if_stop(acc)
         flag_enough = epoch >= self.host_trainer.aconf.epos_min
         return flag_stop & flag_enough
 
diff --git a/examples/conf/vlcs_diva_mldg_dial.yaml b/examples/conf/vlcs_diva_mldg_dial.yaml
index ac2d83337..5ed10d0c5 100644
--- a/examples/conf/vlcs_diva_mldg_dial.yaml
+++ b/examples/conf/vlcs_diva_mldg_dial.yaml
@@ -1,7 +1,7 @@
 te_d: caltech                       # domain name of test domain
 tpath: examples/tasks/task_vlcs.py  # python file path to specify the task
 bs: 2                               # batch size
-val_threshold: 0.8
+val_threshold: 0.8                  # threashold before which training does not stop
 model: dann_diva                    # combine model DANN with DIVA
 epos: 1                             # number of epochs
 trainer: mldg_dial                  # combine trainer MLDG and DIAL

From cc650addd27be3922bfcee46fdc2d3fe1dc86700 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 30 Apr 2024 10:48:10 +0200
Subject: [PATCH 045/273] Removed diva from tests and yaml for gamma hyperparam

---
 domainlab/models/a_model.py                 | 2 +-
 domainlab/utils/hyperparameter_retrieval.py | 2 --
 examples/conf/vlcs_diva_mldg_dial.yaml      | 3 +--
 tests/test_hyperparameter_retrieval.py      | 8 ++++----
 4 files changed, 6 insertions(+), 9 deletions(-)

diff --git a/domainlab/models/a_model.py b/domainlab/models/a_model.py
index 1b7e652f4..71b0db334 100644
--- a/domainlab/models/a_model.py
+++ b/domainlab/models/a_model.py
@@ -196,7 +196,7 @@ def name(self):
         na_class = type(self).__name__
         if na_class[:len_prefix] != na_prefix:
             raise RuntimeError(
-                "Trainer builder node class must start with ",
+                "Model builder node class must start with ",
                 na_prefix,
                 "the current class is named: ",
                 na_class,
diff --git a/domainlab/utils/hyperparameter_retrieval.py b/domainlab/utils/hyperparameter_retrieval.py
index d47135554..9b3c97e7e 100644
--- a/domainlab/utils/hyperparameter_retrieval.py
+++ b/domainlab/utils/hyperparameter_retrieval.py
@@ -7,9 +7,7 @@ def get_gamma_reg(args, model_name):
     Retrieves either a shared gamma regularization, or individual ones for each specified object
     """
     gamma_reg = args.gamma_reg
-    print(gamma_reg)
     if isinstance(gamma_reg, dict):
-        print("is instance dict")
         if model_name in gamma_reg:
             return gamma_reg[model_name]
         if 'default' in gamma_reg:
diff --git a/examples/conf/vlcs_diva_mldg_dial.yaml b/examples/conf/vlcs_diva_mldg_dial.yaml
index 5cf1a8041..71b376a03 100644
--- a/examples/conf/vlcs_diva_mldg_dial.yaml
+++ b/examples/conf/vlcs_diva_mldg_dial.yaml
@@ -7,8 +7,7 @@ epos: 1                             # number of epochs
 trainer: mldg_dial                  # combine trainer MLDG and DIAL
 gamma_reg: 
   default: 1.0
-  dann: 1.5                        
-  diva: 2.0
+  dann: 1.5     
 gamma_y: 700000.0                   # hyperparameter of diva
 gamma_d: 100000.0                   # hyperparameter of diva
 npath: examples/nets/resnet.py      # neural network for class classification
diff --git a/tests/test_hyperparameter_retrieval.py b/tests/test_hyperparameter_retrieval.py
index e166e320b..fa3119e98 100644
--- a/tests/test_hyperparameter_retrieval.py
+++ b/tests/test_hyperparameter_retrieval.py
@@ -13,8 +13,8 @@ def test_store_dict_key_pair_single_value():
 def test_store_dict_key_pair_dict_value():
     """Test to parse a dict for the gamma_reg"""
     parser = mk_parser_main()
-    args = parser.parse_args(['--gamma_reg', 'dann=1.0,diva=2.0'])
-    assert args.gamma_reg == {'dann': 1.0, 'diva': 2.0}
+    args = parser.parse_args(['--gamma_reg', 'dann=1.0,jigen=2.0'])
+    assert args.gamma_reg == {'dann': 1.0, 'jigen': 2.0}
 
 def test_get_gamma_reg_single_value():
     """Test to retrieve a single gamma_reg parameter which is applied to all objects"""
@@ -25,8 +25,8 @@ def test_get_gamma_reg_single_value():
 def test_get_gamma_reg_dict_value():
     """Test to retrieve a dict of gamma_reg parameters for different objects"""
     parser = mk_parser_main()
-    args = parser.parse_args(['--gamma_reg', 'default=5.0,dann=1.0,diva=2.0'])
+    args = parser.parse_args(['--gamma_reg', 'default=5.0,dann=1.0,jigen=2.0'])
     print(args)
     assert get_gamma_reg(args, 'dann') == 1.0
-    assert get_gamma_reg(args, 'diva') == 2.0
+    assert get_gamma_reg(args, 'jigen') == 2.0
     assert get_gamma_reg(args, 'nonexistent') == 5.0

From 3fbd5ce0c21a030d9d545d4f30fbe8a6fe304891 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 2 May 2024 15:59:36 +0200
Subject: [PATCH 046/273] change key value order

---
 examples/tasks/task_blood3.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/tasks/task_blood3.py b/examples/tasks/task_blood3.py
index 416eb893e..595b44e93 100644
--- a/examples/tasks/task_blood3.py
+++ b/examples/tasks/task_blood3.py
@@ -75,13 +75,13 @@
         },
         "mll": {
             "basophil": "basophil",
-            "erythroblast": "normoblast",
+            "normoblast":"erythroblast",
             "metamyelocyte": "metamyelocyte",
             "myeloblast": "myeloblast",
             "neutrophil_band": "neutrophil_band",
             "promyelocyte": "promyelocyte",
             "eosinophil": "eosinophil",
-            "lymphocyte_typical": "lymphocyte",
+            "lymphocyte": "lymphocyte_typical",
             "monocyte": "monocyte",
             "myelocyte": "myelocyte",
             "neutrophil_segmented": "neutrophil_segmented",

From 649046979c5520e3a56d8f95fe4c9f83546c6c90 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 3 May 2024 10:38:38 +0200
Subject: [PATCH 047/273] Added documentation for trainer

---
 docs/doc_trainer.md | 44 ++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 44 insertions(+)
 create mode 100644 docs/doc_trainer.md

diff --git a/docs/doc_trainer.md b/docs/doc_trainer.md
new file mode 100644
index 000000000..757694af4
--- /dev/null
+++ b/docs/doc_trainer.md
@@ -0,0 +1,44 @@
+# Model Specification
+
+When developing new trainers, you can extend the `TrainerBasic` class. This allows you to build upon established training routines while introducing specialized behaviors tailored to your model.
+
+### Steps to Extend `TrainerBasic`
+
+1. **Extend the class**: Begin by inheriting from [`TrainerBasic`](../domainlab/algos/trainers/train_basic.py).
+
+2. **Customize Key Methods**: You have several methods that you can override to customize the trainer's behavior. Here's a brief overview of what they do:
+
+    - **`before_tr(self)`**: Set up necessary configurations or states before training begins. Useful for initial logging or setting model to train mode.
+    
+    - **`tr_epoch(self, epoch)`**: Define the training logic for each epoch. This is where the bulk of your model's training will be implemented.
+    
+    - **`before_epoch(self)`**: Prepare anything specific at the start of each epoch, like resetting counters or updating learning rate schedules.
+    
+    - **`after_epoch(self, epoch)`**: Typically used for logging and validation checks after each epoch.
+    
+    - **`tr_batch(self, tensor_x, tensor_y, tensor_d, others, ind_batch, epoch)`**: Handle the processing of each batch. This includes forward and backward propagation.
+    
+    - **`before_batch(self, epoch, ind_batch)`** and **`after_batch(self, epoch, ind_batch)`**: Perform actions right before and after processing a batch, respectively. Useful for implementing behaviors like batch-wise logging or applying gradients.
+
+3. **Register Your Trainer**: Make sure the framework can utilize the new trainer. For that, it is necessary to register it in the [zoo_trainers.py](../domainlab/algos/trainers/zoo_trainer.py).
+
+### Example Implementation
+
+Here is a simple example of a custom trainer that logs additional details at the start of each training:
+
+```python
+class MyCustomTrainer(TrainerBasic):
+    def before_tr(self):
+        super().before_tr()  # Ensure to call the base method if needed
+        print("Starting training session.")
+
+    def tr_epoch(self, epoch):
+        # Custom training logic for each epoch
+        for ind_batch, data in enumerate(self.loader_tr):
+            self.tr_batch(data, ind_batch, epoch)
+        print(f"Completed epoch {epoch}")
+
+    def tr_batch(self, data, ind_batch, epoch):
+        # Process each batch
+        super().tr_batch(data, ind_batch, epoch)  # Optionally call the base method
+        print(f"Batch {ind_batch} of epoch {epoch} processed.")

From 264343bbb6ac6c4ef12baf8f3f962875bfd9add7 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 08:59:47 +0200
Subject: [PATCH 048/273] merged gamma_reg_collision

---
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diff --git a/.gitignore b/.gitignore
index edfe19c37..2e1aa7a74 100644
--- a/.gitignore
+++ b/.gitignore
@@ -4,4 +4,4 @@
 tests/__pycache__/
 *.pyc
 .vscode/
-data/pacs
+domainlab/zdata/pacs
diff --git a/README.md b/README.md
index ccedf4048..b349654ba 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,119 @@
-# M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling
+# DomainLab: modular python package for training domain invariant neural networks
 
+![GH Actions CI ](https://github.com/marrlab/DomainLab/actions/workflows/ci.yml/badge.svg?branch=master)
+[![codecov](https://codecov.io/gh/marrlab/DomainLab/branch/master/graph/badge.svg)](https://app.codecov.io/gh/marrlab/DomainLab)
+[![Codacy Badge](https://app.codacy.com/project/badge/Grade/bc22a1f9afb742efb02b87284e04dc86)](https://www.codacy.com/gh/marrlab/DomainLab/dashboard)
+[![Documentation](https://img.shields.io/badge/Documentation-Here)](https://marrlab.github.io/DomainLab/)
+[![pages-build-deployment](https://github.com/marrlab/DomainLab/actions/workflows/pages/pages-build-deployment/badge.svg)](https://github.com/marrlab/DomainLab/actions/workflows/pages/pages-build-deployment)
+
+## Distribution shifts, domain generalization and DomainLab
+
+Neural networks trained using data from a specific distribution (domain) usually fails to generalize to novel distributions (domains). Domain generalization aims at learning domain invariant features by utilizing data from multiple domains (data sites, corhorts, batches, vendors) so the learned feature can generalize to new unseen domains (distributions).
+
+DomainLab is a software platform with state-of-the-art domain generalization algorithms implemented, designed by maximal decoupling of different software components thus enhances maximal code reuse.
+
+### DomainLab
+DomainLab decouples the following concepts or objects:
+- task $M$: In DomainLab, a task is a container for datasets from different domains. (e.g. from distribution $D_1$ and $D_2$). Task offer a static protocol to evaluate the generalization performance of a neural network: which dataset(s) is used for training, wich dataset(s) used for testing.  
+- neural network: a map $\phi$ from the input data to the feature space and a map $\varphi$ from feature space to output $\hat{y}$ (e.g. decision variable).
+- model: structural risk in the form of $\ell() + \mu R()$  where
+  - $\ell(Y, \hat{y}=\varphi(\phi(X)))$ is the task specific empirical loss (e.g. cross entropy for classification task).
+  - $R(\phi(X))$ is the penalty loss to boost domain invariant feature extraction using $\phi$.
+  - $\mu$ is the corresponding multiplier to each penalty function factor.
+- trainer:  an object that guides the data flow to model and append further domain invariant losses
+like inter-domain feature alignment.
+
+We offer detailed documentation on how these models and trainers work in our documentation page: https://marrlab.github.io/DomainLab/
+
+DomainLab makes it possible to combine models with models, trainers with models, and trainers with trainers in a decorator pattern like line of code `Trainer A(Trainer B(Model C(Model D(network E), network E, network F)))` which correspond to $\ell() + \mu_a R_a() + \mu_b R_b + \mu_c R_c() + \mu_d R_d()$, where Model C and Model D share neural network E, but Model C has an extra neural network F. All models share the same neural network for feature extraction, but can have different auxilliary networks for $R()$.
+
+<div style="align: center; text-align:center;">
+<figure>  
+<img src="https://github.com/marrlab/DomainLab/blob/master/docs/figs/invarfeat4dg.png?raw=true" style="width:300px;"/> 
+</figure>
+</div>
+
+### M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling
 Source: https://arxiv.org/pdf/2403.13728.pdf
 
+## Getting started
+
+### Installation
+For development version in Github, see [Installation and Dependencies handling](./docs/doc_install.md)
+
+We also offer a PyPI version here https://pypi.org/project/domainlab/  which one could install via `pip install domainlab` and it is recommended to create a virtual environment for it.
+
+### Task specification
+We offer various ways for the user to specify a scenario to evaluate the generalization performance via training on a limited number of datasets. See detail in
+[Task Specification](./docs/doc_tasks.md) 
+
+### Example and usage
+#### Available arguments for commandline
+
+The following command tells which arguments/hyperparameters/multipliers are available to be set by the user and which model they are associated with
+
+```shell
+python main_out.py --help
+```
+
+or 
+
+```
+domainlab --help
+```
+
+#### Command line configuration file
+
+`domainlab -c ./examples/conf/vlcs_diva_mldg_dial.yaml` (if you install via pip)
+
+or if you clone this the code repository for DomainLab
+
+`python main_out.py -c ./examples/conf/vlcs_diva_mldg_dial.yaml`
+
+where the configuration file below can be downloaded [here](https://raw.githubusercontent.com/marrlab/DomainLab/master/examples/conf/vlcs_diva_mldg_dial.yaml)
+```
+te_d: caltech                       # domain name of test domain
+tpath: examples/tasks/task_vlcs.py  # python file path to specify the task
+bs: 2                               # batch size
+model: dann_diva                    # combine model DANN with DIVA
+epos: 1                             # number of epochs
+trainer: mldg_dial                  # combine trainer MLDG and DIAL
+gamma_y: 700000.0                   # hyperparameter of diva
+gamma_d: 100000.0                   # hyperparameter of diva
+npath: examples/nets/resnet.py      # neural network for class classification
+npath_dom: examples/nets/resnet.py  # neural network for domain classification
+```
+See details in [Command line usage](./docs/doc_usage_cmd.md)
+
+#### or Programm against DomainLab API
+
+See example here: [Transformer as feature extractor, decorate JIGEN with DANN, training using MLDG decorated by DIAL](https://github.com/marrlab/DomainLab/blob/master/examples/api/jigen_dann_transformer.py)
+
+
+### Benchmark different methods
+DomainLab provides a powerful benchmark functionality.
+To benchmark several algorithms(combination of neural networks, models, trainers and associated hyperparameters), a single line command along with a benchmark configuration files is sufficient. See details in [benchmarks documentation and tutorial](./docs/doc_benchmark.md)
+
+One could simply run
+`bash run_benchmark_slurm.sh your_benchmark_configuration.yaml` to launch different experiments with specified configuraiton.
+
+
+For example,  the following result (without any augmentation like flip) is for PACS dataset using ResNet. The reader should note that using different neural network, whether pre-trained or not, what kind of preprocessinga and augmentation to use can lead to very different result distributions, which is one of the features DomainLab provide: the above factors get decoupled in DomainLab. 
+
+<div style="align: center; text-align:center;">
+<figure>  
+<img src="https://github.com/marrlab/DomainLab/blob/master/docs/figs/stochastic_variation_two_rows.png?raw=true" style="width:800px;"/>
+<div class="caption" style="align: center; text-align:center;">
+<figcaption>Benchmark results plot generated from DomainLab, where each rectangle represent one model trainer combination, each bar inside the rectangle represent a unique hyperparameter index associated with that method combination, each dot represent a random seeds.</figcaption>
+</div>
+</figure>
+</div>
+
+
+### Citation
+
+Source: https://arxiv.org/pdf/2403.14356.pdf
+
 Citation:
 ```bibtex
 @misc{sun2024m,
@@ -12,6 +124,12 @@ Citation:
   year={2024},
   publisher={https://arxiv.org/pdf/2403.13728.pdf}
 }
+@misc{sun2024domainlab,
+  title={DomainLab: A modular Python package for domain generalization in deep learning},
+  author={Sun, Xudong and Feistner, Carla and Gossmann, Alexej and Schwarz, George and Umer, Rao Muhammad and Beer, Lisa and Rockenschaub, Patrick and Shrestha, Rahul Babu and Gruber, Armin and Chen, Nutan and others},
+  journal={https://arxiv.org/pdf/2403.14356.pdf},
+  year={2024}
+}
 ```
 
 
diff --git a/data/mixed_codec/caltech/auto/text.txt b/data/mixed_codec/caltech/auto/text.txt
deleted file mode 100644
index 557db03de..000000000
--- a/data/mixed_codec/caltech/auto/text.txt
+++ /dev/null
@@ -1 +0,0 @@
-Hello World
diff --git a/data/mixed_codec/caltech/auto/train_imgs_150.jpg b/data/mixed_codec/caltech/auto/train_imgs_150.jpg
deleted file mode 100644
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diff --git a/data/pacs_mini_10/main.sh b/data/pacs_mini_10/main.sh
deleted file mode 100644
index 8e44c8183..000000000
--- a/data/pacs_mini_10/main.sh
+++ /dev/null
@@ -1,7 +0,0 @@
-#!/bin/bash
-# first argument is the file with pointers to image
-# s
-bash run_with_bash_copy_files_according2txt.sh ../pacs_split/art_painting_10.txt ~/Documents/dataset/PACS/raw .
-bash run_with_bash_copy_files_according2txt.sh ../pacs_split/cartoon_10.txt ~/Documents/dataset/PACS/raw .
-bash run_with_bash_copy_files_according2txt.sh ../pacs_split/photo_10.txt ~/Documents/dataset/PACS/raw .
-bash run_with_bash_copy_files_according2txt.sh ../pacs_split/sketch_10.txt ~/Documents/dataset/PACS/raw .
diff --git a/data/pacs_mini_10/photo/dog/n02103406_1011.jpg b/data/pacs_mini_10/photo/dog/n02103406_1011.jpg
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diff --git a/data/pacs_mini_10/run_with_bash_copy_files_according2txt.sh b/data/pacs_mini_10/run_with_bash_copy_files_according2txt.sh
deleted file mode 100644
index 695e46218..000000000
--- a/data/pacs_mini_10/run_with_bash_copy_files_according2txt.sh
+++ /dev/null
@@ -1,26 +0,0 @@
-#!/bin/bash
-input=$1
-path=$2
-
-# test string array works
-sentence="this is a story"
-stringarray=($sentence)
-echo "${stringarray[0]}"
-
-while IFS= read -r line
-do
-  echo "$line"
-  stringarray=($line)
-  echo "${stringarray[0]}"
-  relativepath=${stringarray[0]}
-  fullpath="$path/$relativepath"
-  echo "fullpath is $fullpath"
-  newpath="$3/$relativepath"
-  echo "newpath is $newpath"
-  newpath2=`dirname "$newpath"`
-  echo "newpath2 is $newpath2"
-  mkdir -p "$newpath2"
-  cp "$fullpath" "$newpath2"
-  # cp "$fullpath" --parent "$3"
-
-done < "$input"
diff --git a/data/pacs_mini_10/sketch/dog/5302.png b/data/pacs_mini_10/sketch/dog/5302.png
deleted file mode 100644
index 3ec54e87ba4a4633e2ded07274a0cea856cea41b..0000000000000000000000000000000000000000
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diff --git a/data/pacs_split/art_painting_10.txt b/data/pacs_split/art_painting_10.txt
deleted file mode 100644
index 77f7627a2..000000000
--- a/data/pacs_split/art_painting_10.txt
+++ /dev/null
@@ -1,10 +0,0 @@
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diff --git a/data/pacs_split/art_painting_100.txt b/data/pacs_split/art_painting_100.txt
deleted file mode 100644
index 7da95eda1..000000000
--- a/data/pacs_split/art_painting_100.txt
+++ /dev/null
@@ -1,100 +0,0 @@
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diff --git a/data/pacs_split/art_painting_crossval_kfold.txt b/data/pacs_split/art_painting_crossval_kfold.txt
deleted file mode 100644
index 61b3f44e1..000000000
--- a/data/pacs_split/art_painting_crossval_kfold.txt
+++ /dev/null
@@ -1,208 +0,0 @@
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diff --git a/data/pacs_split/art_painting_test_kfold.txt b/data/pacs_split/art_painting_test_kfold.txt
deleted file mode 100644
index 9a5728738..000000000
--- a/data/pacs_split/art_painting_test_kfold.txt
+++ /dev/null
@@ -1,2048 +0,0 @@
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diff --git a/data/pacs_split/art_painting_train_kfold.txt b/data/pacs_split/art_painting_train_kfold.txt
deleted file mode 100644
index 8b5405715..000000000
--- a/data/pacs_split/art_painting_train_kfold.txt
+++ /dev/null
@@ -1,1840 +0,0 @@
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diff --git a/data/pacs_split/cartoon_10.txt b/data/pacs_split/cartoon_10.txt
deleted file mode 100644
index 9c90dce46..000000000
--- a/data/pacs_split/cartoon_10.txt
+++ /dev/null
@@ -1,10 +0,0 @@
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diff --git a/data/pacs_split/cartoon_100.txt b/data/pacs_split/cartoon_100.txt
deleted file mode 100644
index 678652e4c..000000000
--- a/data/pacs_split/cartoon_100.txt
+++ /dev/null
@@ -1,100 +0,0 @@
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diff --git a/data/pacs_split/cartoon_crossval_kfold.txt b/data/pacs_split/cartoon_crossval_kfold.txt
deleted file mode 100644
index e8374913b..000000000
--- a/data/pacs_split/cartoon_crossval_kfold.txt
+++ /dev/null
@@ -1,237 +0,0 @@
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diff --git a/data/pacs_split/cartoon_test_kfold.txt b/data/pacs_split/cartoon_test_kfold.txt
deleted file mode 100644
index 5daf9281e..000000000
--- a/data/pacs_split/cartoon_test_kfold.txt
+++ /dev/null
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diff --git a/data/pacs_split/cartoon_train_kfold.txt b/data/pacs_split/cartoon_train_kfold.txt
deleted file mode 100644
index 48ceb2f88..000000000
--- a/data/pacs_split/cartoon_train_kfold.txt
+++ /dev/null
@@ -1,2107 +0,0 @@
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diff --git a/data/pacs_split/photo_10.txt b/data/pacs_split/photo_10.txt
deleted file mode 100644
index 59ba86d76..000000000
--- a/data/pacs_split/photo_10.txt
+++ /dev/null
@@ -1,10 +0,0 @@
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diff --git a/data/pacs_split/photo_100.txt b/data/pacs_split/photo_100.txt
deleted file mode 100644
index 9a0951918..000000000
--- a/data/pacs_split/photo_100.txt
+++ /dev/null
@@ -1,100 +0,0 @@
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diff --git a/data/pacs_split/photo_crossval_kfold.txt b/data/pacs_split/photo_crossval_kfold.txt
deleted file mode 100644
index e001ac79e..000000000
--- a/data/pacs_split/photo_crossval_kfold.txt
+++ /dev/null
@@ -1,171 +0,0 @@
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diff --git a/data/pacs_split/photo_test_kfold.txt b/data/pacs_split/photo_test_kfold.txt
deleted file mode 100644
index 643ed4aa8..000000000
--- a/data/pacs_split/photo_test_kfold.txt
+++ /dev/null
@@ -1,1670 +0,0 @@
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diff --git a/data/pacs_split/photo_train_kfold.txt b/data/pacs_split/photo_train_kfold.txt
deleted file mode 100644
index 5edd1d10a..000000000
--- a/data/pacs_split/photo_train_kfold.txt
+++ /dev/null
@@ -1,1499 +0,0 @@
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diff --git a/data/pacs_split/readme.txt b/data/pacs_split/readme.txt
deleted file mode 100644
index 36a00efc7..000000000
--- a/data/pacs_split/readme.txt
+++ /dev/null
@@ -1,10 +0,0 @@
-
-1. The h5py files was pre-read using cv2, so it is BGR channel order.
-2. This benckmark is sensitive to the different train val splits, so please use this train val splits for the fair comparisons.
-
-https://drive.google.com/uc?id=1JFr8f805nMUelQWWmfnJR3y4_SYoN5Pd
-
-[https://drive.google.com/uc?id=1JFr8f805nMUelQWWmfnJR3y4_SYoN5Pd](https://drive.google.com/uc?id=1JFr8f805nMUelQWWmfnJR3y4_SYoN5Pd)
-
-
-https://github.com/facebookresearch/DomainBed/blob/4294ec699df761b46a1505734f6be16ef009cad9/domainbed/scripts/download.py#L29
diff --git a/data/pacs_split/sketch_10.txt b/data/pacs_split/sketch_10.txt
deleted file mode 100644
index 79f855d52..000000000
--- a/data/pacs_split/sketch_10.txt
+++ /dev/null
@@ -1,10 +0,0 @@
-sketch/house/8873.png 6
-sketch/guitar/n03467517_6423-3.png 4
-sketch/elephant/5981.png 2
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-sketch/dog/5317.png 1
diff --git a/data/pacs_split/sketch_100.txt b/data/pacs_split/sketch_100.txt
deleted file mode 100644
index 2856e053f..000000000
--- a/data/pacs_split/sketch_100.txt
+++ /dev/null
@@ -1,100 +0,0 @@
-sketch/guitar/n02676566_6704-1.png 4
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diff --git a/data/pacs_split/sketch_crossval_kfold.txt b/data/pacs_split/sketch_crossval_kfold.txt
deleted file mode 100644
index 63c0f2050..000000000
--- a/data/pacs_split/sketch_crossval_kfold.txt
+++ /dev/null
@@ -1,398 +0,0 @@
-sketch/dog/n02103406_343-1.png 1
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diff --git a/data/pacs_split/sketch_test_kfold.txt b/data/pacs_split/sketch_test_kfold.txt
deleted file mode 100644
index c27970b06..000000000
--- a/data/pacs_split/sketch_test_kfold.txt
+++ /dev/null
@@ -1,3929 +0,0 @@
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diff --git a/data/pacs_split/sketch_train_kfold.txt b/data/pacs_split/sketch_train_kfold.txt
deleted file mode 100644
index a5088dca0..000000000
--- a/data/pacs_split/sketch_train_kfold.txt
+++ /dev/null
@@ -1,3531 +0,0 @@
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diff --git a/data/patches_permutation4jigsaw/permutations_100.npy b/data/patches_permutation4jigsaw/permutations_100.npy
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diff --git a/data/script/download_pacs.py b/data/script/download_pacs.py
deleted file mode 100644
index 51c346f24..000000000
--- a/data/script/download_pacs.py
+++ /dev/null
@@ -1,64 +0,0 @@
-"this script can be used to download the pacs dataset"
-import os
-import tarfile
-from zipfile import ZipFile
-
-import gdown
-
-
-def stage_path(data_dir, name):
-    """
-    creates the path to data_dir/name
-    if it does not exist already
-    """
-    full_path = os.path.join(data_dir, name)
-
-    if not os.path.exists(full_path):
-        os.makedirs(full_path)
-
-    return full_path
-
-
-def download_and_extract(url, dst, remove=True):
-    """
-    downloads and extracts the data behind the url
-    and saves it at dst
-    """
-    gdown.download(url, dst, quiet=False)
-
-    if dst.endswith(".tar.gz"):
-        with open(dst, "r:gz") as tar:
-            tar.extractall(os.path.dirname(dst))
-        tar.close()
-
-    if dst.endswith(".tar"):
-        with open(dst, "r:") as tar:
-            tar.extractall(os.path.dirname(dst))
-        tar.close()
-
-    if dst.endswith(".zip"):
-        zfile = ZipFile(dst, "r")
-        zfile.extractall(os.path.dirname(dst))
-        zfile.close()
-
-    if remove:
-        os.remove(dst)
-
-
-def download_pacs(data_dir):
-    """
-    download and extract dataset pacs.
-    Dataset is saved at location data_dir
-    """
-    full_path = stage_path(data_dir, "PACS")
-
-    download_and_extract(
-        "https://drive.google.com/uc?id=1JFr8f805nMUelQWWmfnJR3y4_SYoN5Pd",
-        os.path.join(data_dir, "PACS.zip"),
-    )
-
-    os.rename(os.path.join(data_dir, "kfold"), full_path)
-
-
-if __name__ == "__main__":
-    download_pacs("../pacs")
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diff --git a/data/ztest_files/aggret_res_test1 b/data/ztest_files/aggret_res_test1
deleted file mode 100644
index f53acf3ae..000000000
--- a/data/ztest_files/aggret_res_test1
+++ /dev/null
@@ -1,2 +0,0 @@
-param_index, method, algo, epos, te_d, seed, params, acc, precision, recall, specificity, f1, auroc
-0, Task1, diva, 2, caltech, 1, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8098495
diff --git a/data/ztest_files/aggret_res_test11 b/data/ztest_files/aggret_res_test11
deleted file mode 100644
index 797cc5055..000000000
--- a/data/ztest_files/aggret_res_test11
+++ /dev/null
@@ -1,9 +0,0 @@
-param_index, method, algo, epos, te_d, seed, params, acc, precision, recall, specificity, f1, auroc
-0, Task1, diva, 2, caltech, 1, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8098495
-0, Task1, diva, 2, caltech, 2, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.8111111, 0.8232258, 0.6903785, 0.6903785, 0.71645665, 0.89284086
-1, Task1, diva, 2, caltech, 1, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8095455
-1, Task1, diva, 2, caltech, 2, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.82222223, 0.8609804, 0.6981304, 0.6981304, 0.7278397, 0.9361605
-0, Task2, hduva, 2, caltech, 1, "{'a': 1, 'b': 3}", 0.76, 0.76, 0.49, 0.56, 0.57, 0.76
-0, Task2, hduva, 2, caltech, 2, "{'a': 1, 'b': 3}", 0.81, 0.75, 0.45, 0.64, 0.75, 0.89
-1, Task2, hduva, 2, caltech, 1, "{'a': 2, 'b': 4}", 0.75, 0.81, 0.45, 0.54, 0.39, 0.88
-1, Task2, hduva, 2, caltech, 2, "{'a': 2, 'b': 4}", 0.73, 0.72, 0.51, 0.51, 0.6, 0.88
diff --git a/data/ztest_files/aggret_res_test2 b/data/ztest_files/aggret_res_test2
deleted file mode 100644
index 93104ef85..000000000
--- a/data/ztest_files/aggret_res_test2
+++ /dev/null
@@ -1,5 +0,0 @@
-param_index, method, algo, epos, te_d, seed, params, acc, precision, recall, specificity, f1, auroc
-0, Task1, diva, 2, caltech, 1, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8098495
-0, Task1, diva, 2, caltech, 2, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.8111111, 0.8232258, 0.6903785, 0.6903785, 0.71645665, 0.89284086
-2, Task1, diva, 2, caltech, 3, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.77397263, 0.82765615, 0.59528303, 0.59528303, 0.5953641, 0.74150944
-0, Task2, diva, 2, caltech, 1, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8098495
diff --git a/data/ztest_files/aggret_res_test21 b/data/ztest_files/aggret_res_test21
deleted file mode 100644
index 5bb677ba7..000000000
--- a/data/ztest_files/aggret_res_test21
+++ /dev/null
@@ -1,23 +0,0 @@
-param_index, method, algo, epos, te_d, seed, params, acc, precision, recall, specificity, f1, auroc
-0, Task1, diva, 2, caltech, 1, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8098495
-0, Task1, diva, 2, caltech, 2, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.8111111, 0.8232258, 0.6903785, 0.6903785, 0.71645665, 0.89284086
-2, Task1, diva, 2, caltech, 3, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.77397263, 0.82765615, 0.59528303, 0.59528303, 0.5953641, 0.74150944
-2, Task1, diva, 2, caltech, 4, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.851917, 0.7569983, 0.8873113, 0.8173113, 0.7985473, 0.8769811
-2, Task1, diva, 2, caltech, 5, "{'gamma_y': 1688039, 'gamma_d': 265711}", 0.84, 0.85, 0.615, 0.62, 0.62, 0.74
-1, Task1, diva, 2, caltech, 1, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.75, 0.87068963, 0.5588235, 0.5588235, 0.53100574, 0.8095455
-1, Task1, diva, 2, caltech, 2, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.82222223, 0.8609804, 0.6981304, 0.6981304, 0.7278397, 0.9361605
-1, Task1, diva, 2, caltech, 3, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.85397263, 0.95765615, 0.67528303, 0.6728303, 0.6853641, 0.81150944
-1, Task1, diva, 2, caltech, 4, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.971917, 0.8869983, 0.9273113, 0.9273113, 0.8285473, 0.9369811
-1, Task1, diva, 2, caltech, 5, "{'gamma_y': 3648291, 'gamma_d': 320432}", 0.92, 0.91, 0.74, 0.75, 0.67, 0.8
-0, Task2, hduva, 2, caltech, 1, "{'gamma_y': 97228, 'zy_dim': 76}", 0.76, 0.76, 0.49, 0.56, 0.57, 0.76
-0, Task2, hduva, 2, caltech, 2, "{'gamma_y': 97228, 'zy_dim': 76}", 0.81, 0.75, 0.45, 0.64, 0.75, 0.89
-0, Task2, hduva, 2, caltech, 3, "{'gamma_y': 97228, 'zy_dim': 76}", 0.8251667, 0.104563385, 0.10817383, 0.90109926, 0.08242064, 0.519054
-0, Task2, hduva, 2, caltech, 4, "{'gamma_y': 97228, 'zy_dim': 76}", 0.97535366, 0.88569593, 0.87402904, 0.98618114, 0.87845683, 0.99118155
-0, Task2, hduva, 2, caltech, 5, "{'gamma_y': 97228, 'zy_dim': 76}", 0.82422227, 0.10658247, 0.1084048, 0.9009563, 0.08635866, 0.51927835
-1, Task2, hduva, 2, caltech, 1, "{'gamma_y': 196616, 'zy_dim': 68}", 0.75, 0.81, 0.45, 0.54, 0.39, 0.88
-1, Task2, hduva, 2, caltech, 2, "{'gamma_y': 196616, 'zy_dim': 68}", 0.73, 0.72, 0.51, 0.51, 0.6, 0.88
-1, Task2, hduva, 2, caltech, 1, "{'gamma_y': 113475, 'zy_dim': 48}", 0.8551667, 0.204563385, 0.20817383, 0.80109926, 0.15242064, 0.559054
-1, Task2, hduva, 2, caltech, 2, "{'gamma_y': 113475, 'zy_dim': 48}", 0.57535366, 0.52569593, 0.41402904, 0.68618114, 0.57845683, 0.89118155
-1, Task2, hduva, 2, caltech, 3, "{'gamma_y': 113475, 'zy_dim': 48}", 0.72422227, 0.20658247, 0.2084048, 0.7009563, 0.18635866, 0.61927835
-1, Task2, erm, 2, caltech, 1, "{}", 0.5, 0.5, 0.5, 0.5, 0.5, 0.5
-1, Task2, erm, 2, caltech, 2, "{}", 0.4, 0.4, 0.4, 0.4, 0.4, 0.4
diff --git a/data/ztest_files/dummy_file.py b/data/ztest_files/dummy_file.py
deleted file mode 100644
index e0c7faa27..000000000
--- a/data/ztest_files/dummy_file.py
+++ /dev/null
@@ -1,4 +0,0 @@
-"""
-I am a dummy file used in tests/test_git_tag.py
-to produce a file which is not commited
-"""
diff --git a/data/ztest_files/test_parameter_samples.csv b/data/ztest_files/test_parameter_samples.csv
deleted file mode 100644
index e3ebdbf4a..000000000
--- a/data/ztest_files/test_parameter_samples.csv
+++ /dev/null
@@ -1,2 +0,0 @@
-,method,model,params
-0,diva,diva,"{'gamma_y': 10e5, 'gamma_d': 1e5}"
diff --git a/docs/doc_tasks.md b/docs/doc_tasks.md
index 3d3f0d73d..1d37bc385 100644
--- a/docs/doc_tasks.md
+++ b/docs/doc_tasks.md
@@ -17,7 +17,7 @@ here in the example, 3 domains are defined to be named "domain1", "domain2", "do
 ## Possibility 2: TaskPathList
 The user need to provide a python file indicating the root directories where images (data) from  each domain are located, and for each domain, the user shall provide a plain text file indicating the file names.
 
-An example python file can be found in the [examples directory of the repository](https://github.com/marrlab/DomainLab/blob/master/examples/tasks/demo_task_path_list_small.py) with the corresponding data be found at [the data directory of the repository](https://github.com/marrlab/DomainLab/tree/master/data), where the text file indicating which file correspond to which class label (starting from 1) can be found at [example text file](https://github.com/marrlab/DomainLab/blob/master/data/pacs_split/art_painting_10.txt).
+An example python file can be found in the [examples directory of the repository](https://github.com/marrlab/DomainLab/blob/master/examples/tasks/demo_task_path_list_small.py) with the corresponding data be found at [the data directory of the repository](https://github.com/marrlab/DomainLab/tree/master/domainlab/zdata), where the text file indicating which file correspond to which class label (starting from 1) can be found at [example text file](https://github.com/marrlab/DomainLab/blob/master/domainlab/zdata/pacs_split/art_painting_10.txt).
 The user should specify the location of the python file via command line arguments `--tpath`
 
 ```shell
diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index b6320328b..dfb92b3ca 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -1,17 +1,119 @@
-### Basic usage
-DomainLab comes with some minimal toy-dataset to test its basis functionality, see [A minimal subsample of the VLCS dataset](../data/vlcs_mini) and [an example configuration file for vlcs_mini](../examples/tasks/task_vlcs.py)
+# DomainLab Usage Guide
 
-Suppose you have cloned the repository and have the dependencies ready, change directory to this repository:
+Given the repository and the dependencies are set up, here is how can use DomainLab: 
 
-To train a domain invariant model on the vlcs_mini task
+
+## Essential Commands
+
+To run DomainLab, the minimum necessary parameters are:
+
+1. **Task Specification (```--tpath``` or ```--task```):** This is to specify a task. You can eiter give a path to as Python file which specifies the task, or use a predfined set. You can find more about specifying tasks [here](./doc_tasks.md). 
+2. **Test Domain (```--te_d```):** Specifies the domain(s) used for testing. Can be a single domain or multiple domains.
+3. **Model Choice (```--model```):** Chooses the algorithm or model for the training (e.g., erm, diva). This also includes hyperparameters for the model, e.g., ```--gamma_d``` and ```--gamma_y``` for diva.
+4. **Neural Network (```--nname``` or ```--npath```):** Specifies which neural network is used for feature extraction, either through a path or predefined options. 
+
+### Example Command
+```python3 main_out.py --te_d 0 1 2  --task=mnistcolor10 --model=diva --nname=conv_bn_pool_2  --gamma_y=7e5 --gamma_d=1e5```
+
+
+## Optional Commands
+
+### Advanced Configuration
+
+- **Learning Rate (`--lr`):** Set the training learning rate.
+- **Regularization (`--gamma_reg`):** Sets the weight of the regularization loss. This parameter can be configured either as a single value applied to individual classes, or using a dictionary to specify different weights for different models and trainers.
+
+  - **Command Line Usage:**
+    - For a single value: `python script.py --gamma_reg=0.1`
+    - For multiple values: `python script.py --gamma_reg='default=0.1,dann=0.05,diva=0.2'`
+
+  - **YAML Configuration:**
+    - For a single value:
+      ```yaml
+      gamma_reg: 0.1
+      ```
+    - For different values:
+      ```yaml
+      gamma_reg:
+        default: 0.1 # every other instance that is not listed below will get this value assigned
+        dann: 0.05
+        diva: 0.2
+      ```- **Early Stopping (`--es`):** Steps for early stopping.
+- **Random Seed (`--seed`):** Seed for reproducibility.
+- **CUDA Options (`--nocu`, `--device`):** Configure CUDA usage and device settings.
+- **Generated Images (`--gen`):** Option to save generated images.
+- **Model Preservation (`--keep_model`):** Choose not to delete the model at the end of training.
+- **Epochs (`--epos`, `--epos_min`):** Configure maximum and minimum numbers of epochs.
+- **Test Interval (`--epo_te`):** Set intervals for testing performance.
+- **Hyperparameter Warm-Up (`-w` or `--warmup`):** Epochs for hyperparameter warm-up.
+- **Debugging (`--debug`):** Enable debug mode for verbose output.
+- **Memory Debugging (`--dmem`):** Memory usage debugging.
+- **Output Suppression (`--no_dump`):** Suppress saving the confusion matrix.
+- **Trainer Selection (`--trainer`):** Specify which trainer to use.
+- **Output Directory (`--out`):** Directory to store outputs.
+- **Data Path (`--dpath`):** Path for storing the downloaded dataset.
+- **Additional Neural Network Options:**
+    - Custom Argument Values (`--npath_argna2val`, `--nname_argna2val`)
+    - Domain Feature Extraction Network (`--npath_dom`, `--nname_dom`)
+    - Custom Algorithm Path (`--apath`)
+- **Experiment and Aggregation Tags (`--exptag`, `--aggtag`):** Tags for experiment tracking and result aggregation.
+- **Benchmarking and Plotting:**
+    - Partial Benchmark Aggregation (`--agg_partial_bm`)
+    - Plot Generation (`--gen_plots`, `--outp_dir`, `--param_idx`)
+
+### Task-Specific Arguments
+
+- **Batch Size (`--bs`):** Loader batch size for mixed domains.
+- **Training-Validation Split (`--split`):** Proportion of training, a value between 0 and 1.
+- **Training Domain (`--tr_d`):** Specify training domain names.
+- **Sanity Check (`--san_check`):** Save images from the dataset as a sanity check.
+- **Sanity Check Image Count (`--san_num`):** Number of images for the sanity check.
+- **Logging Level (`--loglevel`):** Set the log level of the logger.
+- **Shuffling (`--shuffling_off`):** Disable shuffling of the training dataloader for the dataset.
+
+### Model-Specific Hyperparameters
+
+#### VAE Model Parameters
+
+- **Latent Space Dimensions (`--zd_dim`, `--zx_dim`, `--zy_dim`):** Set the size of latent spaces for domain, unobserved, and class features.
+- **Topic Dimension (`--topic_dim`):** Number of topics for HDUVA.
+- **Networks for HDUVA Model:**
+    - Image to Topic Distribution (`--nname_encoder_x2topic_h`, `--npath_encoder_x2topic_h`)
+    - Image and Topic to ZD (`--nname_encoder_sandwich_x2h4zd`, `--npath_encoder_sandwich_x2h4zd`)
+- **Hyperparameters for DIVA and HDUVA (`--gamma_y`, `--gamma_d`, `--beta_t`, `--beta_d`, `--beta_x`, `--beta_y`):** Multipliers for various classifiers and loss components.
+
+#### MatchDG Parameters
+
+- **Cosine Similarity Factor (`--tau`):** Magnify cosine similarity.
+- **Match Tensor Update Frequency (`--epos_per_match_update`):** Epochs before updating the match tensor.
+- **Epochs for CTR (`--epochs_ctr`):** Total epochs for CTR.
+
+#### Jigen Parameters
+
+- **Permutation Settings (`--nperm`, `--pperm`, `--jigen_ppath`):** Configure image tile permutations.
+- **Grid Length (`--grid_len`):** Length of image in tile units.
+
+#### DIAL Parameters
+
+- **Adversarial Image Generation (`--dial_steps_perturb`, `--dial_noise_scale`, `--dial_lr`, `--dial_epsilon`):** Configure parameters for generating adversarial images.
+
+
+For a comprehensive understanding of all available commands, use:
+```shell
+python main_out.py --help
+```
+
+## Example
+DomainLab comes with some minimal toy-dataset to test its basis functionality, see [a minimal subsample of the VLCS dataset](./zdata/vlcs_mini) and [an example configuration file for vlcs_mini](../examples/tasks/task_vlcs.py).
+
+To train a domain invariant model on the vlcs_mini task:
 
 ```shell
 python main_out.py --te_d=caltech --tpath=examples/tasks/task_vlcs.py --config=examples/yaml/demo_config_single_run_diva.yaml
 ```
 where `--tpath` specifies the path of a user specified python file which defines the domain generalization task [see here](../examples/tasks/task_vlcs.py), `--te_d` specifies the test domain name (or index starting from 0), `--config` specifies the configurations of the domain generalization algorithms, [see here](../examples/yaml/demo_config_single_run_diva.yaml)
 
-#### Further usage
-Alternatively, in a verbose mode without using the algorithm configuration file:
+In more detail, in a verbose mode without using the algorithm configuration file:
 
 ```shell
 python main_out.py --te_d=caltech --tpath=examples/tasks/task_vlcs.py --debug --bs=2 --model=diva --gamma_y=7e5 --gamma_d=1e5 --nname=alexnet --nname_dom=conv_bn_pool_2
@@ -19,22 +121,11 @@ python main_out.py --te_d=caltech --tpath=examples/tasks/task_vlcs.py --debug --
 
 where `--model` specifies which algorithm to use, `--bs` specifies the batch size, `--debug` restrain only running for 2 epochs and save results with prefix 'debug'. For DIVA, the hyper-parameters include `--gamma_y=7e5` which is the relative weight of ERM loss compared to ELBO loss, and `--gamma_d=1e5`, which is the relative weight of domain classification loss compared to ELBO loss.
 `--nname` is to specify which neural network to use for feature extraction for classification, `--nname_dom` is to specify which neural network to use for feature extraction of domains.
-For usage of other arguments, check with
-
-```shell
-python main_out.py --help
-```
-
-See also [Examples](./doc_examples.md).
-
-### Custom Neural network
-
-where the user could plugin different neural network architectures for the same algorithm. See
-[Specify Custom Neural Networks for an algorithm](./doc_custom_nn.md)
 
-### Output structure (results storage) and Performance Measure
-[Output structure and Performance Measure](./doc_output.md)
+See [more examples](./doc_examples.md).
 
+## Further Resources
 
-## Software Design Pattern, Extend or Contribution
-[Extend or Contibute](./doc_extend_contribute.md)
+- **Custom Neural Networks:** [Guide on specifying custom neural networks](./doc_custom_nn.md)
+- **Output and Performance:** [Understanding the output structure and performance measures](./doc_output.md)
+- **Extending DomainLab:** [Guide for extending or contributing to DomainLab](./doc_extend_contribute.md)
diff --git a/domainlab/algos/builder_api_model.py b/domainlab/algos/builder_api_model.py
index 07c087e3b..9bfb66fc2 100644
--- a/domainlab/algos/builder_api_model.py
+++ b/domainlab/algos/builder_api_model.py
@@ -20,7 +20,7 @@ def init_business(self, exp):
         """
         args = exp.args
         device = get_device(args)
-        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
         observer = ObVisitor(model_sel)
         trainer = TrainerChainNodeGetter(args.trainer)(default="hyperscheduler")
         return trainer, None, observer, device
diff --git a/domainlab/algos/builder_custom.py b/domainlab/algos/builder_custom.py
index 9c50110b7..166f34018 100644
--- a/domainlab/algos/builder_custom.py
+++ b/domainlab/algos/builder_custom.py
@@ -104,7 +104,8 @@ def init_business(self, exp):
             task = exp.task
             args = exp.args
             device = get_device(args)
-            model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+            model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es),
+                                          val_threshold=args.val_threshold)
             observer = ObVisitor(model_sel)
             model = class_name_model(net_classifier=None, list_str_y=task.list_str_y)
             model = self.init_next_model(model, exp)
diff --git a/domainlab/algos/builder_dann.py b/domainlab/algos/builder_dann.py
index d026a5bb1..73b373c15 100644
--- a/domainlab/algos/builder_dann.py
+++ b/domainlab/algos/builder_dann.py
@@ -13,6 +13,7 @@
 from domainlab.compos.zoo_nn import FeatExtractNNBuilderChainNodeGetter
 from domainlab.models.model_dann import mk_dann
 from domainlab.utils.utils_cuda import get_device
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class NodeAlgoBuilderDANN(NodeAlgoBuilder):
@@ -29,7 +30,7 @@ def init_business(self, exp):
         args = exp.args
         task.get_list_domains_tr_te(args.tr_d, args.te_d)
         device = get_device(args)
-        msel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+        msel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
         observer = ObVisitor(msel)
         observer = ObVisitorCleanUp(observer)
 
@@ -55,7 +56,7 @@ def init_business(self, exp):
         model = mk_dann(list_str_y=task.list_str_y,
                         net_classifier=net_classifier)(
             list_d_tr=task.list_domain_tr,
-            alpha=args.gamma_reg,
+            alpha=get_gamma_reg(args, 'dann'),
             net_encoder=net_encoder,
             net_discriminator=net_discriminator,
             builder=self)
diff --git a/domainlab/algos/builder_diva.py b/domainlab/algos/builder_diva.py
index 34cc3605b..89341dff1 100644
--- a/domainlab/algos/builder_diva.py
+++ b/domainlab/algos/builder_diva.py
@@ -52,7 +52,7 @@ def init_business(self, exp):
         )
         device = get_device(args)
         model_sel = MSelSetpointDelay(
-            MSelOracleVisitor(MSelValPerfTopK(max_es=args.es))
+            MSelOracleVisitor(MSelValPerfTopK(max_es=args.es), val_threshold=args.val_threshold)
         )
         if not args.gen:
             observer = ObVisitor(model_sel)
diff --git a/domainlab/algos/builder_erm.py b/domainlab/algos/builder_erm.py
index 4e76670c0..1221cb209 100644
--- a/domainlab/algos/builder_erm.py
+++ b/domainlab/algos/builder_erm.py
@@ -24,7 +24,7 @@ def init_business(self, exp):
         task = exp.task
         args = exp.args
         device = get_device(args)
-        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
         observer = ObVisitor(model_sel)
 
         builder = FeatExtractNNBuilderChainNodeGetter(
diff --git a/domainlab/algos/builder_hduva.py b/domainlab/algos/builder_hduva.py
index 80e4526cb..1a752e47f 100644
--- a/domainlab/algos/builder_hduva.py
+++ b/domainlab/algos/builder_hduva.py
@@ -43,7 +43,7 @@ def init_business(self, exp):
             beta_d=args.beta_d,
         )
         model = self.init_next_model(model, exp)
-        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es))
+        model_sel = MSelOracleVisitor(MSelValPerf(max_es=args.es), val_threshold=args.val_threshold)
         observer = ObVisitorCleanUp(ObVisitor(model_sel))
         trainer = TrainerChainNodeGetter(args.trainer)(default="hyperscheduler")
         trainer.init_business(model, task, observer, device, args)
diff --git a/domainlab/algos/builder_jigen1.py b/domainlab/algos/builder_jigen1.py
index 712d959d4..fb1e78214 100644
--- a/domainlab/algos/builder_jigen1.py
+++ b/domainlab/algos/builder_jigen1.py
@@ -17,6 +17,7 @@
 from domainlab.dsets.utils_wrapdset_patches import WrapDsetPatches
 from domainlab.models.model_jigen import mk_jigen
 from domainlab.utils.utils_cuda import get_device
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class NodeAlgoBuilderJiGen(NodeAlgoBuilder):
@@ -31,7 +32,7 @@ def init_business(self, exp):
         task = exp.task
         args = exp.args
         device = get_device(args)
-        msel = MSelSetpointDelay(MSelOracleVisitor(MSelValPerfTopK(max_es=args.es)))
+        msel = MSelSetpointDelay(MSelOracleVisitor(MSelValPerfTopK(max_es=args.es)), val_threshold=args.val_threshold)
         observer = ObVisitor(msel)
         observer = ObVisitorCleanUp(observer)
 
@@ -58,7 +59,7 @@ def init_business(self, exp):
         model = mk_jigen(
             list_str_y=task.list_str_y,
             net_classifier=net_classifier)(
-            coeff_reg=args.gamma_reg,
+            coeff_reg=get_gamma_reg(args, 'jigen'),
             net_encoder=net_encoder,
             net_classifier_permutation=net_classifier_perm,
             n_perm=args.nperm,
diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index 1cbfffeaa..1a56bf5cb 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -10,14 +10,16 @@ class AMSel(metaclass=abc.ABCMeta):
     Abstract Model Selection
     """
 
-    def __init__(self):
+    def __init__(self, val_threshold = None):
         """
         trainer and tr_observer
         """
         self.trainer = None
-        self._tr_obs = None
+        self._observer = None
         self.msel = None
         self._max_es = None
+        self._model_selection_epoch = None
+        self._val_threshold = val_threshold
 
     def reset(self):
         """
@@ -27,11 +29,11 @@ def reset(self):
             self.msel.reset()
 
     @property
-    def tr_obs(self):
+    def observer4msel(self):
         """
         the observer from trainer
         """
-        return self._tr_obs
+        return self._observer
 
     @property
     def max_es(self):
@@ -44,27 +46,37 @@ def max_es(self):
             return self.msel.max_es
         return self._max_es
 
-    def accept(self, trainer, tr_obs):
+    def accept(self, trainer, observer4msel):
         """
         Visitor pattern to trainer
         accept trainer and tr_observer
         """
         self.trainer = trainer
-        self._tr_obs = tr_obs
+        self._observer = observer4msel
         if self.msel is not None:
-            self.msel.accept(trainer, tr_obs)
+            self.msel.accept(trainer, observer4msel)
+
+    def update(self, epoch, clear_counter=False):
+        """
+        level above the observer + visitor pattern to get information about the epoch
+        """
+        update = self.base_update(clear_counter)
+        if update:
+            self._model_selection_epoch = epoch
+
+        return update
 
     @abc.abstractmethod
-    def update(self, clear_counter=False):
+    def base_update(self, clear_counter=False):
         """
         observer + visitor pattern to trainer
         if the best model should be updated
         return boolean
         """
 
-    def if_stop(self):
+    def if_stop(self, acc_val):
         """
-        check if trainer should stop
+        check if trainer should stop and additionally tests for validation threshold
         return boolean
         """
         # NOTE: since if_stop is not abstract, one has to
@@ -72,7 +84,17 @@ def if_stop(self):
         # only if the child class has a decorator which will
         # dispatched.
         if self.msel is not None:
-            return self.msel.if_stop()
+            if self._val_threshold is not None and acc_val < self._val_threshold:
+                return False
+        return self.early_stop()
+
+    def early_stop(self):
+        """
+        check if trainer should stop
+        return boolean
+        """
+        if self.msel is not None:
+            return self.msel.early_stop()
         raise NotImplementedError
 
     @property
@@ -107,3 +129,18 @@ def oracle_last_setpoint_sel_te_acc(self):
         if self.msel is not None:
             return self.msel.oracle_last_setpoint_sel_te_acc
         return -1
+
+    def model_selection_epoch(self):
+        """
+        the epoch when the model was selected
+        """
+        if self._model_selection_epoch is not None:
+            return self._model_selection_epoch
+        return -1
+
+    @property
+    def val_threshold(self):
+        """
+        the treshold below which we don't stop early
+        """
+        return self._val_threshold
diff --git a/domainlab/algos/msels/c_msel_oracle.py b/domainlab/algos/msels/c_msel_oracle.py
index e232b1e78..d61047c75 100644
--- a/domainlab/algos/msels/c_msel_oracle.py
+++ b/domainlab/algos/msels/c_msel_oracle.py
@@ -11,11 +11,11 @@ class MSelOracleVisitor(AMSel):
     how the final model is selected
     """
 
-    def __init__(self, msel=None):
+    def __init__(self, msel=None, val_threshold = None):
         """
         Decorator pattern
         """
-        super().__init__()
+        super().__init__(val_threshold)
         self.best_oracle_acc = 0
         self.msel = msel
 
@@ -30,15 +30,15 @@ def oracle_last_setpoint_sel_te_acc(self):
             return self.msel.oracle_last_setpoint_sel_te_acc
         return -1
 
-    def update(self, clear_counter=False):
+    def base_update(self, clear_counter=False):
         """
         if the best model should be updated
         """
         self.trainer.model.save("epoch")
         flag = False
-        if self.tr_obs.metric_val is None:
-            return super().update(clear_counter)
-        metric = self.tr_obs.metric_te[self.tr_obs.str_metric4msel]
+        if self.observer4msel.metric_val is None:
+            return super().base_update(clear_counter)
+        metric = self.observer4msel.metric_te[self.observer4msel.str_metric4msel]
         if metric > self.best_oracle_acc:
             self.best_oracle_acc = metric
             if self.msel is not None:
@@ -49,20 +49,20 @@ def update(self, clear_counter=False):
             logger.info("new oracle model saved")
             flag = True
         if self.msel is not None:
-            return self.msel.update(clear_counter)
+            return self.msel.base_update(clear_counter)
         return flag
 
-    def if_stop(self):
+    def early_stop(self):
         """
         if should early stop
         oracle model selection does not intervene how models get selected
         by the innermost model selection
         """
         if self.msel is not None:
-            return self.msel.if_stop()
+            return self.msel.early_stop()
         return False
 
-    def accept(self, trainer, tr_obs):
+    def accept(self, trainer, observer4msel):
         if self.msel is not None:
-            self.msel.accept(trainer, tr_obs)
-        super().accept(trainer, tr_obs)
+            self.msel.accept(trainer, observer4msel)
+        super().accept(trainer, observer4msel)
diff --git a/domainlab/algos/msels/c_msel_tr_loss.py b/domainlab/algos/msels/c_msel_tr_loss.py
index 58ca03e21..609550a9a 100644
--- a/domainlab/algos/msels/c_msel_tr_loss.py
+++ b/domainlab/algos/msels/c_msel_tr_loss.py
@@ -13,8 +13,8 @@ class MSelTrLoss(AMSel):
     2. Visitor pattern to trainer
     """
 
-    def __init__(self, max_es):
-        super().__init__()
+    def __init__(self, max_es, val_threshold = None):
+        super().__init__(val_threshold)
         # NOTE: super() must come first otherwise it will overwrite existing
         # values!
         self.reset()
@@ -28,7 +28,7 @@ def reset(self):
     def max_es(self):
         return self._max_es
 
-    def update(self, clear_counter=False):
+    def base_update(self, clear_counter=False):
         """
         if the best model should be updated
         """
@@ -50,7 +50,7 @@ def update(self, clear_counter=False):
                 self.es_c = 0
         return flag
 
-    def if_stop(self):
+    def early_stop(self):
         """
         if should early stop
         """
diff --git a/domainlab/algos/msels/c_msel_val.py b/domainlab/algos/msels/c_msel_val.py
index c1f2f5561..38c91ad58 100644
--- a/domainlab/algos/msels/c_msel_val.py
+++ b/domainlab/algos/msels/c_msel_val.py
@@ -11,8 +11,8 @@ class MSelValPerf(MSelTrLoss):
     2. Visitor pattern to trainer
     """
 
-    def __init__(self, max_es):
-        super().__init__(max_es)  # construct self.tr_obs (observer)
+    def __init__(self, max_es, val_threshold = None):
+        super().__init__(max_es, val_threshold)  # construct self.observer4msel (observer)
         self.reset()
 
     def reset(self):
@@ -39,16 +39,16 @@ def best_te_metric(self):
         """
         return self._best_te_metric
 
-    def update(self, clear_counter=False):
+    def base_update(self, clear_counter=False):
         """
         if the best model should be updated
         """
         flag = True
-        if self.tr_obs.metric_val is None:
-            return super().update(clear_counter)
-        metric = self.tr_obs.metric_val[self.tr_obs.str_metric4msel]
-        if self.tr_obs.metric_te is not None:
-            metric_te_current = self.tr_obs.metric_te[self.tr_obs.str_metric4msel]
+        if self.observer4msel.metric_val is None:
+            return super().base_update(clear_counter)
+        metric = self.observer4msel.metric_val[self.observer4msel.str_metric4msel]
+        if self.observer4msel.metric_te is not None:
+            metric_te_current = self.observer4msel.metric_te[self.observer4msel.str_metric4msel]
             self._best_te_metric = max(self._best_te_metric, metric_te_current)
 
         if metric > self._best_val_acc:  # update hat{model}
@@ -56,8 +56,8 @@ def update(self, clear_counter=False):
             # the bigger the better
             self._best_val_acc = metric
             self.es_c = 0  # restore counter
-            if self.tr_obs.metric_te is not None:
-                metric_te_current = self.tr_obs.metric_te[self.tr_obs.str_metric4msel]
+            if self.observer4msel.metric_te is not None:
+                metric_te_current = self.observer4msel.metric_te[self.observer4msel.str_metric4msel]
                 self._sel_model_te_acc = metric_te_current
 
         else:
@@ -65,7 +65,7 @@ def update(self, clear_counter=False):
             logger = Logger.get_logger()
             logger.info(f"early stop counter: {self.es_c}")
             logger.info(
-                f"val acc:{self.tr_obs.metric_val['acc']}, "
+                f"val acc:{self.observer4msel.metric_val['acc']}, "
                 + f"best validation acc: {self.best_val_acc}, "
                 + f"corresponding to test acc: \
                         {self.sel_model_te_acc} / {self.best_te_metric}"
diff --git a/domainlab/algos/observers/b_obvisitor.py b/domainlab/algos/observers/b_obvisitor.py
index 6dce73c28..22db875f2 100644
--- a/domainlab/algos/observers/b_obvisitor.py
+++ b/domainlab/algos/observers/b_obvisitor.py
@@ -61,12 +61,11 @@ def update(self, epoch, flag_info=False):
                     self.loader_te, self.device
                 )
                 self.metric_te = metric_te
-        if self.model_sel.update(flag_info):
+        if self.model_sel.update(epoch, flag_info):
             logger.info("better model found")
             self.host_trainer.model.save()
             logger.info("persisted")
-        flag_stop = self.model_sel.if_stop()
-
+        flag_stop = self.model_sel.if_stop(self.metric_val["acc"])
         flag_enough = epoch >= self.host_trainer.aconf.epos_min
 
         self.flag_setpoint_changed_once |= flag_info
@@ -116,6 +115,7 @@ def after_all(self):
             metric_te.update({"acc_oracle": -1})
         if hasattr(self, "model_sel"):
             metric_te.update({"acc_val": self.model_sel.best_val_acc})
+            metric_te.update({"model_selection_epoch": self.model_sel.model_selection_epoch})
         else:
             metric_te.update({"acc_val": -1})
 
diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 34a603dbe..bd8a41efb 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -272,3 +272,11 @@ def dset_decoration_args_algo(self, args, ddset):
         if self._decoratee is not None:
             return self._decoratee.dset_decoration_args_algo(args, ddset)
         return ddset
+
+    def print_parameters(self):
+        """
+        Function to print all parameters of the object. 
+        Can be used to print the parameters of any child class
+        """
+        params = vars(self)
+        print(f"Parameters of {type(self).__name__}: {params}")
diff --git a/domainlab/algos/trainers/train_dial.py b/domainlab/algos/trainers/train_dial.py
index 76f2dff02..dbcb50eae 100644
--- a/domainlab/algos/trainers/train_dial.py
+++ b/domainlab/algos/trainers/train_dial.py
@@ -5,6 +5,7 @@
 from torch.autograd import Variable
 
 from domainlab.algos.trainers.train_basic import TrainerBasic
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class TrainerDIAL(TrainerBasic):
@@ -49,7 +50,7 @@ def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         tensor_x_adv = self.gen_adversarial(self.device, tensor_x, tensor_y)
         tensor_x_batch_adv_no_grad = Variable(tensor_x_adv, requires_grad=False)
         loss_dial = self.model.cal_task_loss(tensor_x_batch_adv_no_grad, tensor_y)
-        return [loss_dial], [self.aconf.gamma_reg]
+        return [loss_dial], [get_gamma_reg(self.aconf, self.name)]
 
     def hyper_init(self, functor_scheduler, trainer):
         """
diff --git a/domainlab/algos/trainers/train_fishr.py b/domainlab/algos/trainers/train_fishr.py
index 1a11e3780..3580a0721 100644
--- a/domainlab/algos/trainers/train_fishr.py
+++ b/domainlab/algos/trainers/train_fishr.py
@@ -13,6 +13,7 @@
     backpack = None
 
 from domainlab.algos.trainers.train_basic import TrainerBasic
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class TrainerFishr(TrainerBasic):
@@ -39,7 +40,7 @@ def tr_epoch(self, epoch):
             dict_layerwise_var_var_grads_sum = \
                 {key: val.sum() for key, val in dict_layerwise_var_var_grads.items()}
             loss_fishr = sum(dict_layerwise_var_var_grads_sum.values())
-            loss = sum(list_loss_erm) + self.aconf.gamma_reg * loss_fishr
+            loss = sum(list_loss_erm) + get_gamma_reg(self.aconf, self.name) * loss_fishr
             loss.backward()
             self.optimizer.step()
             self.epo_loss_tr += loss.detach().item()
diff --git a/domainlab/algos/trainers/train_matchdg.py b/domainlab/algos/trainers/train_matchdg.py
index cfe8e5a66..e127baa12 100644
--- a/domainlab/algos/trainers/train_matchdg.py
+++ b/domainlab/algos/trainers/train_matchdg.py
@@ -13,6 +13,7 @@
 )
 from domainlab.tasks.utils_task_dset import DsetIndDecorator4XYD
 from domainlab.utils.logger import Logger
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class TrainerMatchDG(AbstractTrainer):
@@ -36,7 +37,7 @@ def init_business(
         self.base_domain_size = get_base_domain_size4match_dg(self.task)
         self.epo_loss_tr = 0
         self.flag_erm = flag_erm
-        self.lambda_ctr = self.aconf.gamma_reg
+        self.lambda_ctr = get_gamma_reg(aconf, self.name)
         self.mk_match_tensor(epoch=0)
         self.flag_match_tensor_sweep_over = False
         self.tuple_tensor_ref_domain2each_y = None
diff --git a/domainlab/algos/trainers/train_mldg.py b/domainlab/algos/trainers/train_mldg.py
index 90318286c..e91310adf 100644
--- a/domainlab/algos/trainers/train_mldg.py
+++ b/domainlab/algos/trainers/train_mldg.py
@@ -10,6 +10,7 @@
 from domainlab.algos.trainers.train_basic import TrainerBasic
 from domainlab.tasks.utils_task import mk_loader
 from domainlab.tasks.utils_task_dset import DsetZip
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class TrainerMLDG(AbstractTrainer):
@@ -108,7 +109,7 @@ def tr_epoch(self, epoch):
             loss = (
                 loss_source_task.sum()
                 + source_reg_tr.sum()
-                + self.aconf.gamma_reg * loss_look_forward.sum()
+                + get_gamma_reg(self.aconf, self.name) * loss_look_forward.sum()
             )
             #
             loss.backward()
diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index 61a2ea97a..0887ba4da 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -13,6 +13,21 @@
 from domainlab.models.args_vae import add_args2parser_vae
 from domainlab.utils.logger import Logger
 
+class StoreDictKeyPair(argparse.Action):
+    """Class used for arg parsing where values are provided in a key value format"""
+
+    def __call__(self, parser, namespace, values, option_string=None):
+        try:
+            if "=" in values:
+                my_dict = {}
+                for kv in values.split(","):
+                    k, v = kv.split("=")
+                    my_dict[k.strip()] = float(v.strip())  # Assuming values are floats
+                setattr(namespace, self.dest, my_dict)
+            else:
+                setattr(namespace, self.dest, float(values))  # Single float value
+        except ValueError:
+            raise argparse.ArgumentError(self, f"Invalid value for {self.dest}: {values}")
 
 def mk_parser_main():
     """
@@ -32,7 +47,10 @@ def mk_parser_main():
     parser.add_argument("--lr", type=float, default=1e-4, help="learning rate")
 
     parser.add_argument(
-        "--gamma_reg", type=float, default=0.1, help="weight of regularization loss"
+        "--gamma_reg",
+        default=0.1,
+        help="weight of regularization loss, can specify per model as 'dann=1.0,diva=2.0'",
+        action=StoreDictKeyPair
     )
 
     parser.add_argument("--es", type=int, default=1, help="early stop steps")
@@ -251,6 +269,13 @@ def mk_parser_main():
 
     parser.add_argument("--task", metavar="ta", type=str, help="task name")
 
+    parser.add_argument(
+        "--val_threshold",
+        type=float,
+        default=None,
+        help="Accuracy threshold before early stopping can be applied"
+    )
+
     arg_group_task = parser.add_argument_group("task args")
 
     arg_group_task.add_argument(
@@ -301,7 +326,10 @@ def mk_parser_main():
     arg_group_task.add_argument(
         "--loglevel", type=str, default="DEBUG", help="sets the loglevel of the logger"
     )
-
+    arg_group_task.add_argument(
+        "--shuffling_off", action="store_true", default=False,
+        help="disable shuffling of the training dataloader for the dataset"
+    )
     # args for variational auto encoder
     arg_group_vae = parser.add_argument_group("vae")
     arg_group_vae = add_args2parser_vae(arg_group_vae)
diff --git a/domainlab/exp/exp_main.py b/domainlab/exp/exp_main.py
index 51397131b..12ecea5f5 100755
--- a/domainlab/exp/exp_main.py
+++ b/domainlab/exp/exp_main.py
@@ -10,7 +10,6 @@
 from domainlab.tasks.zoo_tasks import TaskChainNodeGetter
 from domainlab.utils.logger import Logger
 from domainlab.utils.sanity_check import SanityCheck
-
 os.environ["CUDA_LAUNCH_BLOCKING"] = "1"  # debug
 
 
@@ -51,12 +50,14 @@ def __init__(self, args, task=None, model=None, observer=None, visitor=AggWriter
             self.model = model
         self.epochs = self.args.epos
         self.epoch_counter = 1
+        self.val_threshold = args.val_threshold
         if observer is None:
             observer = observer_default
         if not self.trainer.flag_initialized:
             self.trainer.init_business(self.model, self.task, observer, device, args)
         self.visitor = visitor(self)  # visitor depends on task initialization first
         # visitor must be initialized last after trainer is initialized
+        self.experiment_duration = None
         self.model.set_saver(self.visitor)
 
     def execute(self, num_epochs=None):
@@ -96,6 +97,7 @@ def execute(self, num_epochs=None):
             f"Experiment finished at epoch: {self.epoch_counter} "
             f"with time: {t_c - t_0} at {t_c}"
         )
+        self.experiment_duration = t_c - t_0
         self.trainer.post_tr()
 
     def clean_up(self):
diff --git a/domainlab/exp/exp_utils.py b/domainlab/exp/exp_utils.py
index 2af681731..22a609b2c 100644
--- a/domainlab/exp/exp_utils.py
+++ b/domainlab/exp/exp_utils.py
@@ -179,6 +179,11 @@ def _gen_line(self, dict_metric):
         confmat_filename = dict_cols.get("mname", None)  # return None if not found
         # @FIXME: strong dependency on host attribute name
         dict_cols.update({epos_name: self.host.epoch_counter})
+        if self.host.experiment_duration is not None:
+            dict_cols.update({"experiment_duration": self.host.experiment_duration})
+        else:
+            print("Does not have attribute")
+            print(self.host)
         if not self.has_first_line:
             self.first_line(dict_cols)
         list_str = [str(dict_cols[key]) for key in self.list_cols]
diff --git a/domainlab/models/a_model.py b/domainlab/models/a_model.py
index ca639daa2..3767aa58d 100644
--- a/domainlab/models/a_model.py
+++ b/domainlab/models/a_model.py
@@ -187,3 +187,35 @@ def dset_decoration_args_algo(self, args, ddset):
         if self._decoratee is not None:
             return self._decoratee.dset_decoration_args_algo(args, ddset)
         return ddset
+
+    @property
+    def p_na_prefix(self):
+        """
+        common prefix for Models
+        """
+        return "Model"
+
+    @property
+    def name(self):
+        """
+        get the name of the algorithm
+        """
+        na_prefix = self.p_na_prefix
+        len_prefix = len(na_prefix)
+        na_class = type(self).__name__
+        if na_class[:len_prefix] != na_prefix:
+            raise RuntimeError(
+                "Model builder node class must start with ",
+                na_prefix,
+                "the current class is named: ",
+                na_class,
+            )
+        return type(self).__name__[len_prefix:].lower()
+
+    def print_parameters(self):
+        """
+        Function to print all parameters of the object. 
+        Can be used to print the parameters of every child class.
+        """
+        params = vars(self)
+        print(f"Parameters of {type(self).__name__}: {params}")
diff --git a/domainlab/models/model_dann.py b/domainlab/models/model_dann.py
index b479c309c..16c1d6f8b 100644
--- a/domainlab/models/model_dann.py
+++ b/domainlab/models/model_dann.py
@@ -89,13 +89,15 @@ def hyper_update(self, epoch, fun_scheduler):
             dict_rst = fun_scheduler(
                 epoch
             )  # the __call__ method of hyperparameter scheduler
-            self.alpha = dict_rst["alpha"]
+            self.alpha = dict_rst[self.name + "_alpha"]
 
         def hyper_init(self, functor_scheduler, trainer=None):
             """hyper_init.
             :param functor_scheduler: name of the scheduler class
             """
-            return functor_scheduler(trainer=trainer, alpha=self.alpha)
+            parameters = {}
+            parameters[self.name + "_alpha"] = self.alpha
+            return functor_scheduler(trainer=trainer, **parameters)
 
         def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others):
             _ = others
diff --git a/domainlab/models/model_diva.py b/domainlab/models/model_diva.py
index c907eb94a..3185cc452 100644
--- a/domainlab/models/model_diva.py
+++ b/domainlab/models/model_diva.py
@@ -100,9 +100,9 @@ def hyper_update(self, epoch, fun_scheduler):
             :param fun_scheduler:
             """
             dict_rst = fun_scheduler(epoch)
-            self.beta_d = dict_rst["beta_d"]
-            self.beta_y = dict_rst["beta_y"]
-            self.beta_x = dict_rst["beta_x"]
+            self.beta_d = dict_rst[self.name + "_beta_d"]
+            self.beta_y = dict_rst[self.name + "_beta_x"]
+            self.beta_x = dict_rst[self.name + "_beta_y"]
 
         def hyper_init(self, functor_scheduler, trainer=None):
             """
@@ -110,11 +110,12 @@ def hyper_init(self, functor_scheduler, trainer=None):
 
             :param functor_scheduler: the class name of the scheduler
             """
+            parameters = {}
+            parameters[self.name + "_beta_d"] = self.beta_d
+            parameters[self.name + "_beta_y"] = self.beta_y
+            parameters[self.name + "_beta_x"] = self.beta_x
             return functor_scheduler(
-                trainer=trainer,
-                beta_d=self.beta_d,
-                beta_y=self.beta_y,
-                beta_x=self.beta_x,
+                trainer=trainer, **parameters
             )
 
         @property
diff --git a/domainlab/models/model_hduva.py b/domainlab/models/model_hduva.py
index 929d179b7..91d1ad03a 100644
--- a/domainlab/models/model_hduva.py
+++ b/domainlab/models/model_hduva.py
@@ -66,11 +66,11 @@ def hyper_update(self, epoch, fun_scheduler):
             dict_rst = fun_scheduler(
                 epoch
             )  # the __call__ function of hyper-para-scheduler object
-            self.beta_d = dict_rst["beta_d"]
-            self.beta_y = dict_rst["beta_y"]
-            self.beta_x = dict_rst["beta_x"]
-            self.beta_t = dict_rst["beta_t"]
-            self.mu_recon = dict_rst["mu_recon"]
+            self.beta_d = dict_rst[self.name + "_beta_d"]
+            self.beta_y = dict_rst[self.name + "_beta_y"]
+            self.beta_x = dict_rst[self.name + "_beta_x"]
+            self.beta_t = dict_rst[self.name + "_beta_t"]
+            self.mu_recon = dict_rst[self.name + "_mu_recon"]
 
         def hyper_init(self, functor_scheduler, trainer=None):
             """hyper_init.
@@ -79,13 +79,14 @@ def hyper_init(self, functor_scheduler, trainer=None):
             # calling the constructor of the hyper-parameter-scheduler class, so that this scheduler
             # class build a dictionary {"beta_d":self.beta_d, "beta_y":self.beta_y}
             # constructor signature is def __init__(self, **kwargs):
+            parameters = {}
+            parameters[self.name + "_beta_d"] = self.beta_d
+            parameters[self.name + "_beta_y"] = self.beta_y
+            parameters[self.name + "_beta_x"] = self.beta_x
+            parameters[self.name + "_beta_t"] = self.beta_t
+            parameters[self.name + "_mu_recon"] = self.mu_recon
             return functor_scheduler(
-                trainer=trainer,
-                mu_recon=self.mu_recon,
-                beta_d=self.beta_d,
-                beta_y=self.beta_y,
-                beta_x=self.beta_x,
-                beta_t=self.beta_t,
+                trainer=trainer, **parameters
             )
 
         @store_args
diff --git a/domainlab/utils/hyperparameter_retrieval.py b/domainlab/utils/hyperparameter_retrieval.py
new file mode 100644
index 000000000..9b3c97e7e
--- /dev/null
+++ b/domainlab/utils/hyperparameter_retrieval.py
@@ -0,0 +1,18 @@
+"""
+retrieval for hyperparameters
+"""
+
+def get_gamma_reg(args, model_name):
+    """
+    Retrieves either a shared gamma regularization, or individual ones for each specified object
+    """
+    gamma_reg = args.gamma_reg
+    if isinstance(gamma_reg, dict):
+        if model_name in gamma_reg:
+            return gamma_reg[model_name]
+        if 'default' in gamma_reg:
+            return gamma_reg['default']
+        raise ValueError("""If a gamma_reg dict is specified,
+                              but no value set for every model and trainer,
+                              a default value must be specified.""")
+    return gamma_reg  # Return the single value if it's not a dictionary
diff --git a/domainlab/zdata/ztest_files/test_parameter_samples.csv b/domainlab/zdata/ztest_files/test_parameter_samples.csv
index 609864f2f..e3ebdbf4a 100644
--- a/domainlab/zdata/ztest_files/test_parameter_samples.csv
+++ b/domainlab/zdata/ztest_files/test_parameter_samples.csv
@@ -1,2 +1,2 @@
-,task,algo,params
+,method,model,params
 0,diva,diva,"{'gamma_y': 10e5, 'gamma_d': 1e5}"
diff --git a/examples/benchmark/benchmark_blood3_resnet.yaml b/examples/benchmark/benchmark_blood3_resnet.yaml
new file mode 100644
index 000000000..a9a1cf0ed
--- /dev/null
+++ b/examples/benchmark/benchmark_blood3_resnet.yaml
@@ -0,0 +1,129 @@
+# test benchmark config.
+
+test_domains:
+  - acevedo
+#- mll
+#- matek
+
+output_dir: zoutput/benchmarks/blood
+# number of hyperparameter samples per task.
+# Thus, the total runs of each task are given
+# by len(domains) * num_param_samples * num_seeds (see below)
+num_param_samples: 8
+sampling_seed: 0
+
+startseed: 0
+endseed: 5  # currently included
+
+
+
+domainlab_args:
+  # Domainlab arguments passed to each task.
+  # task specific arguments take precedence.
+  ## dataset
+  tpath: examples/tasks/task_blood3.py
+  dmem: False
+  lr: 5e-5
+  epos: 500
+  epos_min: 20
+  es: 1
+  bs: 32
+  npath: examples/nets/resnet50domainbed.py
+  san_check: True
+
+Shared params:
+  num_shared_param_samples: 8
+  gamma_y:
+    min: 1e4
+    max: 2e5
+    step: 100
+    distribution: loguniform
+
+  zx_dim:
+    min: 0
+    max: 96
+    step: 32
+    distribution: uniform
+    datatype: int
+
+  zy_dim:
+    min: 32
+    max: 96
+    step: 32
+    distribution: uniform
+    datatype: int
+
+  zd_dim:
+    reference: zy_dim
+
+  gamma_reg:
+    min: 0.01
+    max: 10
+    distribution: loguniform
+
+
+
+diva:  # name
+  model: diva
+  # set nname_dom = nname when changing nname
+  npath_dom: examples/nets/resnet50domainbed.py
+  shared:
+    - gamma_y
+    - zx_dim
+    - zy_dim
+    - zd_dim
+
+  hyperparameters:
+    gamma_d:
+      min: 1e4
+      max: 1e6
+      step: 10_000
+      distribution: loguniform
+
+hduva:  # name
+  model: hduva
+
+  npath_encoder_x2topic_h: examples/nets/resnet50domainbed.py
+  npath_encoder_sandwich_x2h4zd: examples/nets/resnet50domainbed.py
+  shared:
+    - gamma_y
+    - zx_dim
+    - zy_dim
+    - zd_dim
+
+erm:  # name
+  model: erm
+
+mldg:
+  model: erm
+  trainer: mldg
+  shared:
+    - gamma_reg
+
+dann:
+  model: dann
+  shared:
+    - gamma_reg
+
+
+dial: # name
+  model: erm
+  trainer: dial
+  shared:
+    - gamma_reg
+  hyperparameters:
+    dial_steps_perturb:
+      min: 1
+      max: 10
+      step: 1
+      distribution: uniform
+
+    dial_noise_scale:
+      min: 0.00001
+      max: 0.1
+      distribution: loguniform
+
+    dial_epsilon:
+      min: 0.001
+      max: 0.01
+      distribution: loguniform
diff --git a/examples/conf/vlcs_diva_mldg_dial.yaml b/examples/conf/vlcs_diva_mldg_dial.yaml
index 0701766ff..71b376a03 100644
--- a/examples/conf/vlcs_diva_mldg_dial.yaml
+++ b/examples/conf/vlcs_diva_mldg_dial.yaml
@@ -1,10 +1,13 @@
 te_d: caltech                       # domain name of test domain
 tpath: examples/tasks/task_vlcs.py  # python file path to specify the task
 bs: 2                               # batch size
+val_threshold: 0.8
 model: dann_diva                    # combine model DANN with DIVA
 epos: 1                             # number of epochs
 trainer: mldg_dial                  # combine trainer MLDG and DIAL
-gamma_reg: 1.0                      # hyperparameter of DANN
+gamma_reg: 
+  default: 1.0
+  dann: 1.5     
 gamma_y: 700000.0                   # hyperparameter of diva
 gamma_d: 100000.0                   # hyperparameter of diva
 npath: examples/nets/resnet.py      # neural network for class classification
diff --git a/examples/tasks/demo_task_path_list_small.py b/examples/tasks/demo_task_path_list_small.py
index 92425774a..af8e469a4 100644
--- a/examples/tasks/demo_task_path_list_small.py
+++ b/examples/tasks/demo_task_path_list_small.py
@@ -31,31 +31,31 @@ def get_task(na=None):
         # ## the text file below only need to specify the relative path
         # ## training
         dict_d2filepath_list_img_tr={
-            "art_painting": "data/pacs_split/art_painting_10.txt",
-            "cartoon": "data/pacs_split/cartoon_10.txt",
-            "photo": "data/pacs_split/photo_10.txt",
-            "sketch": "data/pacs_split/sketch_10.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_10.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_10.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_10.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_10.txt",
         },
         # ## testing
         dict_d2filepath_list_img_te={
-            "art_painting": "data/pacs_split/art_painting_10.txt",
-            "cartoon": "data/pacs_split/cartoon_10.txt",
-            "photo": "data/pacs_split/photo_10.txt",
-            "sketch": "data/pacs_split/sketch_10.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_10.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_10.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_10.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_10.txt",
         },
         # ## validation
         dict_d2filepath_list_img_val={
-            "art_painting": "data/pacs_split/art_painting_10.txt",
-            "cartoon": "data/pacs_split/cartoon_10.txt",
-            "photo": "data/pacs_split/photo_10.txt",
-            "sketch": "data/pacs_split/sketch_10.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_10.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_10.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_10.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_10.txt",
         },
         # ## specify root folder storing the images of each domain:
         dict_domain2imgroot={
-            "art_painting": "data/pacs_mini_10",
-            "cartoon": "data/pacs_mini_10",
-            "photo": "data/pacs_mini_10",
-            "sketch": "data/pacs_mini_10",
+            "art_painting": "domainlab/zdata/pacs_mini_10",
+            "cartoon": "domainlab/zdata/pacs_mini_10",
+            "photo": "domainlab/zdata/pacs_mini_10",
+            "sketch": "domainlab/zdata/pacs_mini_10",
         },
         # ## specify the pytorch transformation you want to apply to the image
         img_trans_tr=transforms.Compose(
diff --git a/examples/tasks/task_blood3.py b/examples/tasks/task_blood3.py
new file mode 100644
index 000000000..416eb893e
--- /dev/null
+++ b/examples/tasks/task_blood3.py
@@ -0,0 +1,107 @@
+"""
+difference than task_blood2.py:
+
+"mll": "/lustre/groups/labs/marr/qscd01/datasets/240416_MLL23",
+
+"""
+from torchvision import transforms
+
+from domainlab.tasks.task_folder_mk import mk_task_folder
+from domainlab.tasks.utils_task import ImSize
+
+IMG_SIZE = 224
+
+trans = transforms.Compose(
+    [
+        transforms.Resize((IMG_SIZE, IMG_SIZE)),
+        transforms.RandomResizedCrop(IMG_SIZE, scale=(0.7, 1.0)),
+        transforms.RandomHorizontalFlip(),
+        transforms.ColorJitter(0.3, 0.3, 0.3, 0.3),
+        transforms.RandomGrayscale(),
+        transforms.ToTensor(),
+        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
+    ]
+)
+
+trans_te = transforms.Compose(
+    [
+        transforms.Resize((IMG_SIZE, IMG_SIZE)),
+        transforms.ToTensor(),
+        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
+    ]
+)
+
+
+TASK = mk_task_folder(
+    extensions={"acevedo": "jpg", "matek": "tiff", "mll": "tif"},
+    list_str_y=[
+        "basophil",
+        "erythroblast",
+        "metamyelocyte",
+        "myeloblast",
+        "neutrophil_band",
+        "promyelocyte",
+        "eosinophil",
+        "lymphocyte_typical",
+        "monocyte",
+        "myelocyte",
+        "neutrophil_segmented",
+    ],
+    dict_domain_folder_name2class={
+        "acevedo": {
+            "basophil": "basophil",
+            "erythroblast": "erythroblast",
+            "metamyelocyte": "metamyelocyte",
+            "neutrophil_band": "neutrophil_band",
+            "promyelocyte": "promyelocyte",
+            "eosinophil": "eosinophil",
+            "lymphocyte_typical": "lymphocyte_typical",
+            "monocyte": "monocyte",
+            "myelocyte": "myelocyte",
+            "neutrophil_segmented": "neutrophil_segmented",
+        },
+        "matek": {
+            "basophil": "basophil",
+            "erythroblast": "erythroblast",
+            "metamyelocyte": "metamyelocyte",
+            "myeloblast": "myeloblast",
+            "neutrophil_band": "neutrophil_band",
+            "promyelocyte": "promyelocyte",
+            "eosinophil": "eosinophil",
+            "lymphocyte_typical": "lymphocyte_typical",
+            "monocyte": "monocyte",
+            "myelocyte": "myelocyte",
+            "neutrophil_segmented": "neutrophil_segmented",
+        },
+        "mll": {
+            "basophil": "basophil",
+            "erythroblast": "normoblast",
+            "metamyelocyte": "metamyelocyte",
+            "myeloblast": "myeloblast",
+            "neutrophil_band": "neutrophil_band",
+            "promyelocyte": "promyelocyte",
+            "eosinophil": "eosinophil",
+            "lymphocyte_typical": "lymphocyte",
+            "monocyte": "monocyte",
+            "myelocyte": "myelocyte",
+            "neutrophil_segmented": "neutrophil_segmented",
+        },
+    },
+    dict_domain_img_trans={
+        "acevedo": trans,
+        "mll": trans,
+        "matek": trans,
+    },
+    img_trans_te=trans_te,
+    isize=ImSize(3, IMG_SIZE, IMG_SIZE),
+    dict_domain2imgroot={
+        "matek": "/lustre/groups/labs/marr/qscd01/datasets/armingruber/_Domains/Matek_cropped",
+        "mll": "/lustre/groups/labs/marr/qscd01/datasets/240416_MLL23",
+        "acevedo": "/lustre/groups/labs/marr/qscd01/datasets/armingruber/_Domains/Acevedo_cropped",
+    },
+    taskna="blood_mon_eos_bas",
+)
+
+
+def get_task(na=None):
+    return TASK
diff --git a/examples/tasks/task_pacs_aug.py b/examples/tasks/task_pacs_aug.py
index 6fc092dca..e971bea8c 100644
--- a/examples/tasks/task_pacs_aug.py
+++ b/examples/tasks/task_pacs_aug.py
@@ -11,8 +11,9 @@
 from domainlab.tasks.utils_task import ImSize
 
 # change this to absolute directory where you have the raw images from PACS,
-G_PACS_RAW_PATH = "data/pacs/PACS"
-# domainlab repository contain already the file names in data/pacs_split folder of domainlab
+G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
+# domainlab repository contain already the file names in
+# domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
@@ -29,22 +30,22 @@ def get_task(na=None):
             "7": "person",
         },
         dict_d2filepath_list_img_tr={
-            "art_painting": "data/pacs_split/art_painting_train_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_train_kfold.txt",
-            "photo": "data/pacs_split/photo_train_kfold.txt",
-            "sketch": "data/pacs_split/sketch_train_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_train_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_train_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_train_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_train_kfold.txt",
         },
         dict_d2filepath_list_img_te={
-            "art_painting": "data/pacs_split/art_painting_test_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_test_kfold.txt",
-            "photo": "data/pacs_split/photo_test_kfold.txt",
-            "sketch": "data/pacs_split/sketch_test_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_test_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_test_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_test_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_test_kfold.txt",
         },
         dict_d2filepath_list_img_val={
-            "art_painting": "data/pacs_split/art_painting_crossval_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_crossval_kfold.txt",
-            "photo": "data/pacs_split/photo_crossval_kfold.txt",
-            "sketch": "data/pacs_split/sketch_crossval_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_crossval_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_crossval_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_crossval_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_crossval_kfold.txt",
         },
         dict_domain2imgroot={
             "art_painting": G_PACS_RAW_PATH,
diff --git a/examples/tasks/task_pacs_aug_noflip_no_zoom.py b/examples/tasks/task_pacs_aug_noflip_no_zoom.py
index c1f8b45a8..0b855d31e 100644
--- a/examples/tasks/task_pacs_aug_noflip_no_zoom.py
+++ b/examples/tasks/task_pacs_aug_noflip_no_zoom.py
@@ -11,8 +11,9 @@
 from domainlab.tasks.utils_task import ImSize
 
 # change this to absolute directory where you have the raw images from PACS,
-G_PACS_RAW_PATH = "data/pacs/PACS"
-# domainlab repository contain already the file names in data/pacs_split folder of domainlab
+G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
+# domainlab repository contain already the file names in
+# domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
@@ -29,22 +30,22 @@ def get_task(na=None):
             "7": "person",
         },
         dict_d2filepath_list_img_tr={
-            "art_painting": "data/pacs_split/art_painting_train_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_train_kfold.txt",
-            "photo": "data/pacs_split/photo_train_kfold.txt",
-            "sketch": "data/pacs_split/sketch_train_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_train_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_train_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_train_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_train_kfold.txt",
         },
         dict_d2filepath_list_img_te={
-            "art_painting": "data/pacs_split/art_painting_test_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_test_kfold.txt",
-            "photo": "data/pacs_split/photo_test_kfold.txt",
-            "sketch": "data/pacs_split/sketch_test_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_test_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_test_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_test_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_test_kfold.txt",
         },
         dict_d2filepath_list_img_val={
-            "art_painting": "data/pacs_split/art_painting_crossval_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_crossval_kfold.txt",
-            "photo": "data/pacs_split/photo_crossval_kfold.txt",
-            "sketch": "data/pacs_split/sketch_crossval_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_crossval_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_crossval_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_crossval_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_crossval_kfold.txt",
         },
         dict_domain2imgroot={
             "art_painting": G_PACS_RAW_PATH,
diff --git a/examples/tasks/task_pacs_no_aug_norm_only.py b/examples/tasks/task_pacs_no_aug_norm_only.py
index 7a1897741..07e6339c3 100644
--- a/examples/tasks/task_pacs_no_aug_norm_only.py
+++ b/examples/tasks/task_pacs_no_aug_norm_only.py
@@ -11,8 +11,9 @@
 from domainlab.tasks.utils_task import ImSize
 
 # change this to absolute directory where you have the raw images from PACS,
-G_PACS_RAW_PATH = "data/pacs/PACS"
-# domainlab repository contain already the file names in data/pacs_split folder of domainlab
+G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
+# domainlab repository contain already the file names in
+# domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
@@ -29,22 +30,22 @@ def get_task(na=None):
             "7": "person",
         },
         dict_d2filepath_list_img_tr={
-            "art_painting": "data/pacs_split/art_painting_train_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_train_kfold.txt",
-            "photo": "data/pacs_split/photo_train_kfold.txt",
-            "sketch": "data/pacs_split/sketch_train_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_train_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_train_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_train_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_train_kfold.txt",
         },
         dict_d2filepath_list_img_te={
-            "art_painting": "data/pacs_split/art_painting_test_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_test_kfold.txt",
-            "photo": "data/pacs_split/photo_test_kfold.txt",
-            "sketch": "data/pacs_split/sketch_test_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_test_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_test_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_test_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_test_kfold.txt",
         },
         dict_d2filepath_list_img_val={
-            "art_painting": "data/pacs_split/art_painting_crossval_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_crossval_kfold.txt",
-            "photo": "data/pacs_split/photo_crossval_kfold.txt",
-            "sketch": "data/pacs_split/sketch_crossval_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_crossval_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_crossval_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_crossval_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_crossval_kfold.txt",
         },
         dict_domain2imgroot={
             "art_painting": G_PACS_RAW_PATH,
diff --git a/examples/tasks/task_pacs_path_list.py b/examples/tasks/task_pacs_path_list.py
index 045232b4a..53d97d640 100644
--- a/examples/tasks/task_pacs_path_list.py
+++ b/examples/tasks/task_pacs_path_list.py
@@ -11,8 +11,9 @@
 from domainlab.tasks.utils_task import ImSize
 
 # change this to absolute directory where you have the raw images from PACS,
-G_PACS_RAW_PATH = "data/pacs/PACS"
-# domainlab repository contain already the file names in data/pacs_split folder of domainlab
+G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
+# domainlab repository contain already the file names in
+# domainlab/zdata/pacs_split folder of domainlab
 
 
 def get_task(na=None):
@@ -29,22 +30,22 @@ def get_task(na=None):
             "7": "person",
         },
         dict_d2filepath_list_img_tr={
-            "art_painting": "data/pacs_split/art_painting_train_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_train_kfold.txt",
-            "photo": "data/pacs_split/photo_train_kfold.txt",
-            "sketch": "data/pacs_split/sketch_train_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_train_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_train_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_train_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_train_kfold.txt",
         },
         dict_d2filepath_list_img_te={
-            "art_painting": "data/pacs_split/art_painting_test_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_test_kfold.txt",
-            "photo": "data/pacs_split/photo_test_kfold.txt",
-            "sketch": "data/pacs_split/sketch_test_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_test_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_test_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_test_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_test_kfold.txt",
         },
         dict_d2filepath_list_img_val={
-            "art_painting": "data/pacs_split/art_painting_crossval_kfold.txt",
-            "cartoon": "data/pacs_split/cartoon_crossval_kfold.txt",
-            "photo": "data/pacs_split/photo_crossval_kfold.txt",
-            "sketch": "data/pacs_split/sketch_crossval_kfold.txt",
+            "art_painting": "domainlab/zdata/pacs_split/art_painting_crossval_kfold.txt",
+            "cartoon": "domainlab/zdata/pacs_split/cartoon_crossval_kfold.txt",
+            "photo": "domainlab/zdata/pacs_split/photo_crossval_kfold.txt",
+            "sketch": "domainlab/zdata/pacs_split/sketch_crossval_kfold.txt",
         },
         dict_domain2imgroot={
             "art_painting": G_PACS_RAW_PATH,
diff --git a/examples/tasks/task_vlcs.py b/examples/tasks/task_vlcs.py
index 3deb6b2d6..498ee27f2 100644
--- a/examples/tasks/task_vlcs.py
+++ b/examples/tasks/task_vlcs.py
@@ -52,9 +52,9 @@
     ),
     isize=ImSize(3, 224, 224),
     dict_domain2imgroot={
-        "caltech": os.path.join(path_this_file, "../../data/vlcs_mini/caltech/"),
-        "sun": os.path.join(path_this_file, "../../data/vlcs_mini/sun/"),
-        "labelme": os.path.join(path_this_file, "../../data/vlcs_mini/labelme/"),
+        "caltech": os.path.join(path_this_file, "../../domainlab/zdata/vlcs_mini/caltech/"),
+        "sun": os.path.join(path_this_file, "../../domainlab/zdata/vlcs_mini/sun/"),
+        "labelme": os.path.join(path_this_file, "../../domainlab/zdata/vlcs_mini/labelme/"),
     },
     taskna="e_mini_vlcs",
 )
diff --git a/scripts/sh_link_pacs_dataset.sh b/scripts/sh_link_pacs_dataset.sh
index 742f256e5..f973db02b 100644
--- a/scripts/sh_link_pacs_dataset.sh
+++ b/scripts/sh_link_pacs_dataset.sh
@@ -1,2 +1,2 @@
-mkdir -p data/pacs
-ln -s ~/Documents/datasets/pacs/raw data/pacs/PACS
+mkdir -p domainlab/zdata/pacs
+ln -s ~/Documents/datasets/pacs/raw domainlab/zdata/pacs/PACS
diff --git a/sh_download_pacs.sh b/sh_download_pacs.sh
old mode 100644
new mode 100755
index e6b8b2020..d28473892
--- a/sh_download_pacs.sh
+++ b/sh_download_pacs.sh
@@ -1,3 +1,3 @@
-mkdir -p data/pacs
-cd data/script
-python download_pacs.py
+mkdir -p domainlab/zdata/pacs
+cd domainlab/zdata/script
+python3 download_pacs.py
diff --git a/tests/dset_subfolder_test.py b/tests/dset_subfolder_test.py
index ccf9bc575..9491bb47c 100644
--- a/tests/dset_subfolder_test.py
+++ b/tests/dset_subfolder_test.py
@@ -10,7 +10,7 @@
 
 def test_fun():
     dset = DsetSubFolder(
-        root="data/vlcs_mini/caltech",
+        root="domainlab/zdata/vlcs_mini/caltech",
         list_class_dir=["auto", "vogel"],
         loader=fun_img_path_loader_default,
         extensions="jpg",
@@ -23,7 +23,7 @@ def test_fun():
 def test_mixed_codec():
     """Check if only images with given extension are loaded."""
     dset = DsetSubFolder(
-        root="data/mixed_codec/caltech",
+        root="domainlab/zdata/mixed_codec/caltech",
         list_class_dir=["auto", "vogel"],
         loader=fun_img_path_loader_default,
         extensions=None,
@@ -33,7 +33,7 @@ def test_mixed_codec():
     assert len(dset.samples) == 6
 
     dset = DsetSubFolder(
-        root="data/mixed_codec/caltech",
+        root="domainlab/zdata/mixed_codec/caltech",
         list_class_dir=["auto", "vogel"],
         loader=fun_img_path_loader_default,
         extensions="jpg",
@@ -42,11 +42,11 @@ def test_mixed_codec():
     )
     assert (
         len(dset.samples) == 4
-    ), f"data/mixed_codec contains 4 jpg files, but {len(dset.samples)} were loaded."
+    ), f"domainlab/zdata/mixed_codec contains 4 jpg files, but {len(dset.samples)} were loaded."
 
     with pytest.raises(ValueError):
         DsetSubFolder(
-            root="data/mixed_codec/caltech",
+            root="domainlab/zdata/mixed_codec/caltech",
             list_class_dir=["auto", "vogel"],
             loader=fun_img_path_loader_default,
             extensions="jpg",
@@ -60,7 +60,7 @@ def test_wrong_class_names():
     """Check for error if list_class_dir does not match the subfolders."""
     with pytest.raises(RuntimeError):
         DsetSubFolder(
-            root="data/mixed_codec/caltech",
+            root="domainlab/zdata/mixed_codec/caltech",
             list_class_dir=["auto", "haus"],
             loader=fun_img_path_loader_default,
             extensions=None,
diff --git a/tests/dset_utils_data_test.py b/tests/dset_utils_data_test.py
index 3b618146c..41b580935 100644
--- a/tests/dset_utils_data_test.py
+++ b/tests/dset_utils_data_test.py
@@ -3,7 +3,7 @@
 
 
 def test_dset_in_mem_decorator():
-    dset = DsetMNISTColorSoloDefault(path="../data", ind_color=1)
+    dset = DsetMNISTColorSoloDefault(path="../domainlab/zdata", ind_color=1)
     dset_in_memory = DsetInMemDecorator(dset=dset)
     dset_in_memory.__len__()
     dset_in_memory.__getitem__(0)
diff --git a/tests/test_benchmark_plots.py b/tests/test_benchmark_plots.py
index f8018dd5f..855157b7f 100644
--- a/tests/test_benchmark_plots.py
+++ b/tests/test_benchmark_plots.py
@@ -9,10 +9,10 @@ def test_benchm_plots():
     test benchmark plots
     """
     gen_benchmark_plots(
-        "data/ztest_files/aggret_res_test1",
+        "domainlab/zdata/ztest_files/aggret_res_test1",
         "zoutput/benchmark_plots_test/outp1",
         use_param_index=False,
     )
     gen_benchmark_plots(
-        "data/ztest_files/aggret_res_test2", "zoutput/benchmark_plots_test/outp2"
+        "domainlab/zdata/ztest_files/aggret_res_test2", "zoutput/benchmark_plots_test/outp2"
     )
diff --git a/tests/test_exp_protocol.py b/tests/test_exp_protocol.py
index 2f9ca03ea..bae262258 100644
--- a/tests/test_exp_protocol.py
+++ b/tests/test_exp_protocol.py
@@ -33,7 +33,7 @@ def utils_run_experiment(yaml_name, list_test_domains, no_run=True):
     config["startseed"] = 1
     config["endseed"] = 1
     config["test_domains"] = list_test_domains
-    param_file = "data/ztest_files/test_parameter_samples.csv"
+    param_file = "domainlab/zdata/ztest_files/test_parameter_samples.csv"
     param_index = 0
     out_file = "zoutput/benchmarks/demo_benchmark/rule_results/0.csv"
 
diff --git a/tests/test_git_tag.py b/tests/test_git_tag.py
index 2bd96e146..72616a2ed 100644
--- a/tests/test_git_tag.py
+++ b/tests/test_git_tag.py
@@ -19,14 +19,14 @@ def test_git_tag_error():
     test git_tag error
     """
     # add one line to the file
-    with open("data/ztest_files/dummy_file.py", "a") as f:
+    with open("domainlab/zdata/ztest_files/dummy_file.py", "a") as f:
         f.write("\n# I am a dummy command")
     get_git_tag(print_diff=True)
     # delete the last line on the file again
-    with open("data/ztest_files/dummy_file.py", "r") as f:
+    with open("domainlab/zdata/ztest_files/dummy_file.py", "r") as f:
         lines = f.readlines()
         lines = lines[:-1]
-    with open("data/ztest_files/dummy_file.py", "w") as f:
+    with open("domainlab/zdata/ztest_files/dummy_file.py", "w") as f:
         for num, line in enumerate(lines):
             if num == len(lines) - 1:
                 f.write(line[:-2])
diff --git a/tests/test_hyperparameter_retrieval.py b/tests/test_hyperparameter_retrieval.py
new file mode 100644
index 000000000..fa3119e98
--- /dev/null
+++ b/tests/test_hyperparameter_retrieval.py
@@ -0,0 +1,32 @@
+"""
+unit test for hyperparameter parsing
+"""
+from domainlab.arg_parser import mk_parser_main
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
+
+def test_store_dict_key_pair_single_value():
+    """Test to parse a single gamma_reg parameter"""
+    parser = mk_parser_main()
+    args = parser.parse_args(['--gamma_reg', '0.5'])
+    assert args.gamma_reg == 0.5
+
+def test_store_dict_key_pair_dict_value():
+    """Test to parse a dict for the gamma_reg"""
+    parser = mk_parser_main()
+    args = parser.parse_args(['--gamma_reg', 'dann=1.0,jigen=2.0'])
+    assert args.gamma_reg == {'dann': 1.0, 'jigen': 2.0}
+
+def test_get_gamma_reg_single_value():
+    """Test to retrieve a single gamma_reg parameter which is applied to all objects"""
+    parser = mk_parser_main()
+    args = parser.parse_args(['--gamma_reg', '0.5'])
+    assert get_gamma_reg(args, 'dann') == 0.5
+
+def test_get_gamma_reg_dict_value():
+    """Test to retrieve a dict of gamma_reg parameters for different objects"""
+    parser = mk_parser_main()
+    args = parser.parse_args(['--gamma_reg', 'default=5.0,dann=1.0,jigen=2.0'])
+    print(args)
+    assert get_gamma_reg(args, 'dann') == 1.0
+    assert get_gamma_reg(args, 'jigen') == 2.0
+    assert get_gamma_reg(args, 'nonexistent') == 5.0
diff --git a/tests/test_msel_oracle.py b/tests/test_msel_oracle.py
index 3dfdd6fbe..8a28567b0 100644
--- a/tests/test_msel_oracle.py
+++ b/tests/test_msel_oracle.py
@@ -66,7 +66,7 @@ def mk_exp(
             model_sel.msel._best_val_acc = 1.0
     observer = ObVisitor(model_sel)
     exp = Exp(conf, task, model=model, observer=observer)
-    model_sel.update(clear_counter=True)
+    model_sel.update(epoch=1, clear_counter=True)
     return exp
 
 
@@ -142,7 +142,7 @@ def test_msel_oracle1():
     )
 
     exp.execute(num_epochs=2)
-    exp.trainer.observer.model_sel.msel.update(clear_counter=True)
+    exp.trainer.observer.model_sel.msel.update(epoch=1, clear_counter=True)
     del exp
 
 
@@ -261,5 +261,5 @@ def test_msel_oracle4():
     )
     exp.execute(num_epochs=2)
     exp.trainer.observer.model_sel.msel.best_loss = 0
-    exp.trainer.observer.model_sel.msel.update(clear_counter=True)
+    exp.trainer.observer.model_sel.msel.update(epoch = 1, clear_counter=True)
     del exp
diff --git a/tests/test_run_experiment.py b/tests/test_run_experiment.py
index b22593a91..98cc5201d 100644
--- a/tests/test_run_experiment.py
+++ b/tests/test_run_experiment.py
@@ -18,7 +18,7 @@ def test_run_experiment():
     config["startseed"] = 1
     config["endseed"] = 1
     config["test_domains"] = ["caltech"]
-    param_file = "data/ztest_files/test_parameter_samples.csv"
+    param_file = "domainlab/zdata/ztest_files/test_parameter_samples.csv"
     param_index = 0
     out_file = "zoutput/benchmarks/demo_benchmark/rule_results/0.csv"
 
@@ -41,7 +41,7 @@ def test_run_experiment_parameter_doubling_error():
     config["endseed"] = 1
     config["test_domains"] = ["caltech"]
     config["diva"]["gamma_y"] = 1e4
-    param_file = "data/ztest_files/test_parameter_samples.csv"
+    param_file = "domainlab/zdata/ztest_files/test_parameter_samples.csv"
     param_index = 0
     out_file = "zoutput/benchmarks/demo_benchmark/rule_results/0.csv"
 
@@ -58,7 +58,7 @@ def test_run_experiment_parameter_doubling_error():
     config["endseed"] = 1
     config["test_domains"] = ["caltech"]
     config["domainlab_args"]["gamma_y"] = 1e4
-    param_file = "data/ztest_files/test_parameter_samples.csv"
+    param_file = "domainlab/zdata/ztest_files/test_parameter_samples.csv"
     param_index = 0
     out_file = "zoutput/benchmarks/demo_benchmark/rule_results/0.csv"
 
diff --git a/tests/test_task_folder.py b/tests/test_task_folder.py
index 3b78b5f2c..ed2683a23 100644
--- a/tests/test_task_folder.py
+++ b/tests/test_task_folder.py
@@ -36,9 +36,9 @@ def test_fun():
         ),
         isize=ImSize(3, 224, 224),
         dict_domain2imgroot={
-            "caltech": "data/vlcs_mini/caltech/",
-            "sun": "data/vlcs_mini/sun/",
-            "labelme": "data/vlcs_mini/labelme/",
+            "caltech": "domainlab/zdata/vlcs_mini/caltech/",
+            "sun": "domainlab/zdata/vlcs_mini/sun/",
+            "labelme": "domainlab/zdata/vlcs_mini/labelme/",
         },
         taskna="mini_vlcs",
         succ=None,
@@ -99,9 +99,9 @@ def test_mk_task_folder():
         },
         isize=ImSize(3, 224, 224),
         dict_domain2imgroot={
-            "caltech": "data/vlcs_mini/caltech/",
-            "sun": "data/vlcs_mini/sun/",
-            "labelme": "data/vlcs_mini/labelme/",
+            "caltech": "domainlab/zdata/vlcs_mini/caltech/",
+            "sun": "domainlab/zdata/vlcs_mini/sun/",
+            "labelme": "domainlab/zdata/vlcs_mini/labelme/",
         },
         taskna="mini_vlcs",
     )
@@ -133,9 +133,9 @@ def test_none_extensions():
         ),
         isize=ImSize(3, 224, 224),
         dict_domain2imgroot={
-            "caltech": "data/vlcs_mini/caltech/",
-            "labelme": "data/vlcs_mini/labelme/",
-            "sun": "data/vlcs_mini/sun/",
+            "caltech": "domainlab/zdata/vlcs_mini/caltech/",
+            "labelme": "domainlab/zdata/vlcs_mini/labelme/",
+            "sun": "domainlab/zdata/vlcs_mini/sun/",
         },
         taskna="mini_vlcs",
         succ=None,
@@ -169,8 +169,8 @@ def test_none_extensions():
         ),
         isize=ImSize(3, 224, 224),
         dict_domain2imgroot={
-            "caltech": "data/mixed_codec/caltech/",
-            "sun": "data/mixed_codec/sun/",
+            "caltech": "domainlab/zdata/mixed_codec/caltech/",
+            "sun": "domainlab/zdata/mixed_codec/sun/",
         },
         taskna="mixed_codec",
         succ=None,
@@ -208,8 +208,8 @@ def test_none_extensions():
         ),
         isize=ImSize(3, 224, 224),
         dict_domain2imgroot={
-            "caltech": "data/mixed_codec/caltech/",
-            "sun": "data/mixed_codec/sun/",
+            "caltech": "domainlab/zdata/mixed_codec/caltech/",
+            "sun": "domainlab/zdata/mixed_codec/sun/",
         },
         taskna="mixed_codec",
         succ=None,
@@ -231,8 +231,8 @@ def pacs_node():
     node.extensions = ("jpg",)
     node.list_str_y = ["dog", "elephant"]
     node.dict_domain2imgroot = {
-        "cartoon": "data/pacs_mini_10/cartoon/",
-        "photo": "data/pacs_mini_10/photo/",
+        "cartoon": "domainlab/zdata/pacs_mini_10/cartoon/",
+        "photo": "domainlab/zdata/pacs_mini_10/photo/",
     }
     return node
 

From 5a6ba4e856913f8eb0d9b831ed3832221405a003 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 09:00:23 +0200
Subject: [PATCH 049/273] Added changes to the new model selection

---
 domainlab/algos/msels/c_msel_setpoint_delay.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/domainlab/algos/msels/c_msel_setpoint_delay.py b/domainlab/algos/msels/c_msel_setpoint_delay.py
index 8387dbb26..a9c8933ea 100644
--- a/domainlab/algos/msels/c_msel_setpoint_delay.py
+++ b/domainlab/algos/msels/c_msel_setpoint_delay.py
@@ -11,8 +11,8 @@ class MSelSetpointDelay(AMSel):
     selected performance from the decoratee each time the setpoint shrinks
     """
 
-    def __init__(self, msel):
-        super().__init__()
+    def __init__(self, msel, val_threshold = None):
+        super().__init__(val_threshold)
         # NOTE: super() has to come first always otherwise self.msel will be overwritten to be None
         self.msel = msel
         self._oracle_last_setpoint_sel_te_acc = 0.0

From febe8760366adcd991f66b469284502177e55cd6 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 11:16:44 +0200
Subject: [PATCH 050/273] Increased test coverage

---
 domainlab/arg_parser.py                | 29 ++++++------
 tests/test_a_model.py                  | 64 ++++++++++++++++++++++++++
 tests/test_a_trainer.py                | 34 ++++++++++++++
 tests/test_argparse.py                 | 31 ++++++++++++-
 tests/test_hyperparameter_retrieval.py | 10 +++-
 5 files changed, 153 insertions(+), 15 deletions(-)
 create mode 100644 tests/test_a_model.py
 create mode 100644 tests/test_a_trainer.py

diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index 50ab707db..32faa48be 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -12,21 +12,24 @@
 from domainlab.models.args_vae import add_args2parser_vae
 from domainlab.utils.logger import Logger
 
-class StoreDictKeyPair(argparse.Action):
+class ParseValuesOrKeyValuePairs(argparse.Action):
     """Class used for arg parsing where values are provided in a key value format"""
 
     def __call__(self, parser, namespace, values, option_string=None):
-        try:
-            if "=" in values:
-                my_dict = {}
-                for kv in values.split(","):
-                    k, v = kv.split("=")
-                    my_dict[k.strip()] = float(v.strip())  # Assuming values are floats
-                setattr(namespace, self.dest, my_dict)
-            else:
-                setattr(namespace, self.dest, float(values))  # Single float value
-        except ValueError:
-            raise argparse.ArgumentError(self, f"Invalid value for {self.dest}: {values}")
+        if "=" in values:
+            my_dict = {}
+            for kv in values.split(","):
+                k, v = kv.split("=")
+                try:
+                    my_dict[k.strip()] = float(v.strip())
+                except ValueError:
+                    raise ValueError(f"Invalid value in key-value pair: '{kv}', must be float")
+            setattr(namespace, self.dest, my_dict)
+        else:
+            try:
+                setattr(namespace, self.dest, float(values))
+            except ValueError:
+                raise ValueError(f"Invalid value for {self.dest}: '{values}', must be float")
 
 def mk_parser_main():
     """
@@ -49,7 +52,7 @@ def mk_parser_main():
         "--gamma_reg",
         default=0.1,
         help="weight of regularization loss, can specify per model as 'dann=1.0,diva=2.0'",
-        action=StoreDictKeyPair
+        action=ParseValuesOrKeyValuePairs
     )
 
     parser.add_argument("--es", type=int, default=1, help="early stop steps")
diff --git a/tests/test_a_model.py b/tests/test_a_model.py
new file mode 100644
index 000000000..c770f271d
--- /dev/null
+++ b/tests/test_a_model.py
@@ -0,0 +1,64 @@
+"""
+Test a model functionality
+"""
+
+import pytest
+from io import StringIO
+import sys
+from torch import nn
+from domainlab.models.a_model import AModel
+
+class ModelTest(AModel):
+    """
+    A test model class conforming to model naming
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.test_param = 42
+
+    def cal_task_loss(self, tensor_x, tensor_y):
+        return 0
+
+    def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
+        return 0
+
+
+class InvalidTest(AModel):
+    """
+    A test model class that does not conform to the "Model" prefix naming convention
+    """
+
+    def cal_task_loss(self, tensor_x, tensor_y):
+        return 0
+
+    def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
+        return 0
+
+
+def test_model_name_valid():
+    """
+    Test a valid model name
+    """
+    model = ModelTest()
+    assert model.name == "test", f"Expected 'test' but got '{model.name}'"
+
+
+def test_model_name_invalid():
+    """
+    Test an invalid model name
+    """
+    model = InvalidTest()
+    with pytest.raises(RuntimeError, match="Model builder node class must start with"):
+        model.name
+
+
+def test_print_parameters(capsys):
+    """
+    Test the printing of parameters
+    """
+    model = ModelTest()
+    model.print_parameters()
+    captured = capsys.readouterr()
+    assert "Parameters of ModelTest:" in captured.out
+    assert "'test_param': 42" in captured.out    
\ No newline at end of file
diff --git a/tests/test_a_trainer.py b/tests/test_a_trainer.py
new file mode 100644
index 000000000..4543f0d20
--- /dev/null
+++ b/tests/test_a_trainer.py
@@ -0,0 +1,34 @@
+"""
+Test a trainer functionality
+"""
+
+from domainlab.algos.trainers.a_trainer import AbstractTrainer
+
+class TrainerTest(AbstractTrainer):
+    """
+    A test trainer class conforming to model naming
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.test_param = 42
+
+    def tr_epoch(self, epoch):
+        """
+        :param epoch:
+        """
+
+    def before_tr(self):
+        """
+        before training, probe model performance
+        """
+
+def test_print_parameters(capsys):
+    """
+    Test the printing of parameters
+    """
+    trainer = TrainerTest()
+    trainer.print_parameters()
+    captured = capsys.readouterr()
+    assert "Parameters of TrainerTest:" in captured.out
+    assert "'test_param': 42" in captured.out    
\ No newline at end of file
diff --git a/tests/test_argparse.py b/tests/test_argparse.py
index 683f66911..199f6d56a 100644
--- a/tests/test_argparse.py
+++ b/tests/test_argparse.py
@@ -7,7 +7,8 @@
 
 import pytest
 
-from domainlab.arg_parser import apply_dict_to_args, mk_parser_main, parse_cmd_args
+from domainlab.arg_parser import apply_dict_to_args, mk_parser_main, parse_cmd_args, ParseValuesOrKeyValuePairs
+import argparse
 
 
 def test_parse_cmd_args_warning():
@@ -54,3 +55,31 @@ def test_apply_dict_to_args():
     apply_dict_to_args(args, data, extend=True)
     assert args.a == 1
     assert args.model == "diva"
+
+def test_store_dict_key_value_valid():
+    """Testing to parse valid gamma_reg value"""
+    parser = mk_parser_main()
+    parser.add_argument("--keypair", action=ParseValuesOrKeyValuePairs)
+    namespace = parser.parse_args(["--keypair", "1"])
+    assert namespace.keypair == 1.0
+
+def test_store_dict_key_value_pair_valid():
+    """Testing to parse valid gamma_reg key value paris"""
+    parser = mk_parser_main()
+    parser.add_argument("--keypair", action=ParseValuesOrKeyValuePairs)
+    namespace = parser.parse_args(["--keypair", "value1=1,value2=2"])
+    assert namespace.keypair == {"value1": 1.0, "value2": 2.0}
+
+def test_store_dict_key_value_invalid():
+    """Testing to parse invalid gamma_reg value"""
+    parser = mk_parser_main()
+    parser.add_argument("--keypair", action=ParseValuesOrKeyValuePairs)
+    with pytest.raises(ValueError):
+        parser.parse_args(["--keypair", "invalid"])
+
+def test_store_dict_key_value_pair_invalid():
+    """Testing to parse invalid gamma_reg key value pairs"""
+    parser = mk_parser_main()
+    parser.add_argument("--keypair", action=ParseValuesOrKeyValuePairs)
+    with pytest.raises(ValueError):
+        parser.parse_args(["--keypair", "value1=1,value2=invalid"])
diff --git a/tests/test_hyperparameter_retrieval.py b/tests/test_hyperparameter_retrieval.py
index fa3119e98..ec2f4d2b4 100644
--- a/tests/test_hyperparameter_retrieval.py
+++ b/tests/test_hyperparameter_retrieval.py
@@ -3,6 +3,7 @@
 """
 from domainlab.arg_parser import mk_parser_main
 from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
+import pytest
 
 def test_store_dict_key_pair_single_value():
     """Test to parse a single gamma_reg parameter"""
@@ -26,7 +27,14 @@ def test_get_gamma_reg_dict_value():
     """Test to retrieve a dict of gamma_reg parameters for different objects"""
     parser = mk_parser_main()
     args = parser.parse_args(['--gamma_reg', 'default=5.0,dann=1.0,jigen=2.0'])
-    print(args)
     assert get_gamma_reg(args, 'dann') == 1.0
     assert get_gamma_reg(args, 'jigen') == 2.0
     assert get_gamma_reg(args, 'nonexistent') == 5.0
+
+def test_exception():
+    """Test to not specify a default value"""
+    parser = mk_parser_main()
+    args = parser.parse_args(['--gamma_reg', 'dann=1.0'])
+
+    with pytest.raises(ValueError, match="If a gamma_reg dict is specified"):
+        get_gamma_reg(args, 'jigen')

From fd360565d9aab1ca3cb60b90feac0493b6ced126 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 11:28:09 +0200
Subject: [PATCH 051/273] fixed codacity

---
 tests/test_a_model.py                  | 18 +++++++++++-------
 tests/test_a_trainer.py                |  2 +-
 tests/test_argparse.py                 |  8 ++------
 tests/test_hyperparameter_retrieval.py |  2 +-
 4 files changed, 15 insertions(+), 15 deletions(-)

diff --git a/tests/test_a_model.py b/tests/test_a_model.py
index c770f271d..8480cfd55 100644
--- a/tests/test_a_model.py
+++ b/tests/test_a_model.py
@@ -1,11 +1,7 @@
 """
 Test a model functionality
 """
-
 import pytest
-from io import StringIO
-import sys
-from torch import nn
 from domainlab.models.a_model import AModel
 
 class ModelTest(AModel):
@@ -22,6 +18,10 @@ def cal_task_loss(self, tensor_x, tensor_y):
 
     def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         return 0
+    
+    @property
+    def metric4msel(self):
+        return ""
 
 
 class InvalidTest(AModel):
@@ -35,6 +35,10 @@ def cal_task_loss(self, tensor_x, tensor_y):
     def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         return 0
 
+    @property
+    def metric4msel(self):
+        return ""
+
 
 def test_model_name_valid():
     """
@@ -49,8 +53,7 @@ def test_model_name_invalid():
     Test an invalid model name
     """
     model = InvalidTest()
-    with pytest.raises(RuntimeError, match="Model builder node class must start with"):
-        model.name
+    with pytest.raises(RuntimeError, match="Model builder node class must start with"): model.name
 
 
 def test_print_parameters(capsys):
@@ -61,4 +64,5 @@ def test_print_parameters(capsys):
     model.print_parameters()
     captured = capsys.readouterr()
     assert "Parameters of ModelTest:" in captured.out
-    assert "'test_param': 42" in captured.out    
\ No newline at end of file
+    assert "'test_param': 42" in captured.out
+  
\ No newline at end of file
diff --git a/tests/test_a_trainer.py b/tests/test_a_trainer.py
index 4543f0d20..d4e073ae3 100644
--- a/tests/test_a_trainer.py
+++ b/tests/test_a_trainer.py
@@ -31,4 +31,4 @@ def test_print_parameters(capsys):
     trainer.print_parameters()
     captured = capsys.readouterr()
     assert "Parameters of TrainerTest:" in captured.out
-    assert "'test_param': 42" in captured.out    
\ No newline at end of file
+    assert "'test_param': 42" in captured.out
diff --git a/tests/test_argparse.py b/tests/test_argparse.py
index 199f6d56a..2eaaae10b 100644
--- a/tests/test_argparse.py
+++ b/tests/test_argparse.py
@@ -1,15 +1,11 @@
 """
 Test argparser functionality
 """
-
 import os
 import sys
-
 import pytest
-
-from domainlab.arg_parser import apply_dict_to_args, mk_parser_main, parse_cmd_args, ParseValuesOrKeyValuePairs
-import argparse
-
+from domainlab.arg_parser import apply_dict_to_args, mk_parser_main, parse_cmd_args
+from domainlab.arg_parser import ParseValuesOrKeyValuePairs
 
 def test_parse_cmd_args_warning():
     """Call argparser for command line"""
diff --git a/tests/test_hyperparameter_retrieval.py b/tests/test_hyperparameter_retrieval.py
index ec2f4d2b4..cfc7b28f9 100644
--- a/tests/test_hyperparameter_retrieval.py
+++ b/tests/test_hyperparameter_retrieval.py
@@ -1,9 +1,9 @@
 """
 unit test for hyperparameter parsing
 """
+import pytest
 from domainlab.arg_parser import mk_parser_main
 from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
-import pytest
 
 def test_store_dict_key_pair_single_value():
     """Test to parse a single gamma_reg parameter"""

From 6520834b1af455710b8b656eb8e7195ada50b84e Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 11:33:18 +0200
Subject: [PATCH 052/273] fixed codacity

---
 tests/test_a_model.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/tests/test_a_model.py b/tests/test_a_model.py
index 8480cfd55..5b2d7bd0a 100644
--- a/tests/test_a_model.py
+++ b/tests/test_a_model.py
@@ -18,7 +18,7 @@ def cal_task_loss(self, tensor_x, tensor_y):
 
     def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         return 0
-    
+
     @property
     def metric4msel(self):
         return ""
@@ -53,7 +53,8 @@ def test_model_name_invalid():
     Test an invalid model name
     """
     model = InvalidTest()
-    with pytest.raises(RuntimeError, match="Model builder node class must start with"): model.name
+    with pytest.raises(RuntimeError, match="Model builder node class must start with"): 
+        _ = model.name
 
 
 def test_print_parameters(capsys):

From c5e3e6af6bb3480497a9f74dfa9dde8c4b23c3f7 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 11:36:31 +0200
Subject: [PATCH 053/273] fixed codacity

---
 tests/test_a_model.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_a_model.py b/tests/test_a_model.py
index 5b2d7bd0a..fac060f06 100644
--- a/tests/test_a_model.py
+++ b/tests/test_a_model.py
@@ -53,7 +53,7 @@ def test_model_name_invalid():
     Test an invalid model name
     """
     model = InvalidTest()
-    with pytest.raises(RuntimeError, match="Model builder node class must start with"): 
+    with pytest.raises(RuntimeError, match="Model builder node class must start with"):
         _ = model.name
 
 

From 7173bd09c8f5da9024a9854cf7fda15ed0e347f8 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 12:19:09 +0200
Subject: [PATCH 054/273] Added changes to benchmark script

---
 run_benchmark_standalone.sh | 13 ++++++++++++-
 1 file changed, 12 insertions(+), 1 deletion(-)

diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index 8f712d1d1..4c02427e8 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -47,6 +47,17 @@ else
       export NUMBER_GPUS=$4
 fi
 
+# Extract output_dir from the YAML configuration file
+output_dir=$(awk '/output_dir:/ {print $2}' "$CONFIGFILE")
+if [ -z "$output_dir" ]; then
+  echo "Error: output_dir not specified in $CONFIGFILE"
+  exit 1
+fi
+
+# Create a timestamped output directory
+results_dir="${output_dir}_$(timestamp)"
+mkdir -p "$results_dir"
+
 
 # -n: dry-run  (A dry run is a software testing process where the effects of a possible failure are intentionally mitigated, For example, there is rsync utility for transfer data over some interface, but user can try rsync with dry-run option to check syntax and test communication without data transferring.)
 # -p: print shell commands
@@ -61,7 +72,7 @@ fi
 snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --keep-going --summary  # this will give us a clue first what jobs will be run
 
 # second submit the jobs, make sure you have more than 4 cores on your laptop, otherwise adjust the cores
-snakemake --config yaml_file=$CONFIGFILE --rerun-incomplete --resources nvidia_gpu=$NUMBER_GPUS --cores 4 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" 2>&1 | tee "$logfile"
+snakemake --config yaml_file=$CONFIGFILE --rerun-incomplete --resources nvidia_gpu=$NUMBER_GPUS --cores 4 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
 
 
 # snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk" --configfile "examples/yaml/demo_benchmark.yaml"

From 064471bce55c7db47d6031db6ae49e89e71df4ca Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 12:26:48 +0200
Subject: [PATCH 055/273] Added changes to benchmark script to add timestamp to
 output directory

---
 run_benchmark_slurm.sh      | 11 ++++++++++-
 run_benchmark_standalone.sh |  1 -
 2 files changed, 10 insertions(+), 2 deletions(-)

diff --git a/run_benchmark_slurm.sh b/run_benchmark_slurm.sh
index 61615198a..39ae4751e 100755
--- a/run_benchmark_slurm.sh
+++ b/run_benchmark_slurm.sh
@@ -20,6 +20,15 @@ else
       export DOMAINLAB_CUDA_START_SEED=$2
 fi
 
+# Extract output_dir from the YAML configuration file
+output_dir=$(awk '/output_dir:/ {print $2}' "$CONFIGFILE")
+if [ -z "$output_dir" ]; then
+  echo "Error: output_dir not specified in $CONFIGFILE"
+  exit 1
+fi
+
+# Create a timestamped output directory
+results_dir="${output_dir}_$(timestamp)"
 
 # ensure all runs sample the same hyperparameters
 export DOMAINLAB_CUDA_HYPERPARAM_SEED=0
@@ -32,4 +41,4 @@ echo "Configuration file: $CONFIGFILE"
 echo "starting seed is: $DOMAINLAB_CUDA_START_SEED"
 echo "verbose log: $logfile"
 # Helmholtz
-snakemake --profile "examples/yaml/slurm" --config yaml_file=$CONFIGFILE --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" 2>&1 | tee "$logfile"
+snakemake --profile "examples/yaml/slurm" --config yaml_file=$CONFIGFILE --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index 4c02427e8..31fb46ba2 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -56,7 +56,6 @@ fi
 
 # Create a timestamped output directory
 results_dir="${output_dir}_$(timestamp)"
-mkdir -p "$results_dir"
 
 
 # -n: dry-run  (A dry run is a software testing process where the effects of a possible failure are intentionally mitigated, For example, there is rsync utility for transfer data over some interface, but user can try rsync with dry-run option to check syntax and test communication without data transferring.)

From 884682b54c1cf9c597498bd93559bf7d09ac2280 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 14:12:20 +0200
Subject: [PATCH 056/273] Added quotes around variables

---
 run_benchmark_slurm.sh      | 2 +-
 run_benchmark_standalone.sh | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/run_benchmark_slurm.sh b/run_benchmark_slurm.sh
index 61615198a..8db5b6965 100755
--- a/run_benchmark_slurm.sh
+++ b/run_benchmark_slurm.sh
@@ -32,4 +32,4 @@ echo "Configuration file: $CONFIGFILE"
 echo "starting seed is: $DOMAINLAB_CUDA_START_SEED"
 echo "verbose log: $logfile"
 # Helmholtz
-snakemake --profile "examples/yaml/slurm" --config yaml_file=$CONFIGFILE --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" 2>&1 | tee "$logfile"
+snakemake --profile "examples/yaml/slurm" --config yaml_file="$CONFIGFILE" --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" 2>&1 | tee "$logfile"
diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index 8f712d1d1..386b7dab5 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -61,7 +61,7 @@ fi
 snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --keep-going --summary  # this will give us a clue first what jobs will be run
 
 # second submit the jobs, make sure you have more than 4 cores on your laptop, otherwise adjust the cores
-snakemake --config yaml_file=$CONFIGFILE --rerun-incomplete --resources nvidia_gpu=$NUMBER_GPUS --cores 4 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" 2>&1 | tee "$logfile"
+snakemake --config yaml_file="$CONFIGFILE" --rerun-incomplete --resources nvidia_gpu="$NUMBER_GPUS" --cores 4 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" 2>&1 | tee "$logfile"
 
 
 # snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk" --configfile "examples/yaml/demo_benchmark.yaml"

From 2d869fa5f567df9224baba55cc719e39b3ecd110 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 14:16:01 +0200
Subject: [PATCH 057/273] Added quotes around variables

---
 run_benchmark_slurm.sh      | 2 +-
 run_benchmark_standalone.sh | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/run_benchmark_slurm.sh b/run_benchmark_slurm.sh
index 39ae4751e..1d5ca419d 100755
--- a/run_benchmark_slurm.sh
+++ b/run_benchmark_slurm.sh
@@ -41,4 +41,4 @@ echo "Configuration file: $CONFIGFILE"
 echo "starting seed is: $DOMAINLAB_CUDA_START_SEED"
 echo "verbose log: $logfile"
 # Helmholtz
-snakemake --profile "examples/yaml/slurm" --config yaml_file=$CONFIGFILE --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
+snakemake --profile "examples/yaml/slurm" --config yaml_file="$CONFIGFILE" --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index 31fb46ba2..fffb953cb 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -71,7 +71,7 @@ results_dir="${output_dir}_$(timestamp)"
 snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --keep-going --summary  # this will give us a clue first what jobs will be run
 
 # second submit the jobs, make sure you have more than 4 cores on your laptop, otherwise adjust the cores
-snakemake --config yaml_file=$CONFIGFILE --rerun-incomplete --resources nvidia_gpu=$NUMBER_GPUS --cores 4 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
+snakemake --config yaml_file="$CONFIGFILE" --rerun-incomplete --resources nvidia_gpu="$NUMBER_GPUS" --cores 4 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
 
 
 # snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk" --configfile "examples/yaml/demo_benchmark.yaml"

From d957d3f766a0756301bd2c73d660d201de03acb0 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 7 May 2024 15:06:23 +0200
Subject: [PATCH 058/273] Added more documentation for the task

---
 docs/doc_tasks.md | 28 +++++++++++++++++-----------
 1 file changed, 17 insertions(+), 11 deletions(-)

diff --git a/docs/doc_tasks.md b/docs/doc_tasks.md
index 1d37bc385..21a774c59 100644
--- a/docs/doc_tasks.md
+++ b/docs/doc_tasks.md
@@ -32,10 +32,16 @@ To give an example, suppose we have a classification task to classify between ca
 
 In each folder, the images are organized in sub-folders by their class. For example, "/path/to/3rd_domain/folder_c/dog" folder contains all the images of class "dog" from the 3rd domain.
 
-It might be the case that across the different data sources the same class is named differently. For example, in the 1st data source, the class dog is stored in sub-folder named
-"hund", in the 2nd data source, the dog is stored in sub-folder named "husky" and in the 3rd data source, the dog is stored in sub-folder named "dog".
+It might be the case that the same classes are named differently across the different data sources. For example, in the 1st data source, the class dog is stored in a sub-folder named "hund", in the 2nd data source, the dog is stored in a sub-folder named "husky", and in the 3rd data source, the dog is stored in a sub-folder called "dog".
 
-It might also be the case that some classes exist in one data source but does not exist in another data source. For example, folder "/path/to/2nd_domain/folder_b" does not have a sub-folder for class "human".
+In that case, we can use `dict_domain_folder_name2class` to map the corresponding subfolders to the correct domain. The `dict_domain_folder_name2class` parameter is a dictionary where:
+
+- Key: The name of a subfolder in a specific domain.
+- Value: The corresponding user-defined class name.
+
+This is also shown in the example below, where the dictionary maps the different subfolder names to 'car' and 'chair', which are the user defined classes. A more complex example of such a mapping can be found [here](../examples/tasks/task_blood3.py).
+
+It might also be the case that some classes exist in one data source but do not exist in another data source. For example, folder "/path/to/2nd_domain/folder_b" does not have a sub-folder for the class "human". In that case, we don't add the entry into the `dict_domain_folder_name2class` mapping.
 
 Folder structure of the 1st domain:
 ```text
@@ -125,28 +131,28 @@ from domainlab.tasks import mk_task_folder
 print(mk_task_folder.__doc__)
 ```
 
-extensions: a python dictionary with key as the domain name
+`extensions`: a python dictionary with key as the domain name
 and value as the file extensions of the image.
 
-list_str_y: a python list with user defined class names where
+`list_str_y`: a python list with user defined class names where
 the order of the list matters.
 
-dict_domain_folder_name2class: a python dictionary, with key
+`dict_domain_folder_name2class`: a python dictionary, with key
 as the user specified domain name, value as a dictionary to map the
 sub-folder name of each domain's class folder into the user defined
 common class name.
 
-dict_domain_img_trans: a python dictionary with keys as the user
+`dict_domain_img_trans`: a python dictionary with keys as the user
 specified domain name, value as a user defined torchvision transform.
 This feature allows carrying out different transformation (composition) to different
 domains at training time.
 
-img_trans_te: at test or inference time, we do not have knowledge
+`img_trans_te`: at test or inference time, we do not have knowledge
 of domain information so only a unique transform (composition) is allowed.
 
-isize: domainlab.tasks.ImSize(image channel, image height, image width)
+`isize`: domainlab.tasks.ImSize(image channel, image height, image width)
 
-dict_domain2imgroot: a python dictionary with keys as user specified domain names and values
+`dict_domain2imgroot`: a python dictionary with keys as user specified domain names and values
 as the absolute path to each domain's data.
 
-taskna: user defined task name
+`taskna`: user defined task name

From 79a2524560f8a654ff4032dc992d35f4b7183027 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 7 May 2024 16:39:28 +0200
Subject: [PATCH 059/273] .

---
 domainlab/algos/trainers/a_trainer.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 9bc126705..d9bda1513 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -127,7 +127,9 @@ def init_business(self, model, task, observer, device, aconf, flag_accept=True):
             self._decoratee.init_business(
                 model, task, observer, device, aconf, flag_accept
             )
-        self.model = model
+            self.model = self._decoratee
+        else:
+            self.model = model
         self.task = task
         self.task.init_business(trainer=self, args=aconf)
         self.model.list_d_tr = self.task.list_domain_tr

From 160a998dad0d79cdad4483b5cc1785ef68623c3f Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 7 May 2024 16:57:05 +0200
Subject: [PATCH 060/273] init

---
 domainlab/algos/trainers/train_irm.py | 36 +++++++++++++++++++++++++++
 1 file changed, 36 insertions(+)
 create mode 100644 domainlab/algos/trainers/train_irm.py

diff --git a/domainlab/algos/trainers/train_irm.py b/domainlab/algos/trainers/train_irm.py
new file mode 100644
index 000000000..abfff426b
--- /dev/null
+++ b/domainlab/algos/trainers/train_irm.py
@@ -0,0 +1,36 @@
+"""
+use random start to generate adversarial images
+"""
+import torch
+from torch import nn
+from torch.nn import functional as F
+import torch.autograd as autograd
+from domainlab.algos.trainers.train_basic import TrainerBasic
+
+
+class TrainerIRM(TrainerBasic):
+    """
+    The goal is to minimize the variance of the domain-level variance of the gradients.
+    This aligns the domain-level loss landscapes locally around the final weights, reducing
+    inconsistencies across domains.
+
+    For more details, see: Alexandre Ramé, Corentin Dancette, and Matthieu Cord.
+        "Fishr: Invariant gradient variances for out-of-distribution generalization."
+        International Conference on Machine Learning. PMLR, 2022.
+    """
+    def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
+        """
+        Let trainer behave like a model, so that other trainer could use it
+        """
+        _ = tensor_d
+        _ = others
+        y = tensor_y
+        logits = self.model.cal_logit_y(tensor_x)
+        device = "cuda" if logits[0][0].is_cuda else "cpu"
+        scale = torch.tensor(1.).to(device).requires_grad_()
+        loss_1 = F.cross_entropy(logits[::2] * scale, y[::2])
+        loss_2 = F.cross_entropy(logits[1::2] * scale, y[1::2])
+        grad_1 = autograd.grad(loss_1, [scale], create_graph=True)[0]
+        grad_2 = autograd.grad(loss_2, [scale], create_graph=True)[0]
+        loss_irm = torch.sum(grad_1 * grad_2)
+        return [loss_irm], [self.aconf.gamma_reg]

From fe2a91916a142021b4c839f18218a0300643102c Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 7 May 2024 16:58:42 +0200
Subject: [PATCH 061/273] .

---
 test_irm.sh | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 test_irm.sh

diff --git a/test_irm.sh b/test_irm.sh
new file mode 100644
index 000000000..72ed9bec1
--- /dev/null
+++ b/test_irm.sh
@@ -0,0 +1 @@
+python main_out.py --te_d=0 --task=mnistcolor10 --keep_model --model=erm --trainer=irm --nname=conv_bn_pool_2

From a4407a5f903bee2dab66230b4b2ad37356532cdd Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 7 May 2024 16:59:39 +0200
Subject: [PATCH 062/273] .

---
 domainlab/algos/trainers/zoo_trainer.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/domainlab/algos/trainers/zoo_trainer.py b/domainlab/algos/trainers/zoo_trainer.py
index 1cfa15a7f..1800e307c 100644
--- a/domainlab/algos/trainers/zoo_trainer.py
+++ b/domainlab/algos/trainers/zoo_trainer.py
@@ -7,6 +7,7 @@
 from domainlab.algos.trainers.train_matchdg import TrainerMatchDG
 from domainlab.algos.trainers.train_mldg import TrainerMLDG
 from domainlab.algos.trainers.train_fishr import TrainerFishr
+from domainlab.algos.trainers.train_irm import TrainerIRM
 
 
 class TrainerChainNodeGetter(object):
@@ -49,6 +50,7 @@ def __call__(self, lst_candidates=None, default=None, lst_excludes=None):
         chain = TrainerMatchDG(chain)
         chain = TrainerMLDG(chain)
         chain = TrainerFishr(chain)
+        chain = TrainerIRM(chain)
         chain = TrainerHyperScheduler(chain)
         node = chain.handle(self.request)
         head = node

From ab5f3993c717cecf53b8baaeae8ee4ad6d041198 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 8 May 2024 09:04:27 +0200
Subject: [PATCH 063/273] ver 0.6.3

---
 pyproject.toml | 2 +-
 setup.py       | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index ad1bbb2cd..629aa6fac 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "domainlab"
-version = "0.6.1"
+version = "0.6.3"
 readme = "README.md"
 repository = "https://github.com/marrlab/DomainLab"
 homepage = "https://marrlab.github.io/DomainLab/"
diff --git a/setup.py b/setup.py
index 3d80b71c9..e185f6377 100644
--- a/setup.py
+++ b/setup.py
@@ -38,7 +38,7 @@ def copy_dir(dir_path="zdata"):
     package_data={
         "zdata": [f for f in copy_dir()],
     },
-    version="0.6.1",
+    version="0.6.3",
     description="Library of modular domain generalization for deep learning",
     url="https://github.com/marrlab/DomainLab",
     author="Xudong Sun, et.al.",

From 75db7ad3ab60dffd578ee4f53bfb5da7007adce6 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Wed, 8 May 2024 14:46:22 +0200
Subject: [PATCH 064/273] Update doc_benchmark.md

---
 docs/doc_benchmark.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/doc_benchmark.md b/docs/doc_benchmark.md
index 082b14632..df1d748f2 100644
--- a/docs/doc_benchmark.md
+++ b/docs/doc_benchmark.md
@@ -36,11 +36,11 @@ example.
 
 ## Running a benchmark
 For the execution of a benchmark we provide two scripts in our repository:
-- local version for running the benchmark on a standalone machine:
+- running the benchmark on a standalone machine (computation node):
 [run_benchmark_standalone.sh](https://github.com/marrlab/DomainLab/blob/master/run_benchmark_standalone.sh)
-- cluster version for running the benchmark on a slurm cluster: [run_benchmark_slurm.sh](https://github.com/marrlab/DomainLab/blob/master/run_benchmark_slurm.sh)
+- launching the benchmark on the login node of a slurm cluster (benchmark will be dispatched to computation node via DomainLab scripts): [run_benchmark_slurm.sh](https://github.com/marrlab/DomainLab/blob/master/run_benchmark_slurm.sh)
 
-### Benchmark on a standalone machine (with or without GPU)
+### Benchmark on a standalone machine/computation node (with or without GPU)
 To run the benchmark with a specific configuration on a standalone machine, inside the DomainLab
 folder, one can execute (we assume you have a machine with 4 cores or more)
 ```shell

From b351b54d4378621d00a4779793863598157b7736 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 10 May 2024 13:38:01 +0200
Subject: [PATCH 065/273] strip rear slash in benchmark folder name

---
 domainlab/exp_protocol/aggregate_results.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/domainlab/exp_protocol/aggregate_results.py b/domainlab/exp_protocol/aggregate_results.py
index d67cf5a0a..2d72316bb 100644
--- a/domainlab/exp_protocol/aggregate_results.py
+++ b/domainlab/exp_protocol/aggregate_results.py
@@ -43,6 +43,7 @@ def agg_from_directory(input_dir: str, output_file: str):
 
 def agg_main(bm_dir: str, skip_plotting: bool = False):
     """Aggregates partial results and generate plots."""
+    bm_dir.rstrip("/")
     agg_output = f"{bm_dir}/results.csv"
     agg_input = f"{bm_dir}/rule_results"
     agg_from_directory(agg_input, agg_output)

From 2b3573de4db496436491ed2661f26210f43f248a Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 10 May 2024 13:51:01 +0200
Subject: [PATCH 066/273] added new benchmark for pacs, dial, fopt, erm

---
 examples/benchmark/pacs_fbopt_dial_erm.yaml | 68 +++++++++++++++++++++
 1 file changed, 68 insertions(+)
 create mode 100644 examples/benchmark/pacs_fbopt_dial_erm.yaml

diff --git a/examples/benchmark/pacs_fbopt_dial_erm.yaml b/examples/benchmark/pacs_fbopt_dial_erm.yaml
new file mode 100644
index 000000000..784f2e7be
--- /dev/null
+++ b/examples/benchmark/pacs_fbopt_dial_erm.yaml
@@ -0,0 +1,68 @@
+mode: grid
+
+output_dir: zoutput/benchmarks/benchmark_fbopt_pacs
+
+sampling_seed: 0
+startseed: 0
+endseed: 2
+
+test_domains:
+  - sketch
+
+domainlab_args:
+  tpath: examples/tasks/task_pacs_path_list.py
+  dmem: False
+  lr: 5e-5
+  epos: 1
+  es: 5
+  bs: 64
+  san_check: True
+  npath: examples/nets/resnet50domainbed.py
+  npath_encoder_x2topic_h: examples/nets/resnet50domainbed.py
+  npath_encoder_sandwich_x2h4zd: examples/nets/resnet50domainbed.py
+  exp_shoulder_clip: 10
+  mu_clip: 10_000
+  coeff_ma: 0.5
+  no_tensorboard: False
+
+
+
+Shared params:
+  ini_setpoint_ratio:
+    min: 0.5
+    max: 0.99
+    num: 2
+    step: 0.05
+    distribution: uniform
+
+  k_i_gain:
+    min: 0.0001
+    max: 0.01
+    num: 2
+    step: 0.0001
+    distribution: uniform
+  
+  dial_lr: 
+    min: 1e-5
+    max: 1e-3
+    num: 2
+    step: 1e-5
+    distribution: uniform
+
+  dial_epsilon: 
+    min: 1e-5
+    max: 1e-3
+    num: 2
+    step: 1e-5
+    distribution: uniform
+
+# Test fbopt with different hyperparameter configurations
+
+dann_fbopt:
+  model: erm
+  trainer: fbopt_dial
+  shared:
+    - ini_setpoint_ratio
+    - k_i_gain
+    - dial_lr 
+    - dial_epsilon

From f17e540959ad1ede393a618de6211587a38adb99 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 10 May 2024 14:12:15 +0200
Subject: [PATCH 067/273] updated benchmark

---
 examples/benchmark/pacs_fbopt_dial_erm.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/benchmark/pacs_fbopt_dial_erm.yaml b/examples/benchmark/pacs_fbopt_dial_erm.yaml
index 784f2e7be..eb8b64e1b 100644
--- a/examples/benchmark/pacs_fbopt_dial_erm.yaml
+++ b/examples/benchmark/pacs_fbopt_dial_erm.yaml
@@ -58,7 +58,7 @@ Shared params:
 
 # Test fbopt with different hyperparameter configurations
 
-dann_fbopt:
+dial_fbopt:
   model: erm
   trainer: fbopt_dial
   shared:

From 2bf91a83073fa21efe2bcb8de99e1bd69358bc98 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 10 May 2024 14:45:16 +0200
Subject: [PATCH 068/273] using diva instead of erm as it has hyper init

---
 ..._dial_erm.yaml => pacs_fbopt_dial_diva.yaml} | 17 ++++++++++++++++-
 1 file changed, 16 insertions(+), 1 deletion(-)
 rename examples/benchmark/{pacs_fbopt_dial_erm.yaml => pacs_fbopt_dial_diva.yaml} (84%)

diff --git a/examples/benchmark/pacs_fbopt_dial_erm.yaml b/examples/benchmark/pacs_fbopt_dial_diva.yaml
similarity index 84%
rename from examples/benchmark/pacs_fbopt_dial_erm.yaml
rename to examples/benchmark/pacs_fbopt_dial_diva.yaml
index eb8b64e1b..84c0fa60d 100644
--- a/examples/benchmark/pacs_fbopt_dial_erm.yaml
+++ b/examples/benchmark/pacs_fbopt_dial_diva.yaml
@@ -56,10 +56,25 @@ Shared params:
     step: 1e-5
     distribution: uniform
 
+  gamma_y:
+    min: 1.0
+    max: 1e6
+    step: 100
+    num: 3
+    distribution: loguniform
+
+  gamma_d:
+    min: 1.0
+    max: 1e6
+    step: 100
+    num: 3
+    distribution: loguniform
+
+
 # Test fbopt with different hyperparameter configurations
 
 dial_fbopt:
-  model: erm
+  model: diva
   trainer: fbopt_dial
   shared:
     - ini_setpoint_ratio

From 61659c083410453bf7d9db86a4312060df237549 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Fri, 10 May 2024 15:02:18 +0200
Subject: [PATCH 069/273] Update ci.yml

---
 .github/workflows/ci.yml | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index fee343308..e3cd32e01 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -46,4 +46,9 @@ jobs:
     - name: test if examples in markdown works
       run: bash -x -v ci_run_examples.sh
     - name: test if benchmark works
-      run: pip install snakemake==7.32.0 && pip install pulp==2.7.0 && sed -i '1s/^/#!\/bin\/bash -x -v\n/' run_benchmark_standalone.sh && bash -x -v run_benchmark_standalone.sh examples/benchmark/demo_shared_hyper_grid.yaml && cat zoutput/benchmarks/mnist_benchmark_grid/hyperparameters.csv && cat zoutput/benchmarks/mnist_benchmark_grid/results.csv
+      run: | 
+          pip install snakemake==7.32.0 && pip install pulp==2.7.0
+          sed -i '1s/^/#!\/bin\/bash -x -v\n/' run_benchmark_standalone.sh
+          bash -x -v run_benchmark_standalone.sh examples/benchmark/demo_shared_hyper_grid.yaml
+          cat zoutput/benchmarks/mnist_benchmark_grid/hyperparameters.csv
+          cat zoutput/benchmarks/mnist_benchmark_grid/results.csv

From 3b3d7e41657923efe758afa67cd5704a8394d3f1 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 10 May 2024 15:09:22 +0200
Subject: [PATCH 070/273] only plot col 9-17 instead to the end which is not
 numerical column

---
 domainlab/utils/generate_benchmark_plots.py | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/domainlab/utils/generate_benchmark_plots.py b/domainlab/utils/generate_benchmark_plots.py
index 9125ec7b8..420bcd76c 100644
--- a/domainlab/utils/generate_benchmark_plots.py
+++ b/domainlab/utils/generate_benchmark_plots.py
@@ -15,13 +15,16 @@
 matplotlib.use("Agg")
 
 # header of the csv file:
-# param_index, task, algo, epos, te_d, seed, params, acc, precision, recall, specificity, f1, auroc
+# 0,              1,       2,      3,    4,    5,    6,    7,      8,   9,        10,     11,          12, 13,    14,         15,      17,                    18,                  19
+# param_index, method, mname, commit, algo, epos, te_d, seed, params, acc, precision, recall, specificity, f1, auroc, acc_oracle, acc_val, model_selection_epoch, experiment_duration
+
 
 COLNAME_METHOD = "method"
 COLNAME_IDX_PARAM = "param_index"
 COLNAME_PARAM = "params"
 G_DF_TASK_COL = 1  # column in which the method name is saved
 G_DF_PLOT_COL_METRIC_START = 9  # first 0-6 columns are not metric
+G_DF_PLOT_COL_METRIC_END = 17  # first 0-6 columns are not metric
 
 
 def gen_benchmark_plots(
@@ -87,8 +90,7 @@ def gen_plots(dataframe: pd.DataFrame, output_dir: str, use_param_index: bool):
     ['param_index','task',' algo',' epos',' te_d',' seed',' params',' acc','precision',...]
     """
     os.makedirs(output_dir, exist_ok=True)
-    obj = dataframe.columns[G_DF_PLOT_COL_METRIC_START:]
-
+    obj = dataframe.columns[G_DF_PLOT_COL_METRIC_START:G_DF_PLOT_COL_METRIC_END]
     # boxplots
     for objective in obj:
         boxplot(
@@ -265,7 +267,7 @@ def scatterplot_matrix(
         but also between the parameter setups
     """
     dataframe = dataframe_in.copy()
-    index = list(range(G_DF_PLOT_COL_METRIC_START, dataframe.shape[1]))
+    index = list(range(G_DF_PLOT_COL_METRIC_START, G_DF_PLOT_COL_METRIC_END))
     if distinguish_param_setups:
         dataframe_ = dataframe.iloc[:, index]
         dataframe_.insert(
@@ -278,7 +280,7 @@ def scatterplot_matrix(
 
         g_p = sns.pairplot(data=dataframe_, hue="label", corner=True, kind=kind)
     else:
-        index_ = list(range(G_DF_PLOT_COL_METRIC_START, dataframe.shape[1]))
+        index_ = list(range(G_DF_PLOT_COL_METRIC_START, G_DF_PLOT_COL_METRIC_END))
         index_.insert(0, G_DF_TASK_COL)
         dataframe_ = dataframe.iloc[:, index_]
 
@@ -415,7 +417,7 @@ def radar_plot(dataframe_in, file=None, distinguish_hyperparam=True):
     else:
         dataframe.insert(0, "label", dataframe[COLNAME_METHOD])
     # we need "G_DF_PLOT_COL_METRIC_START + 1" as we did insert the columns 'label' at index 0
-    index = list(range(G_DF_PLOT_COL_METRIC_START + 1, dataframe.shape[1]))
+    index = list(range(G_DF_PLOT_COL_METRIC_START + 1, G_DF_PLOT_COL_METRIC_END))
     num_lines = len(dataframe["label"].unique())
     _, axis = plt.subplots(
         figsize=(9, 9 + (0.28 * num_lines)), subplot_kw=dict(polar=True)

From 71b9d26377a38005041de60a85a11480d857931f Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Fri, 10 May 2024 15:14:36 +0200
Subject: [PATCH 071/273] updated benchmark yaml

---
 examples/benchmark/pacs_fbopt_dial_diva.yaml | 22 +++++++++++---------
 1 file changed, 12 insertions(+), 10 deletions(-)

diff --git a/examples/benchmark/pacs_fbopt_dial_diva.yaml b/examples/benchmark/pacs_fbopt_dial_diva.yaml
index 84c0fa60d..9b8f493fa 100644
--- a/examples/benchmark/pacs_fbopt_dial_diva.yaml
+++ b/examples/benchmark/pacs_fbopt_dial_diva.yaml
@@ -10,20 +10,20 @@ test_domains:
   - sketch
 
 domainlab_args:
-  tpath: examples/tasks/task_pacs_path_list.py
+  tpath: examples/tasks/task_pacs_aug.py
   dmem: False
   lr: 5e-5
-  epos: 1
+  epos: 500
+  epos_min: 200
   es: 5
-  bs: 64
-  san_check: True
+  bs: 32
+  san_check: False
   npath: examples/nets/resnet50domainbed.py
-  npath_encoder_x2topic_h: examples/nets/resnet50domainbed.py
-  npath_encoder_sandwich_x2h4zd: examples/nets/resnet50domainbed.py
-  exp_shoulder_clip: 10
-  mu_clip: 10_000
-  coeff_ma: 0.5
-  no_tensorboard: False
+  npath_dom: examples/nets/resnet50domainbed.py
+  zx_dim: 0
+  zy_dim: 64
+  zd_dim: 64
+
 
 
 
@@ -81,3 +81,5 @@ dial_fbopt:
     - k_i_gain
     - dial_lr 
     - dial_epsilon
+    - gamma_y
+    - gamma_d

From cf2d3b2ade202a76ecf234a369f61c8e6095f093 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 10 May 2024 15:16:35 +0200
Subject: [PATCH 072/273] update doc for benchmark

---
 docs/doc_benchmark.md | 11 +++++------
 1 file changed, 5 insertions(+), 6 deletions(-)

diff --git a/docs/doc_benchmark.md b/docs/doc_benchmark.md
index df1d748f2..41b19bffb 100644
--- a/docs/doc_benchmark.md
+++ b/docs/doc_benchmark.md
@@ -138,8 +138,8 @@ the following after cd into the DomainLab directory:
 ```commandline
 python main_out.py --agg_partial_bm OUTPUT_DIR
 ```
-specifying the benchmark output directory containing the partially completed benchmark,
-e.g. `./zoutput/benchmarks/demo_benchmark`, where `demo_benchmark` is a name defined in the yaml file.
+where `OUTPUT_DIR` specifying the benchmark output directory containing the partially completed benchmark,
+e.g. `./zoutput/benchmarks/demo_benchmark`, where `demo_benchmark` is a name defined in the benchmark yaml file.
 
 Alternatively, one could use
 ```examples
@@ -155,10 +155,9 @@ Here for, the user must cd into the DomainLab directory and run
 ```commandline
 python main_out.py --gen_plots CSV_FILE --outp_dir OUTPUT_DIR
 ```
-
-specifying the path of the csv file of the aggregated results (e.g. `./zoutput/benchmarks/demo_benchmark/results.csv`)
-and the output directory of the partially completed benchmark (e.g. `./zoutput/benchmarks/demo_benchmark`).
-Note that the cvs file must have the same form as the one generated by the fully executed benchmark, i.e.
+where `CSV_FILE` specifies the path of the csv file of the aggregated results (e.g. `./zoutput/benchmarks/demo_benchmark/results.csv`)
+and `OUTPUT_DIR` specifies the output directory of the partially completed benchmark (e.g. `./zoutput/benchmarks/demo_benchmark`).
+Note that the cvs file must have the same form as the one generated by the fully executed benchmark, e.g.
 
 
 

From 3e35e5df1fb65c9d51358850904e94ae663f2942 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 10 May 2024 16:13:10 +0200
Subject: [PATCH 073/273] fix bug in numerical column index for benchmark plot

---
 domainlab/utils/generate_benchmark_plots.py | 12 ++++++++----
 1 file changed, 8 insertions(+), 4 deletions(-)

diff --git a/domainlab/utils/generate_benchmark_plots.py b/domainlab/utils/generate_benchmark_plots.py
index 420bcd76c..9c0be5fae 100644
--- a/domainlab/utils/generate_benchmark_plots.py
+++ b/domainlab/utils/generate_benchmark_plots.py
@@ -90,7 +90,8 @@ def gen_plots(dataframe: pd.DataFrame, output_dir: str, use_param_index: bool):
     ['param_index','task',' algo',' epos',' te_d',' seed',' params',' acc','precision',...]
     """
     os.makedirs(output_dir, exist_ok=True)
-    obj = dataframe.columns[G_DF_PLOT_COL_METRIC_START:G_DF_PLOT_COL_METRIC_END]
+    pos_numeric_end = min(G_DF_PLOT_COL_METRIC_END, dataframe.shape[1])
+    obj = dataframe.columns[G_DF_PLOT_COL_METRIC_START:pos_numeric_end]
     # boxplots
     for objective in obj:
         boxplot(
@@ -267,7 +268,8 @@ def scatterplot_matrix(
         but also between the parameter setups
     """
     dataframe = dataframe_in.copy()
-    index = list(range(G_DF_PLOT_COL_METRIC_START, G_DF_PLOT_COL_METRIC_END))
+    pos_numeric_end = min(G_DF_PLOT_COL_METRIC_END, dataframe.shape[1])
+    index = list(range(G_DF_PLOT_COL_METRIC_START, pos_numeric_end))
     if distinguish_param_setups:
         dataframe_ = dataframe.iloc[:, index]
         dataframe_.insert(
@@ -280,7 +282,8 @@ def scatterplot_matrix(
 
         g_p = sns.pairplot(data=dataframe_, hue="label", corner=True, kind=kind)
     else:
-        index_ = list(range(G_DF_PLOT_COL_METRIC_START, G_DF_PLOT_COL_METRIC_END))
+        pos_numeric_end = min(G_DF_PLOT_COL_METRIC_END, dataframe.shape[1])
+        index_ = list(range(G_DF_PLOT_COL_METRIC_START, pos_numeric_end))
         index_.insert(0, G_DF_TASK_COL)
         dataframe_ = dataframe.iloc[:, index_]
 
@@ -417,7 +420,8 @@ def radar_plot(dataframe_in, file=None, distinguish_hyperparam=True):
     else:
         dataframe.insert(0, "label", dataframe[COLNAME_METHOD])
     # we need "G_DF_PLOT_COL_METRIC_START + 1" as we did insert the columns 'label' at index 0
-    index = list(range(G_DF_PLOT_COL_METRIC_START + 1, G_DF_PLOT_COL_METRIC_END))
+    pos_numeric_end = min(G_DF_PLOT_COL_METRIC_END, dataframe.shape[1])
+    index = list(range(G_DF_PLOT_COL_METRIC_START + 1, pos_numeric_end))
     num_lines = len(dataframe["label"].unique())
     _, axis = plt.subplots(
         figsize=(9, 9 + (0.28 * num_lines)), subplot_kw=dict(polar=True)

From b463852fa1dc15ca42dc1730a04cc4f6e3051459 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sun, 12 May 2024 09:35:00 +0200
Subject: [PATCH 074/273] mv scripts to subfolder, fix issue # 803

---
 .github/workflows/ci.yml                         | 3 ++-
 ci.sh => scripts/ci.sh                           | 0
 ci_benchmark.sh => scripts/ci_benchmark.sh       | 0
 ci_pytest_cov.sh => scripts/ci_pytest_cov.sh     | 0
 ci_run_examples.sh => scripts/ci_run_examples.sh | 0
 clean.sh => scripts/clean.sh                     | 0
 gen_doc.sh => scripts/gen_doc.sh                 | 0
 sh_publish.sh => scripts/sh_publish.sh           | 0
 8 files changed, 2 insertions(+), 1 deletion(-)
 rename ci.sh => scripts/ci.sh (100%)
 rename ci_benchmark.sh => scripts/ci_benchmark.sh (100%)
 rename ci_pytest_cov.sh => scripts/ci_pytest_cov.sh (100%)
 rename ci_run_examples.sh => scripts/ci_run_examples.sh (100%)
 rename clean.sh => scripts/clean.sh (100%)
 rename gen_doc.sh => scripts/gen_doc.sh (100%)
 rename sh_publish.sh => scripts/sh_publish.sh (100%)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index e3cd32e01..f0d7fd8ef 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -44,10 +44,11 @@ jobs:
     - name: check if readme yaml works
       run: rm -r zoutput && python main_out.py -c ./examples/conf/vlcs_diva_mldg_dial.yaml
     - name: test if examples in markdown works
-      run: bash -x -v ci_run_examples.sh
+      run: bash -x -v scripts/ci_run_examples.sh
     - name: test if benchmark works
       run: | 
           pip install snakemake==7.32.0 && pip install pulp==2.7.0
+          echo "insert a shebang line (#!/bin/bash -x -v) at the beginning of the bash script"
           sed -i '1s/^/#!\/bin\/bash -x -v\n/' run_benchmark_standalone.sh
           bash -x -v run_benchmark_standalone.sh examples/benchmark/demo_shared_hyper_grid.yaml
           cat zoutput/benchmarks/mnist_benchmark_grid/hyperparameters.csv
diff --git a/ci.sh b/scripts/ci.sh
similarity index 100%
rename from ci.sh
rename to scripts/ci.sh
diff --git a/ci_benchmark.sh b/scripts/ci_benchmark.sh
similarity index 100%
rename from ci_benchmark.sh
rename to scripts/ci_benchmark.sh
diff --git a/ci_pytest_cov.sh b/scripts/ci_pytest_cov.sh
similarity index 100%
rename from ci_pytest_cov.sh
rename to scripts/ci_pytest_cov.sh
diff --git a/ci_run_examples.sh b/scripts/ci_run_examples.sh
similarity index 100%
rename from ci_run_examples.sh
rename to scripts/ci_run_examples.sh
diff --git a/clean.sh b/scripts/clean.sh
similarity index 100%
rename from clean.sh
rename to scripts/clean.sh
diff --git a/gen_doc.sh b/scripts/gen_doc.sh
similarity index 100%
rename from gen_doc.sh
rename to scripts/gen_doc.sh
diff --git a/sh_publish.sh b/scripts/sh_publish.sh
similarity index 100%
rename from sh_publish.sh
rename to scripts/sh_publish.sh

From 06152ae07c7d7d99d7ddf8cf3924297725177054 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sun, 12 May 2024 09:35:37 +0200
Subject: [PATCH 075/273] 0.6.4, fix benchmark bug

---
 pyproject.toml | 2 +-
 setup.py       | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 629aa6fac..2f44de78a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "domainlab"
-version = "0.6.3"
+version = "0.6.4"
 readme = "README.md"
 repository = "https://github.com/marrlab/DomainLab"
 homepage = "https://marrlab.github.io/DomainLab/"
diff --git a/setup.py b/setup.py
index e185f6377..c56a64115 100644
--- a/setup.py
+++ b/setup.py
@@ -38,7 +38,7 @@ def copy_dir(dir_path="zdata"):
     package_data={
         "zdata": [f for f in copy_dir()],
     },
-    version="0.6.3",
+    version="0.6.4",
     description="Library of modular domain generalization for deep learning",
     url="https://github.com/marrlab/DomainLab",
     author="Xudong Sun, et.al.",

From 2a12d9eb801f9a4987eb74ddbe46a03662747cd3 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Mon, 13 May 2024 10:34:32 +0200
Subject: [PATCH 076/273] use domain wise batch, add test

---
 domainlab/algos/trainers/train_irm.py | 66 ++++++++++++++++++++-------
 tests/test_irm.py                     | 13 ++++++
 2 files changed, 63 insertions(+), 16 deletions(-)
 create mode 100644 tests/test_irm.py

diff --git a/domainlab/algos/trainers/train_irm.py b/domainlab/algos/trainers/train_irm.py
index abfff426b..0da2d0bde 100644
--- a/domainlab/algos/trainers/train_irm.py
+++ b/domainlab/algos/trainers/train_irm.py
@@ -2,22 +2,57 @@
 use random start to generate adversarial images
 """
 import torch
-from torch import nn
+from torch import autograd
 from torch.nn import functional as F
-import torch.autograd as autograd
 from domainlab.algos.trainers.train_basic import TrainerBasic
 
 
 class TrainerIRM(TrainerBasic):
     """
-    The goal is to minimize the variance of the domain-level variance of the gradients.
-    This aligns the domain-level loss landscapes locally around the final weights, reducing
-    inconsistencies across domains.
-
-    For more details, see: Alexandre Ramé, Corentin Dancette, and Matthieu Cord.
-        "Fishr: Invariant gradient variances for out-of-distribution generalization."
-        International Conference on Machine Learning. PMLR, 2022.
+    IRMv1 split a minibatch into half, and use an unbiased estimate of the
+    squared gradient norm via inner product
+    $$\\delta_{w|w=1} \\ell(w\\dot \\Phi(X^{e, i}), Y^{e, i})$$
+    of dimension dim(Grad)
+    with
+    $$\\delta_{w|w=1} \\ell(w\\dot \\Phi(X^{e, j}), Y^{e, j})$$
+    of dimension dim(Grad)
+    For more details, see section 3.2 and Appendix D of :
+    Arjovsky et al., “Invariant Risk Minimization.”
     """
+    def tr_epoch(self, epoch):
+        list_loaders = list(self.dict_loader_tr.values())
+        loaders_zip = zip(*list_loaders)
+        self.model.train()
+        self.epo_loss_tr = 0
+
+        for ind_batch, tuple_data_domains_batch in enumerate(loaders_zip):
+            self.optimizer.zero_grad()
+            list_domain_loss_erm = []
+            list_domain_reg = []
+            for batch_domain_e in tuple_data_domains_batch:
+                tensor_x, tensor_y, tensor_d, *others = batch_domain_e
+                tensor_x, tensor_y, tensor_d = \
+                    tensor_x.to(self.device), tensor_y.to(self.device), \
+                    tensor_d.to(self.device)
+                list_domain_loss_erm.append(
+                    self.model.cal_task_loss(tensor_x, tensor_y))
+                list_1ele_loss_irm, _ = \
+                    self._cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
+                list_domain_reg += list_1ele_loss_irm
+            loss = torch.sum(torch.stack(list_domain_loss_erm)) + \
+                self.aconf.gamma_reg * torch.sum(torch.stack(list_domain_reg))
+            loss.backward()
+            self.optimizer.step()
+            self.epo_loss_tr += loss.detach().item()
+            self.after_batch(epoch, ind_batch)
+
+        flag_stop = self.observer.update(epoch)  # notify observer
+        return flag_stop
+
+    def _cal_phi(self, tensor_x):
+        logits = self.model.cal_logit_y(tensor_x)
+        return logits
+
     def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         """
         Let trainer behave like a model, so that other trainer could use it
@@ -25,12 +60,11 @@ def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         _ = tensor_d
         _ = others
         y = tensor_y
-        logits = self.model.cal_logit_y(tensor_x)
-        device = "cuda" if logits[0][0].is_cuda else "cpu"
-        scale = torch.tensor(1.).to(device).requires_grad_()
-        loss_1 = F.cross_entropy(logits[::2] * scale, y[::2])
-        loss_2 = F.cross_entropy(logits[1::2] * scale, y[1::2])
-        grad_1 = autograd.grad(loss_1, [scale], create_graph=True)[0]
-        grad_2 = autograd.grad(loss_2, [scale], create_graph=True)[0]
+        phi = self._cal_phi(tensor_x)
+        dummy_w_scale = torch.tensor(1.).to(tensor_x.device).requires_grad_()
+        loss_1 = F.cross_entropy(phi[::2] * dummy_w_scale, y[::2])
+        loss_2 = F.cross_entropy(phi[1::2] * dummy_w_scale, y[1::2])
+        grad_1 = autograd.grad(loss_1, [dummy_w_scale], create_graph=True)[0]
+        grad_2 = autograd.grad(loss_2, [dummy_w_scale], create_graph=True)[0]
         loss_irm = torch.sum(grad_1 * grad_2)
         return [loss_irm], [self.aconf.gamma_reg]
diff --git a/tests/test_irm.py b/tests/test_irm.py
new file mode 100644
index 000000000..1015c4c62
--- /dev/null
+++ b/tests/test_irm.py
@@ -0,0 +1,13 @@
+"""
+unit and end-end test for deep all, mldg
+"""
+from tests.utils_test import utils_test_algo
+
+
+def test_deepall_mldg():
+    """
+    train DeepAll with MLDG
+    """
+    args = "--te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm \
+        --trainer=irm --nname=alexnet"
+    utils_test_algo(args)

From ef16d066889f5fd52b533882da7284518579156b Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Mon, 13 May 2024 10:48:31 +0200
Subject: [PATCH 077/273] fix codacy

---
 test_irm.sh       |  1 -
 tests/test_irm.py | 15 ++++++++++++---
 2 files changed, 12 insertions(+), 4 deletions(-)
 delete mode 100644 test_irm.sh

diff --git a/test_irm.sh b/test_irm.sh
deleted file mode 100644
index 72ed9bec1..000000000
--- a/test_irm.sh
+++ /dev/null
@@ -1 +0,0 @@
-python main_out.py --te_d=0 --task=mnistcolor10 --keep_model --model=erm --trainer=irm --nname=conv_bn_pool_2
diff --git a/tests/test_irm.py b/tests/test_irm.py
index 1015c4c62..5ed8b4ceb 100644
--- a/tests/test_irm.py
+++ b/tests/test_irm.py
@@ -1,13 +1,22 @@
 """
-unit and end-end test for deep all, mldg
+end-end test
 """
 from tests.utils_test import utils_test_algo
 
 
-def test_deepall_mldg():
+def test_irm():
     """
-    train DeepAll with MLDG
+    train with Invariant Risk Minimization
     """
     args = "--te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm \
         --trainer=irm --nname=alexnet"
     utils_test_algo(args)
+
+
+def test_irm_mnist():
+    """
+    train with Invariant Risk Minimization
+    """
+    args = "--te_d=0 --task=mnistcolor10 --keep_model --model=erm \
+        --trainer=irm --nname=conv_bn_pool_2"
+    utils_test_algo(args)

From 547c3a3f2bbfc8ccdbdf0f4726c2de728206e9fc Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Mon, 13 May 2024 13:46:40 +0200
Subject: [PATCH 078/273] add wildcard * to benchmarks results to represent
 date

---
 .github/workflows/ci.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index f0d7fd8ef..f1a4fa9b6 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -51,5 +51,5 @@ jobs:
           echo "insert a shebang line (#!/bin/bash -x -v) at the beginning of the bash script"
           sed -i '1s/^/#!\/bin\/bash -x -v\n/' run_benchmark_standalone.sh
           bash -x -v run_benchmark_standalone.sh examples/benchmark/demo_shared_hyper_grid.yaml
-          cat zoutput/benchmarks/mnist_benchmark_grid/hyperparameters.csv
-          cat zoutput/benchmarks/mnist_benchmark_grid/results.csv
+          cat zoutput/benchmarks/mnist_benchmark_grid*/hyperparameters.csv
+          cat zoutput/benchmarks/mnist_benchmark_grid*/results.csv

From 2d275a4c8ef085353b00660483d9d78b8b43a23e Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Mon, 13 May 2024 16:43:38 +0200
Subject: [PATCH 079/273] renamed the update method to conform with naming
 convention for early stopping prevention

---
 domainlab/algos/msels/c_msel_setpoint_delay.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/domainlab/algos/msels/c_msel_setpoint_delay.py b/domainlab/algos/msels/c_msel_setpoint_delay.py
index a9c8933ea..d62983e89 100644
--- a/domainlab/algos/msels/c_msel_setpoint_delay.py
+++ b/domainlab/algos/msels/c_msel_setpoint_delay.py
@@ -24,7 +24,7 @@ def oracle_last_setpoint_sel_te_acc(self):
         """
         return self._oracle_last_setpoint_sel_te_acc
 
-    def update(self, clear_counter=False):
+    def base_update(self, clear_counter=False):
         """
         if the best model should be updated
         currently, clear_counter is set via

From e4d87d930e4034d50f7dea7414082bb63c4da99b Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Mon, 13 May 2024 17:18:48 +0200
Subject: [PATCH 080/273] added hyper init and hyper update function and a new
 benchmark for fbopt, fishr and erm

---
 domainlab/models/model_erm.py                | 19 ++++++
 examples/benchmark/pacs_fbopt_fishr_erm.yaml | 68 ++++++++++++++++++++
 2 files changed, 87 insertions(+)
 create mode 100644 examples/benchmark/pacs_fbopt_fishr_erm.yaml

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index 6ee9c23f9..778001578 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -53,4 +53,23 @@ def convert4backpack(self):
             """
             self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
             self.net_classifier = extend(self.net_classifier,  use_converter=True)
+    
+        def hyper_update(self, epoch, fun_scheduler):
+            """hyper_update.
+
+            :param epoch:
+            :param fun_scheduler:
+            """
+            pass
+
+        def hyper_init(self, functor_scheduler, trainer=None):
+            """
+            initiate a scheduler object via class name and things inside this model
+
+            :param functor_scheduler: the class name of the scheduler
+            """
+            return functor_scheduler(
+                trainer=trainer
+            )
+
     return ModelERM
diff --git a/examples/benchmark/pacs_fbopt_fishr_erm.yaml b/examples/benchmark/pacs_fbopt_fishr_erm.yaml
new file mode 100644
index 000000000..6c26c516f
--- /dev/null
+++ b/examples/benchmark/pacs_fbopt_fishr_erm.yaml
@@ -0,0 +1,68 @@
+mode: grid
+
+output_dir: zoutput/benchmarks/benchmark_fbopt_fishr_erm_pacs
+
+sampling_seed: 0
+startseed: 0
+endseed: 2
+
+test_domains:
+  - sketch
+
+domainlab_args:
+  tpath: examples/tasks/task_pacs_aug.py
+  dmem: False
+  lr: 5e-5
+  epos: 500
+  epos_min: 200
+  es: 5
+  bs: 32
+  san_check: False
+  npath: examples/nets/resnet50domainbed.py
+  npath_dom: examples/nets/resnet50domainbed.py
+  zx_dim: 0
+  zy_dim: 64
+  zd_dim: 64
+
+
+
+
+Shared params:
+  ini_setpoint_ratio:
+    min: 0.5
+    max: 0.99
+    num: 2
+    step: 0.05
+    distribution: uniform
+
+  k_i_gain:
+    min: 0.0001
+    max: 0.01
+    num: 2
+    step: 0.0001
+    distribution: uniform
+
+  gamma_reg:
+    min: 0.01
+    max: 1e4
+    num: 3
+    distribution: loguniform
+
+
+# Test fbopt with different hyperparameter configurations
+
+fbopt_fishr_erm:
+  model: erm
+  trainer: fbopt_fishr
+  shared:
+    - ini_setpoint_ratio
+    - k_i_gain
+    - gamma_reg
+
+fishr_erm:
+  model: erm
+  trainer: fishr
+  shared:
+    - ini_setpoint_ratio
+    - k_i_gain
+    - gamma_reg
\ No newline at end of file

From 5c44550bab7ab0d90a719a1c5a4c3722632117ea Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 14 May 2024 08:42:42 +0200
Subject: [PATCH 081/273] Fixed import of backpack

---
 domainlab/models/a_model_classif.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/domainlab/models/a_model_classif.py b/domainlab/models/a_model_classif.py
index 1917f752e..3dd9831d0 100644
--- a/domainlab/models/a_model_classif.py
+++ b/domainlab/models/a_model_classif.py
@@ -20,11 +20,11 @@
 
 try:
     from backpack import extend
-except:
-    backpack = None
-
-loss_cross_entropy_extended = extend(nn.CrossEntropyLoss(reduction="none"))
-
+    loss_cross_entropy_extended = extend(nn.CrossEntropyLoss(reduction="none"))
+except ImportError:
+    # Handle the case where backpack is not available
+    loss_cross_entropy_extended = nn.CrossEntropyLoss(reduction="none")
+    print("Backpack could not be imported. Using standard nn.CrossEntropyLoss.")
 
 class AModelClassif(AModel, metaclass=abc.ABCMeta):
     """

From 416389fe38bc6915fba1c97964a30ad3267572c5 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 14 May 2024 08:55:56 +0200
Subject: [PATCH 082/273] Fixed benchmark import not successfull in erm

---
 domainlab/models/model_erm.py | 20 +++++++++++++-------
 1 file changed, 13 insertions(+), 7 deletions(-)

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index 778001578..5b8bb5cfb 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -7,8 +7,10 @@
 
 try:
     from backpack import extend
-except:
-    backpack = None
+except ImportError as e:
+    print(f"Failed to import 'extend' from backpack: {e}")
+    extend = None  # Ensure extend is defined to avoid NameError later in the code
+
 
 
 def mk_erm(parent_class=AModelClassif, **kwargs):
@@ -47,12 +49,16 @@ def __init__(self, net=None, net_feat=None):
             super().__init__(**kwargs)
             self._net_invar_feat = net_feat
 
-        def convert4backpack(self):
-            """
-            convert the module to backpack for 2nd order gradients
-            """
+    def convert4backpack(self):
+        """
+        Convert the module to backpack for 2nd order gradients
+        """
+        if extend is not None:
             self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
-            self.net_classifier = extend(self.net_classifier,  use_converter=True)
+            self.net_classifier = extend(self.net_classifier, use_converter=True)
+        else:
+            print("Backpack's extend function is not available.")
+
     
         def hyper_update(self, epoch, fun_scheduler):
             """hyper_update.

From d59d37ad1b634120553b9c721252fe67908f8da9 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 14 May 2024 08:59:21 +0200
Subject: [PATCH 083/273] fixed indentation

---
 domainlab/models/model_erm.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index 5b8bb5cfb..b4ec477a6 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -49,15 +49,15 @@ def __init__(self, net=None, net_feat=None):
             super().__init__(**kwargs)
             self._net_invar_feat = net_feat
 
-    def convert4backpack(self):
-        """
-        Convert the module to backpack for 2nd order gradients
-        """
-        if extend is not None:
-            self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
-            self.net_classifier = extend(self.net_classifier, use_converter=True)
-        else:
-            print("Backpack's extend function is not available.")
+        def convert4backpack(self):
+            """
+            Convert the module to backpack for 2nd order gradients
+            """
+            if extend is not None:
+                self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
+                self.net_classifier = extend(self.net_classifier, use_converter=True)
+            else:
+                print("Backpack's extend function is not available.")
 
     
         def hyper_update(self, epoch, fun_scheduler):

From a4fa31dd9d00697c1a8406a39d7b9996a52bc741 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 14 May 2024 09:04:21 +0200
Subject: [PATCH 084/273] Added backpack check for fishr

---
 domainlab/algos/trainers/train_fishr.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/train_fishr.py b/domainlab/algos/trainers/train_fishr.py
index 3580a0721..40a7bc50e 100644
--- a/domainlab/algos/trainers/train_fishr.py
+++ b/domainlab/algos/trainers/train_fishr.py
@@ -156,10 +156,15 @@ def cal_dict_variance_grads(self, tensor_x, vec_y):
         loss = self.model.cal_task_loss(tensor_x.clone(), vec_y)
         loss = loss.sum()
 
-        with backpack(Variance()):
+        if backpack is None:
             loss.backward(
                 inputs=list(self.model.parameters()), retain_graph=True, create_graph=True
             )
+        else:
+            with backpack(Variance()):
+                loss.backward(
+                    inputs=list(self.model.parameters()), retain_graph=True, create_graph=True
+                )
 
         for name, param in self.model.named_parameters():
             print(name)

From a38c777522e66cc8b7a446107c9b12192e43eb82 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 14 May 2024 09:24:39 +0200
Subject: [PATCH 085/273] Debugging backpack in erm

---
 domainlab/models/model_erm.py | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index b4ec477a6..b4ac550b6 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -50,15 +50,19 @@ def __init__(self, net=None, net_feat=None):
             self._net_invar_feat = net_feat
 
         def convert4backpack(self):
-            """
-            Convert the module to backpack for 2nd order gradients
-            """
+            print("Extending model components...")
             if extend is not None:
+                if hasattr(self._net_invar_feat, 'parameters'):
+                    print("Net features before extend:", self._net_invar_feat)
                 self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
+                
+                if hasattr(self.net_classifier, 'parameters'):
+                    print("Net classifier before extend:", self.net_classifier)
                 self.net_classifier = extend(self.net_classifier, use_converter=True)
             else:
                 print("Backpack's extend function is not available.")
 
+
     
         def hyper_update(self, epoch, fun_scheduler):
             """hyper_update.

From 870bc57a2064d99f8c5a88a95112450537535e7b Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 14 May 2024 10:16:55 +0200
Subject: [PATCH 086/273] Adding more logging to erm

---
 domainlab/models/model_erm.py | 11 ++++++++---
 1 file changed, 8 insertions(+), 3 deletions(-)

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index b4ac550b6..a253eaac1 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -4,6 +4,7 @@
 from domainlab.compos.nn_zoo.nn import LayerId
 from domainlab.models.a_model_classif import AModelClassif
 from domainlab.utils.override_interface import override_interface
+import traceback
 
 try:
     from backpack import extend
@@ -52,9 +53,13 @@ def __init__(self, net=None, net_feat=None):
         def convert4backpack(self):
             print("Extending model components...")
             if extend is not None:
-                if hasattr(self._net_invar_feat, 'parameters'):
-                    print("Net features before extend:", self._net_invar_feat)
-                self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
+                try:
+                    if hasattr(self._net_invar_feat, 'parameters'):
+                        print("Net features before extend:", self._net_invar_feat)
+                    self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
+                except Exception as e:
+                    print("An error occurred:", e)
+                    traceback.print_exc()
                 
                 if hasattr(self.net_classifier, 'parameters'):
                     print("Net classifier before extend:", self.net_classifier)

From d66de086e15a712e419278c28765f7abe3480d18 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 14 May 2024 11:00:51 +0200
Subject: [PATCH 087/273] irm benhcmakr

---
 examples/benchmark/pacs_fbopt_irm_erm.yaml | 66 ++++++++++++++++++++++
 1 file changed, 66 insertions(+)
 create mode 100644 examples/benchmark/pacs_fbopt_irm_erm.yaml

diff --git a/examples/benchmark/pacs_fbopt_irm_erm.yaml b/examples/benchmark/pacs_fbopt_irm_erm.yaml
new file mode 100644
index 000000000..70ab77707
--- /dev/null
+++ b/examples/benchmark/pacs_fbopt_irm_erm.yaml
@@ -0,0 +1,66 @@
+mode: grid
+
+output_dir: zoutput/benchmarks/benchmark_fbopt_fishr_erm_pacs
+
+sampling_seed: 0
+startseed: 0
+endseed: 2
+
+test_domains:
+  - sketch
+
+domainlab_args:
+  tpath: examples/tasks/task_pacs_aug.py
+  dmem: False
+  lr: 5e-5
+  epos: 500
+  epos_min: 200
+  es: 5
+  bs: 32
+  san_check: False
+  npath: examples/nets/resnet50domainbed.py
+  npath_dom: examples/nets/resnet50domainbed.py
+  zx_dim: 0
+  zy_dim: 64
+  zd_dim: 64
+
+
+
+
+Shared params:
+  ini_setpoint_ratio:
+    min: 0.5
+    max: 0.99
+    num: 2
+    step: 0.05
+    distribution: uniform
+
+  k_i_gain:
+    min: 0.0001
+    max: 0.01
+    num: 2
+    step: 0.0001
+    distribution: uniform
+
+  gamma_reg:
+    min: 0.01
+    max: 1e4
+    num: 3
+    distribution: loguniform
+
+
+# Test fbopt with different hyperparameter configurations
+
+fbopt_irm_erm:
+  model: erm
+  trainer: fbopt_irm
+  shared:
+    - ini_setpoint_ratio
+    - k_i_gain
+    - gamma_reg
+
+irm_erm:
+  model: erm
+  trainer: irm
+  shared:
+    - gamma_reg

From f7795a927c082e3a10ba8cb6aa79998298fe86fc Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Tue, 14 May 2024 11:49:51 +0200
Subject: [PATCH 088/273] added list_str_multiplier

---
 domainlab/models/model_erm.py | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index a253eaac1..d6ec3b35c 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -86,5 +86,12 @@ def hyper_init(self, functor_scheduler, trainer=None):
             return functor_scheduler(
                 trainer=trainer
             )
+        
+        @property
+        def list_str_multiplier_na(self):
+            """
+            list of multipliers which match the order in cal_reg_loss
+            """
+            return []
 
     return ModelERM

From 6c5ca27e91f7ca27db97aaed2802952c191789a3 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 14 May 2024 16:03:08 +0200
Subject: [PATCH 089/273] Added directories to gitignore, adjusted
 fobt_fishr_erm benchmark

---
 .gitignore                                   | 10 ++++++++--
 examples/benchmark/pacs_fbopt_fishr_erm.yaml |  8 +++-----
 2 files changed, 11 insertions(+), 7 deletions(-)

diff --git a/.gitignore b/.gitignore
index 2e1aa7a74..a351b31fe 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,7 +1,13 @@
 .ropeproject
-./zdpath
-./zoutput
+/zdpath
+/zoutput
 tests/__pycache__/
 *.pyc
 .vscode/
 domainlab/zdata/pacs
+/data/
+/.snakemake/
+/dist 
+/domainlab.egg-info
+/runs
+/slurm_errors.txt
\ No newline at end of file
diff --git a/examples/benchmark/pacs_fbopt_fishr_erm.yaml b/examples/benchmark/pacs_fbopt_fishr_erm.yaml
index 6c26c516f..721833e7b 100644
--- a/examples/benchmark/pacs_fbopt_fishr_erm.yaml
+++ b/examples/benchmark/pacs_fbopt_fishr_erm.yaml
@@ -18,8 +18,8 @@ domainlab_args:
   es: 5
   bs: 32
   san_check: False
-  npath: examples/nets/resnet50domainbed.py
-  npath_dom: examples/nets/resnet50domainbed.py
+  nname: alexnet
+  nname_dom: alexnet
   zx_dim: 0
   zy_dim: 64
   zd_dim: 64
@@ -63,6 +63,4 @@ fishr_erm:
   model: erm
   trainer: fishr
   shared:
-    - ini_setpoint_ratio
-    - k_i_gain
-    - gamma_reg
\ No newline at end of file
+    - gamma_reg

From 2e1fea4536a0fd1ab0f41a9f64b5859b644f0d12 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 14 May 2024 16:08:37 +0200
Subject: [PATCH 090/273] updated gitignore

---
 .gitignore | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/.gitignore b/.gitignore
index 2e1aa7a74..a351b31fe 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,7 +1,13 @@
 .ropeproject
-./zdpath
-./zoutput
+/zdpath
+/zoutput
 tests/__pycache__/
 *.pyc
 .vscode/
 domainlab/zdata/pacs
+/data/
+/.snakemake/
+/dist 
+/domainlab.egg-info
+/runs
+/slurm_errors.txt
\ No newline at end of file

From 6738c2cea5406813638ce8f9d28b781f7a14511a Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 14 May 2024 19:03:26 +0200
Subject: [PATCH 091/273] Changed batch size due to memory reasons and changed
 task naming

---
 examples/benchmark/pacs_fbopt_dial_diva.yaml | 13 +++++++++++--
 1 file changed, 11 insertions(+), 2 deletions(-)

diff --git a/examples/benchmark/pacs_fbopt_dial_diva.yaml b/examples/benchmark/pacs_fbopt_dial_diva.yaml
index 9b8f493fa..3ac91d67d 100644
--- a/examples/benchmark/pacs_fbopt_dial_diva.yaml
+++ b/examples/benchmark/pacs_fbopt_dial_diva.yaml
@@ -1,6 +1,6 @@
 mode: grid
 
-output_dir: zoutput/benchmarks/benchmark_fbopt_pacs
+output_dir: zoutput/benchmarks/benchmark_fbopt_dial_diva_pacs
 
 sampling_seed: 0
 startseed: 0
@@ -16,7 +16,7 @@ domainlab_args:
   epos: 500
   epos_min: 200
   es: 5
-  bs: 32
+  bs: 16
   san_check: False
   npath: examples/nets/resnet50domainbed.py
   npath_dom: examples/nets/resnet50domainbed.py
@@ -83,3 +83,12 @@ dial_fbopt:
     - dial_epsilon
     - gamma_y
     - gamma_d
+
+dial:
+  model: diva
+  trainer: dial
+  shared:
+    - dial_lr 
+    - dial_epsilon
+    - gamma_y
+    - gamma_d

From abebfd8112299da8e41785ac52bbf478cec65ed3 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Wed, 15 May 2024 18:04:25 +0200
Subject: [PATCH 092/273] Abstracted common functions from the script

---
 run_benchmark_slurm.sh                | 50 +++++++-----------
 run_benchmark_standalone.sh           | 75 ++++++++-------------------
 scripts/common_benchmark_functions.sh | 25 +++++++++
 3 files changed, 66 insertions(+), 84 deletions(-)
 create mode 100644 scripts/common_benchmark_functions.sh

diff --git a/run_benchmark_slurm.sh b/run_benchmark_slurm.sh
index 1d5ca419d..cdf889a87 100755
--- a/run_benchmark_slurm.sh
+++ b/run_benchmark_slurm.sh
@@ -1,44 +1,30 @@
 #!/bin/bash
 
-timestamp() {
-#  date +"%T" # current time
-  date +"%Y-%m-%d_%H-%M-%S"
-}
+# Source the common functions script
+source scripts/common_benchmark_functions.sh
 
 # CONFIGFILE="examples/yaml/test_helm_benchmark.yaml"
 CONFIGFILE=$1
-export DOMAINLAB_CUDA_START_SEED=$2
-
-if [ -z "$2" ]
-then
-      echo "argument 2: DOMAINLAB_CUDA_START_SEED empty, will set to 0"
-      export DOMAINLAB_CUDA_START_SEED=0
-      # in fact, the smk code will hash empty string to zero, see standalone script,
-      # but here we just want to ensure the seed is 0 without worrying a different
-      # behavior of the hash function
-else
-      export DOMAINLAB_CUDA_START_SEED=$2
-fi
-
-# Extract output_dir from the YAML configuration file
-output_dir=$(awk '/output_dir:/ {print $2}' "$CONFIGFILE")
-if [ -z "$output_dir" ]; then
-  echo "Error: output_dir not specified in $CONFIGFILE"
-  exit 1
-fi
-
-# Create a timestamped output directory
-results_dir="${output_dir}_$(timestamp)"
+logfile=$(create_log_file)
+echo "Configuration file: $CONFIGFILE"
+echo "verbose log: $logfile"
+
+# Configuring DOMAINLAB_CUDA_START_SEED
+DOMAINLAB_CUDA_START_SEED=${2:-0}
+export DOMAINLAB_CUDA_START_SEED
+echo "argument 2: DOMAINLAB_CUDA_START_SEED=$DOMAINLAB_CUDA_START_SEED"
 
 # ensure all runs sample the same hyperparameters
 export DOMAINLAB_CUDA_HYPERPARAM_SEED=0
 
 export NUMBER_GPUS=1
-logdir="zoutput/logs"
-mkdir -p $logdir
-logfile="$logdir/$(timestamp).out"
-echo "Configuration file: $CONFIGFILE"
-echo "starting seed is: $DOMAINLAB_CUDA_START_SEED"
-echo "verbose log: $logfile"
+
+results_dir=$(extract_output_dir "$CONFIGFILE")
+
+echo "Starting seed is: $DOMAINLAB_CUDA_START_SEED"
+echo "Hyperparameter seed is: $DOMAINLAB_CUDA_HYPERPARAM_SEED"
+echo "Number of GPUs: $NUMBER_GPUS"
+echo "Results will be stored in: $results_dir"
+
 # Helmholtz
 snakemake --profile "examples/yaml/slurm" --config yaml_file="$CONFIGFILE" --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index fffb953cb..e4b2c1efe 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -1,62 +1,35 @@
+#!/bin/bash
 set -e
 
-timestamp() {
-#  date +"%T" # current time
-  date +"%Y-%m-%d_%H-%M-%S"
-}
-
-
-logdir="zoutput/logs"
-mkdir -p $logdir
-logfile="$logdir/$(timestamp).out"
-echo "verbose log: $logfile"
-
+# Source the common functions script
+source scripts/common_benchmark_functions.sh
 
 CONFIGFILE=$1
+logfile=$(create_log_file)
+echo "Configuration file: $CONFIGFILE"
+echo "verbose log: $logfile"
 
+# Configuring DOMAINLAB_CUDA_START_SEED
+DOMAINLAB_CUDA_START_SEED=${2:-0}
+export DOMAINLAB_CUDA_START_SEED
+echo "argument 2: DOMAINLAB_CUDA_START_SEED=$DOMAINLAB_CUDA_START_SEED"
 
-
-echo "argument 2=$2"
-if [ -z "$2" ]
-then
-      echo "argument 2: DOMAINLAB_CUDA_START_SEED empty"
-      echo "empty string will be hashed into 0"
-fi
-
-export DOMAINLAB_CUDA_START_SEED=$2
-
-
-echo "argument 3: $3"
-
-if [ -z "$3" ]
-then
-      echo "argument 3: DOMAINLAB_CUDA_HYPERPARAM_SEED empty, will set to 0"
-      export DOMAINLAB_CUDA_HYPERPARAM_SEED=0
-else
-      export DOMAINLAB_CUDA_HYPERPARAM_SEED=$3
-fi
-
+# Configuring DOMAINLAB_CUDA_HYPERPARAM_SEED
+DOMAINLAB_CUDA_HYPERPARAM_SEED=${3:-0}
+export DOMAINLAB_CUDA_HYPERPARAM_SEED
+echo "argument 3: DOMAINLAB_CUDA_HYPERPARAM_SEED=$DOMAINLAB_CUDA_HYPERPARAM_SEED"
 
 echo "argument 4: NUMBER_GPUS=$4"
-if [ -z "$4" ]
-then
-      export NUMBER_GPUS=1
-      echo "argument 4: NUMBER_GPUS set to 1"
-      echo "argument 4: NUMBER_GPUS=$NUMBER_GPUS"
-else
-      export NUMBER_GPUS=$4
-fi
-
-# Extract output_dir from the YAML configuration file
-output_dir=$(awk '/output_dir:/ {print $2}' "$CONFIGFILE")
-if [ -z "$output_dir" ]; then
-  echo "Error: output_dir not specified in $CONFIGFILE"
-  exit 1
-fi
-
-# Create a timestamped output directory
-results_dir="${output_dir}_$(timestamp)"
+NUMBER_GPUS=${4:-1}
+export NUMBER_GPUS
+echo "argument 4: NUMBER_GPUS set to ${NUMBER_GPUS}"
 
+results_dir=$(extract_output_dir "$CONFIGFILE")
+
+echo "Starting seed is: $DOMAINLAB_CUDA_START_SEED"
+echo "Hyperparameter seed is: $DOMAINLAB_CUDA_HYPERPARAM_SEED"
+echo "Number of GPUs: $NUMBER_GPUS"
+echo "Results will be stored in: $results_dir"
 
 # -n: dry-run  (A dry run is a software testing process where the effects of a possible failure are intentionally mitigated, For example, there is rsync utility for transfer data over some interface, but user can try rsync with dry-run option to check syntax and test communication without data transferring.)
 # -p: print shell commands
@@ -65,8 +38,6 @@ results_dir="${output_dir}_$(timestamp)"
 # -- configfile: configuration yaml file of the benchmark
 
 
-
-
 # first display all tasks
 snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --keep-going --summary  # this will give us a clue first what jobs will be run
 
diff --git a/scripts/common_benchmark_functions.sh b/scripts/common_benchmark_functions.sh
new file mode 100644
index 000000000..a489f4ca9
--- /dev/null
+++ b/scripts/common_benchmark_functions.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+
+# This script contains common functions used in multiple scripts
+
+timestamp() {
+    date +"%Y-%m-%d_%H-%M-%S"
+}
+
+create_log_file() {
+    local logdir="zoutput/logs"
+    mkdir -p "$logdir"
+    local logfile="$logdir/$(timestamp).out"
+    echo "verbose log: $logfile"
+    echo "$logfile"
+}
+
+extract_output_dir() {
+    local config_file=$1
+    local output_dir=$(awk '/output_dir:/ {print $2}' "$config_file")
+    if [ -z "$output_dir" ]; then
+        echo "Error: output_dir not specified in $config_file"
+        exit 1
+    fi
+    echo "${output_dir}_$(timestamp)"
+}

From 7d792c34854fa42674aa533e780f204cfd665101 Mon Sep 17 00:00:00 2001
From: matteowohlrapp <matteo.wohlrapp@tum.de>
Date: Thu, 16 May 2024 15:35:58 +0200
Subject: [PATCH 093/273] Remove set -e to see if it extends the logs

---
 run_benchmark_standalone.sh | 1 -
 1 file changed, 1 deletion(-)

diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index e4b2c1efe..093ba42a6 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -1,5 +1,4 @@
 #!/bin/bash
-set -e
 
 # Source the common functions script
 source scripts/common_benchmark_functions.sh

From 67691de018e4f6a8a235f71638159b2c1f05bb6b Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 17 May 2024 16:58:54 +0200
Subject: [PATCH 094/273] correct hyper spec

---
 examples/benchmark/pacs_fbopt_irm_erm.yaml | 2 --
 1 file changed, 2 deletions(-)

diff --git a/examples/benchmark/pacs_fbopt_irm_erm.yaml b/examples/benchmark/pacs_fbopt_irm_erm.yaml
index 70ab77707..2c435f2da 100644
--- a/examples/benchmark/pacs_fbopt_irm_erm.yaml
+++ b/examples/benchmark/pacs_fbopt_irm_erm.yaml
@@ -56,8 +56,6 @@ fbopt_irm_erm:
   trainer: fbopt_irm
   shared:
     - ini_setpoint_ratio
-    - k_i_gain
-    - gamma_reg
 
 irm_erm:
   model: erm

From 38fb5f20ac72a9b213ea42f80e2d5d713ac49c7b Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Wed, 22 May 2024 09:39:53 +0200
Subject: [PATCH 095/273] Solved indexing issue in fbopt mu controller and
 added flag info to train epoch. Reverted prior backpack changes

---
 .../algos/trainers/fbopt_mu_controller.py     | 49 +++++++++++--------
 domainlab/algos/trainers/train_fishr.py       | 17 ++-----
 .../algos/trainers/train_hyper_scheduler.py   |  2 +-
 domainlab/algos/trainers/train_irm.py         |  4 +-
 domainlab/algos/trainers/train_matchdg.py     |  2 +-
 domainlab/algos/trainers/train_mldg.py        |  4 +-
 domainlab/models/a_model_classif.py           |  9 ++--
 domainlab/models/model_erm.py                 | 30 +++---------
 8 files changed, 51 insertions(+), 66 deletions(-)

diff --git a/domainlab/algos/trainers/fbopt_mu_controller.py b/domainlab/algos/trainers/fbopt_mu_controller.py
index 9f8e02971..793395f03 100644
--- a/domainlab/algos/trainers/fbopt_mu_controller.py
+++ b/domainlab/algos/trainers/fbopt_mu_controller.py
@@ -206,27 +206,36 @@ def search_mu(
             self.writer.add_scalar(f"controller_gain/{key}", dict_gain[key], miter)
             ind = list_str_multiplier_na.index(key)
             self.writer.add_scalar(f"delta/{key}", self.delta_epsilon_r[ind], miter)
-        for i, (reg_dyn, reg_set) in enumerate(
-            zip(epo_reg_loss, self.get_setpoint4r())
-        ):
-            self.writer.add_scalar(
-                f"lossrd/dyn_{list_str_multiplier_na[i]}", reg_dyn, miter
-            )
-            self.writer.add_scalar(
-                f"lossrs/setpoint_{list_str_multiplier_na[i]}", reg_set, miter
-            )
+        
+        print(f"Epo Reg Loss: {epo_reg_loss}")
+        print(f"Setpoint: {self.get_setpoint4r()}")
+        print(f"List: {list_str_multiplier_na}")
 
-            self.writer.add_scalars(
-                f"loss_rds/loss_{list_str_multiplier_na[i]}_w_setpoint",
-                {
-                    f"lossr/loss_{list_str_multiplier_na[i]}": reg_dyn,
-                    f"lossr/setpoint_{list_str_multiplier_na[i]}": reg_set,
-                },
-                miter,
-            )
-            self.writer.add_scalar(
-                f"x_ell_y_r/loss_{list_str_multiplier_na[i]}", reg_dyn, epo_task_loss
-            )
+        if list_str_multiplier_na:
+            for i, (reg_dyn, reg_set) in enumerate(
+                zip(epo_reg_loss, self.get_setpoint4r())
+            ):
+
+                self.writer.add_scalar(
+                    f"lossrd/dyn_{list_str_multiplier_na[i]}", reg_dyn, miter
+                )
+                self.writer.add_scalar(
+                    f"lossrs/setpoint_{list_str_multiplier_na[i]}", reg_set, miter
+                )
+
+                self.writer.add_scalars(
+                    f"loss_rds/loss_{list_str_multiplier_na[i]}_w_setpoint",
+                    {
+                        f"lossr/loss_{list_str_multiplier_na[i]}": reg_dyn,
+                        f"lossr/setpoint_{list_str_multiplier_na[i]}": reg_set,
+                    },
+                    miter,
+                )
+                self.writer.add_scalar(
+                    f"x_ell_y_r/loss_{list_str_multiplier_na[i]}", reg_dyn, epo_task_loss
+                )
+        else: 
+            logger.info("No multiplier provided")
         self.writer.add_scalar("loss_task/penalized", epo_loss_tr, miter)
         self.writer.add_scalar("loss_task/ell", epo_task_loss, miter)
         acc_te = 0
diff --git a/domainlab/algos/trainers/train_fishr.py b/domainlab/algos/trainers/train_fishr.py
index 40a7bc50e..bd67aa001 100644
--- a/domainlab/algos/trainers/train_fishr.py
+++ b/domainlab/algos/trainers/train_fishr.py
@@ -26,7 +26,7 @@ class TrainerFishr(TrainerBasic):
         "Fishr: Invariant gradient variances for out-of-distribution generalization."
         International Conference on Machine Learning. PMLR, 2022.
     """
-    def tr_epoch(self, epoch):
+    def tr_epoch(self, epoch, flag_info=False):
         list_loaders = list(self.dict_loader_tr.values())
         loaders_zip = zip(*list_loaders)
         self.model.train()
@@ -46,7 +46,7 @@ def tr_epoch(self, epoch):
             self.epo_loss_tr += loss.detach().item()
             self.after_batch(epoch, ind_batch)
 
-        flag_stop = self.observer.update(epoch)  # notify observer
+        flag_stop = self.observer.update(epoch, flag_info)  # notify observer
         return flag_stop
 
     def var_grads_and_loss(self, tuple_data_domains_batch):
@@ -156,20 +156,11 @@ def cal_dict_variance_grads(self, tensor_x, vec_y):
         loss = self.model.cal_task_loss(tensor_x.clone(), vec_y)
         loss = loss.sum()
 
-        if backpack is None:
+        with backpack(Variance()):
             loss.backward(
                 inputs=list(self.model.parameters()), retain_graph=True, create_graph=True
             )
-        else:
-            with backpack(Variance()):
-                loss.backward(
-                    inputs=list(self.model.parameters()), retain_graph=True, create_graph=True
-                )
-
-        for name, param in self.model.named_parameters():
-            print(name)
-            print(".grad.shape:             ", param.variance.shape)
-
+          
         dict_variance = OrderedDict(
             [(name, weights.variance.clone())
              for name, weights in self.model.named_parameters()
diff --git a/domainlab/algos/trainers/train_hyper_scheduler.py b/domainlab/algos/trainers/train_hyper_scheduler.py
index 2e60bf5e8..9eda2e494 100644
--- a/domainlab/algos/trainers/train_hyper_scheduler.py
+++ b/domainlab/algos/trainers/train_hyper_scheduler.py
@@ -55,7 +55,7 @@ def before_tr(self):
                 flag_update_epoch=True,
             )
 
-    def tr_epoch(self, epoch):
+    def tr_epoch(self, epoch, flag_info=False):
         """
         update hyper-parameters only per epoch
         """
diff --git a/domainlab/algos/trainers/train_irm.py b/domainlab/algos/trainers/train_irm.py
index 0da2d0bde..9e91f1edc 100644
--- a/domainlab/algos/trainers/train_irm.py
+++ b/domainlab/algos/trainers/train_irm.py
@@ -19,7 +19,7 @@ class TrainerIRM(TrainerBasic):
     For more details, see section 3.2 and Appendix D of :
     Arjovsky et al., “Invariant Risk Minimization.”
     """
-    def tr_epoch(self, epoch):
+    def tr_epoch(self, epoch, flag_info=False):
         list_loaders = list(self.dict_loader_tr.values())
         loaders_zip = zip(*list_loaders)
         self.model.train()
@@ -46,7 +46,7 @@ def tr_epoch(self, epoch):
             self.epo_loss_tr += loss.detach().item()
             self.after_batch(epoch, ind_batch)
 
-        flag_stop = self.observer.update(epoch)  # notify observer
+        flag_stop = self.observer.update(epoch, flag_info)  # notify observer
         return flag_stop
 
     def _cal_phi(self, tensor_x):
diff --git a/domainlab/algos/trainers/train_matchdg.py b/domainlab/algos/trainers/train_matchdg.py
index e127baa12..ef4b1c862 100644
--- a/domainlab/algos/trainers/train_matchdg.py
+++ b/domainlab/algos/trainers/train_matchdg.py
@@ -95,7 +95,7 @@ def tr_epoch(self, epoch, flag_info=False):
 
         logger.info("\n\nPhase erm+ctr \n\n")
         self.flag_erm = True
-        flag_stop = self.observer.update(epoch)  # notify observer
+        flag_stop = self.observer.update(epoch, flag_info)  # notify observer
         return flag_stop
 
     def tr_batch(self, epoch, batch_idx, x_e, y_e, d_e, others=None):
diff --git a/domainlab/algos/trainers/train_mldg.py b/domainlab/algos/trainers/train_mldg.py
index e91310adf..9e13ff58b 100644
--- a/domainlab/algos/trainers/train_mldg.py
+++ b/domainlab/algos/trainers/train_mldg.py
@@ -51,7 +51,7 @@ def prepare_ziped_loader(self):
         ddset_mix = DsetZip(ddset_source, ddset_target)
         self.loader_tr_source_target = mk_loader(ddset_mix, self.aconf.bs)
 
-    def tr_epoch(self, epoch):
+    def tr_epoch(self, epoch, flag_info=False):
         self.model.train()
         self.epo_loss_tr = 0
         self.prepare_ziped_loader()
@@ -117,5 +117,5 @@ def tr_epoch(self, epoch):
             self.optimizer.step()
             self.epo_loss_tr += loss.detach().item()
             self.after_batch(epoch, ind_batch)
-        flag_stop = self.observer.update(epoch)  # notify observer
+        flag_stop = self.observer.update(epoch, flag_info)  # notify observer
         return flag_stop
diff --git a/domainlab/models/a_model_classif.py b/domainlab/models/a_model_classif.py
index 3dd9831d0..1f72eec0a 100644
--- a/domainlab/models/a_model_classif.py
+++ b/domainlab/models/a_model_classif.py
@@ -20,11 +20,10 @@
 
 try:
     from backpack import extend
-    loss_cross_entropy_extended = extend(nn.CrossEntropyLoss(reduction="none"))
-except ImportError:
-    # Handle the case where backpack is not available
-    loss_cross_entropy_extended = nn.CrossEntropyLoss(reduction="none")
-    print("Backpack could not be imported. Using standard nn.CrossEntropyLoss.")
+except:
+    backpack = None
+
+loss_cross_entropy_extended = extend(nn.CrossEntropyLoss(reduction="none"))
 
 class AModelClassif(AModel, metaclass=abc.ABCMeta):
     """
diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index d6ec3b35c..a47cb9844 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -4,13 +4,11 @@
 from domainlab.compos.nn_zoo.nn import LayerId
 from domainlab.models.a_model_classif import AModelClassif
 from domainlab.utils.override_interface import override_interface
-import traceback
 
 try:
     from backpack import extend
-except ImportError as e:
-    print(f"Failed to import 'extend' from backpack: {e}")
-    extend = None  # Ensure extend is defined to avoid NameError later in the code
+except:
+    backpack = None
 
 
 
@@ -51,24 +49,12 @@ def __init__(self, net=None, net_feat=None):
             self._net_invar_feat = net_feat
 
         def convert4backpack(self):
-            print("Extending model components...")
-            if extend is not None:
-                try:
-                    if hasattr(self._net_invar_feat, 'parameters'):
-                        print("Net features before extend:", self._net_invar_feat)
-                    self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
-                except Exception as e:
-                    print("An error occurred:", e)
-                    traceback.print_exc()
-                
-                if hasattr(self.net_classifier, 'parameters'):
-                    print("Net classifier before extend:", self.net_classifier)
-                self.net_classifier = extend(self.net_classifier, use_converter=True)
-            else:
-                print("Backpack's extend function is not available.")
-
-
-    
+        """
+        convert the module to backpack for 2nd order gradients
+        """
+        self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
+        self.net_classifier = extend(self.net_classifier,  use_converter=True)
+
         def hyper_update(self, epoch, fun_scheduler):
             """hyper_update.
 

From caf32b7cb674d7d54268ab08f15a84cff9caf644 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Wed, 22 May 2024 09:42:56 +0200
Subject: [PATCH 096/273] removed prints

---
 domainlab/algos/trainers/fbopt_mu_controller.py | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/domainlab/algos/trainers/fbopt_mu_controller.py b/domainlab/algos/trainers/fbopt_mu_controller.py
index 793395f03..25432bb45 100644
--- a/domainlab/algos/trainers/fbopt_mu_controller.py
+++ b/domainlab/algos/trainers/fbopt_mu_controller.py
@@ -206,10 +206,6 @@ def search_mu(
             self.writer.add_scalar(f"controller_gain/{key}", dict_gain[key], miter)
             ind = list_str_multiplier_na.index(key)
             self.writer.add_scalar(f"delta/{key}", self.delta_epsilon_r[ind], miter)
-        
-        print(f"Epo Reg Loss: {epo_reg_loss}")
-        print(f"Setpoint: {self.get_setpoint4r()}")
-        print(f"List: {list_str_multiplier_na}")
 
         if list_str_multiplier_na:
             for i, (reg_dyn, reg_set) in enumerate(

From a098a681bbd72c13fffe5f0da1aa18858b7d4b58 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Wed, 22 May 2024 09:50:28 +0200
Subject: [PATCH 097/273] Fixed indentation for convert4backpack

---
 domainlab/models/model_erm.py | 12 +++++-------
 1 file changed, 5 insertions(+), 7 deletions(-)

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index a47cb9844..48330f6fa 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -10,8 +10,6 @@
 except:
     backpack = None
 
-
-
 def mk_erm(parent_class=AModelClassif, **kwargs):
     """
     Instantiate a Deepall (ERM) model
@@ -49,11 +47,11 @@ def __init__(self, net=None, net_feat=None):
             self._net_invar_feat = net_feat
 
         def convert4backpack(self):
-        """
-        convert the module to backpack for 2nd order gradients
-        """
-        self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
-        self.net_classifier = extend(self.net_classifier,  use_converter=True)
+            """
+            convert the module to backpack for 2nd order gradients
+            """
+            self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
+            self.net_classifier = extend(self.net_classifier,  use_converter=True)
 
         def hyper_update(self, epoch, fun_scheduler):
             """hyper_update.

From ee84bcbb0ec103c7cec5ee3633ec1ead48a9e874 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 28 May 2024 10:19:00 +0200
Subject: [PATCH 098/273] Adding debug statements to standalone script, exiting
 without errors

---
 run_benchmark_standalone.sh           | 6 ++++++
 scripts/common_benchmark_functions.sh | 1 -
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index 093ba42a6..86e9a8d47 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -1,5 +1,7 @@
 #!/bin/bash
 
+set -e
+
 # Source the common functions script
 source scripts/common_benchmark_functions.sh
 
@@ -44,6 +46,10 @@ snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk"
 snakemake --config yaml_file="$CONFIGFILE" --rerun-incomplete --resources nvidia_gpu="$NUMBER_GPUS" --cores 4 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
 
 
+snakemake_exit_code=${PIPESTATUS[0]}
+echo "Snakemake exited with code: $snakemake_exit_code"
+exit $snakemake_exit_code
+
 # snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk" --configfile "examples/yaml/demo_benchmark.yaml"
 # snakemake -np -s "domainlab/exp_protocol/benchmark.smk" --configfile "examples/yaml/demo_benchmark.yaml"
 
diff --git a/scripts/common_benchmark_functions.sh b/scripts/common_benchmark_functions.sh
index a489f4ca9..9253f8ebc 100644
--- a/scripts/common_benchmark_functions.sh
+++ b/scripts/common_benchmark_functions.sh
@@ -10,7 +10,6 @@ create_log_file() {
     local logdir="zoutput/logs"
     mkdir -p "$logdir"
     local logfile="$logdir/$(timestamp).out"
-    echo "verbose log: $logfile"
     echo "$logfile"
 }
 

From 518d919bb3459b80fc492879219b8bd8188a3b81 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 28 May 2024 11:39:18 +0200
Subject: [PATCH 099/273] fixed codacity

---
 domainlab/algos/trainers/fbopt_mu_controller.py | 2 +-
 domainlab/algos/trainers/train_fishr.py         | 2 +-
 domainlab/models/model_erm.py                   | 4 ++--
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/domainlab/algos/trainers/fbopt_mu_controller.py b/domainlab/algos/trainers/fbopt_mu_controller.py
index 25432bb45..824638461 100644
--- a/domainlab/algos/trainers/fbopt_mu_controller.py
+++ b/domainlab/algos/trainers/fbopt_mu_controller.py
@@ -230,7 +230,7 @@ def search_mu(
                 self.writer.add_scalar(
                     f"x_ell_y_r/loss_{list_str_multiplier_na[i]}", reg_dyn, epo_task_loss
                 )
-        else: 
+        else:
             logger.info("No multiplier provided")
         self.writer.add_scalar("loss_task/penalized", epo_loss_tr, miter)
         self.writer.add_scalar("loss_task/ell", epo_task_loss, miter)
diff --git a/domainlab/algos/trainers/train_fishr.py b/domainlab/algos/trainers/train_fishr.py
index bd67aa001..e8d0c71b8 100644
--- a/domainlab/algos/trainers/train_fishr.py
+++ b/domainlab/algos/trainers/train_fishr.py
@@ -160,7 +160,7 @@ def cal_dict_variance_grads(self, tensor_x, vec_y):
             loss.backward(
                 inputs=list(self.model.parameters()), retain_graph=True, create_graph=True
             )
-          
+    
         dict_variance = OrderedDict(
             [(name, weights.variance.clone())
              for name, weights in self.model.named_parameters()
diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index 48330f6fa..f863da655 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -59,7 +59,7 @@ def hyper_update(self, epoch, fun_scheduler):
             :param epoch:
             :param fun_scheduler:
             """
-            pass
+            ...
 
         def hyper_init(self, functor_scheduler, trainer=None):
             """
@@ -70,7 +70,7 @@ def hyper_init(self, functor_scheduler, trainer=None):
             return functor_scheduler(
                 trainer=trainer
             )
-        
+    
         @property
         def list_str_multiplier_na(self):
             """

From e947f67176c1be3ea9cae338c6f0c2c1531f7228 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 28 May 2024 12:15:52 +0200
Subject: [PATCH 100/273] fixed codacity

---
 domainlab/algos/trainers/train_fishr.py | 2 +-
 domainlab/models/model_erm.py           | 7 ++++---
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/domainlab/algos/trainers/train_fishr.py b/domainlab/algos/trainers/train_fishr.py
index e8d0c71b8..250b4109d 100644
--- a/domainlab/algos/trainers/train_fishr.py
+++ b/domainlab/algos/trainers/train_fishr.py
@@ -160,7 +160,7 @@ def cal_dict_variance_grads(self, tensor_x, vec_y):
             loss.backward(
                 inputs=list(self.model.parameters()), retain_graph=True, create_graph=True
             )
-    
+
         dict_variance = OrderedDict(
             [(name, weights.variance.clone())
              for name, weights in self.model.named_parameters()
diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index f863da655..5e491a5b7 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -53,13 +53,14 @@ def convert4backpack(self):
             self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
             self.net_classifier = extend(self.net_classifier,  use_converter=True)
 
-        def hyper_update(self, epoch, fun_scheduler):
+        def hyper_update(self, _epoch, _fun_scheduler):
             """hyper_update.
 
             :param epoch:
             :param fun_scheduler:
             """
-            ...
+            """Method necessary to combine with hyperparameter scheduler"""
+            return
 
         def hyper_init(self, functor_scheduler, trainer=None):
             """
@@ -70,7 +71,7 @@ def hyper_init(self, functor_scheduler, trainer=None):
             return functor_scheduler(
                 trainer=trainer
             )
-    
+
         @property
         def list_str_multiplier_na(self):
             """

From 5b28c73c0d42b838108263016f88624faf2135a9 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@gpusrv12.scidom.de>
Date: Tue, 28 May 2024 16:53:17 +0200
Subject: [PATCH 101/273] Added the hyperparameter naming to parts of the
 models novel on this branch

---
 domainlab/models/model_dann.py  |  2 +-
 domainlab/models/model_diva.py  | 55 +++++++++++++++++----------------
 domainlab/models/model_hduva.py | 12 +++----
 domainlab/models/model_jigen.py |  4 +--
 4 files changed, 38 insertions(+), 35 deletions(-)

diff --git a/domainlab/models/model_dann.py b/domainlab/models/model_dann.py
index 16c1d6f8b..08e1fb74f 100644
--- a/domainlab/models/model_dann.py
+++ b/domainlab/models/model_dann.py
@@ -79,7 +79,7 @@ def reset_aux_net(self):
 
         @property
         def list_str_multiplier_na(self):
-            return ["alpha"]
+            return [self.name + "_alpha"]
 
         def hyper_update(self, epoch, fun_scheduler):
             """hyper_update.
diff --git a/domainlab/models/model_diva.py b/domainlab/models/model_diva.py
index 3185cc452..859fb6fa5 100644
--- a/domainlab/models/model_diva.py
+++ b/domainlab/models/model_diva.py
@@ -123,7 +123,7 @@ def list_str_multiplier_na(self):
             """
             list of multipliers name
             """
-            return ["mu_recon", "beta_d", "beta_x", "beta_y", "gamma_d"]
+            return [f"{self.name}_mu_recon", f"{self.name}_beta_d", f"{self.name}_beta_x", f"{self.name}_beta_y", f"{self.name}_gamma_d"]
 
         @property
         def dict_multiplier(self):
@@ -131,11 +131,11 @@ def dict_multiplier(self):
             list of multipliers name, which correspond to cal_reg_loss
             """
             return {
-                "mu_recon": self.mu_recon,
-                "beta_d": self.beta_d,
-                "beta_x": self.beta_x,
-                "beta_y": self.beta_y,
-                "gamma_d": self.gamma_d,
+                f"{self.name}_mu_recon": self.mu_recon,
+                f"{self.name}_beta_d": self.beta_d,
+                f"{self.name}_beta_x": self.beta_x,
+                f"{self.name}_beta_y": self.beta_y,
+                f"{self.name}_gamma_d": self.gamma_d,
             }
 
         def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
@@ -187,11 +187,11 @@ def hyper_update(self, epoch, fun_scheduler):
             :param fun_scheduler:
             """
             dict_rst = fun_scheduler(epoch)
-            self.beta_d = dict_rst["beta_d"]
-            self.beta_y = dict_rst["beta_y"]
-            self.beta_x = dict_rst["beta_x"]
-            self.gamma_d = dict_rst["gamma_d"]
-            self.mu_recon = dict_rst["mu_recon"]
+            self.beta_d = dict_rst[self.name + "_beta_d"]
+            self.beta_y = dict_rst[self.name + "_beta_x"]
+            self.beta_x = dict_rst[self.name + "_beta_y"]
+            self.gamma_d = dict_rst[self.name + "_gamma_d"]
+            self.mu_recon = dict_rst[self.name + "_mu_recon"]
 
         def hyper_init(self, functor_scheduler, trainer=None):
             """
@@ -199,13 +199,14 @@ def hyper_init(self, functor_scheduler, trainer=None):
 
             :param functor_scheduler: the class name of the scheduler
             """
+            parameters = {}
+            parameters[self.name + "_beta_d"] = self.beta_d
+            parameters[self.name + "_beta_y"] = self.beta_y
+            parameters[self.name + "_beta_x"] = self.beta_x
+            parameters[self.name + "_gamma_d"] = self.gamma_d
+            parameters[self.name + "_mu_recon"] = self.mu_recon
             return functor_scheduler(
-                trainer=trainer,
-                beta_d=self.beta_d,
-                beta_y=self.beta_y,
-                beta_x=self.beta_x,
-                gamma_d=self.gamma_d,
-                mu_recon=self.mu_recon,
+                trainer=trainer, **parameters
             )
 
     class ModelDIVAGammadReconPerPixel(ModelDIVAGammadRecon):
@@ -238,10 +239,10 @@ def hyper_update(self, epoch, fun_scheduler):
             :param fun_scheduler:
             """
             dict_rst = fun_scheduler(epoch)
-            self.beta_d = dict_rst["beta_d"]
-            self.beta_y = dict_rst["beta_y"]
-            self.beta_x = dict_rst["beta_x"]
-            self.gamma_d = dict_rst["gamma_d"]
+            self.beta_d = dict_rst[self.name + "_beta_d"]
+            self.beta_y = dict_rst[self.name + "_beta_x"]
+            self.beta_x = dict_rst[self.name + "_beta_y"]
+            self.gamma_d = dict_rst[self.name + "_gamma_d"]
 
         def hyper_init(self, functor_scheduler, trainer=None):
             """
@@ -249,12 +250,14 @@ def hyper_init(self, functor_scheduler, trainer=None):
 
             :param functor_scheduler: the class name of the scheduler
             """
+            parameters = {}
+            parameters[self.name + "_beta_d"] = self.beta_d
+            parameters[self.name + "_beta_y"] = self.beta_y
+            parameters[self.name + "_beta_x"] = self.beta_x
+            parameters[self.name + "_gamma_d"] = self.gamma_d
+            parameters[self.name + "_mu_recon"] = self.mu_recon
             return functor_scheduler(
-                trainer=trainer,
-                beta_d=self.beta_d,
-                beta_y=self.beta_y,
-                beta_x=self.beta_x,
-                gamma_d=self.gamma_d,
+                trainer=trainer, **parameters
             )
 
     class ModelDIVADefault(ModelDIVA):
diff --git a/domainlab/models/model_hduva.py b/domainlab/models/model_hduva.py
index 91d1ad03a..f7ab1d48c 100644
--- a/domainlab/models/model_hduva.py
+++ b/domainlab/models/model_hduva.py
@@ -208,7 +208,7 @@ def list_str_multiplier_na(self):
             """
             list of multipliers name which matches the order from cal_reg_loss
             """
-            return ["mu_recon", "beta_x", "beta_y", "beta_d", "beta_t"]
+            return [f"{self.name}_mu_recon", f"{self.name}_beta_d", f"{self.name}_beta_x", f"{self.name}_beta_y", f"{self.name}_beta_t"]
 
         @property
         def dict_multiplier(self):
@@ -216,11 +216,11 @@ def dict_multiplier(self):
             dictionary of multipliers name
             """
             return {
-                "mu_recon": self.mu_recon,
-                "beta_d": self.beta_d,
-                "beta_x": self.beta_x,
-                "beta_y": self.beta_y,
-                "beta_t": self.beta_t,
+                f"{self.name}_mu_recon": self.mu_recon,
+                f"{self.name}_beta_d": self.beta_d,
+                f"{self.name}_beta_x": self.beta_x,
+                f"{self.name}_beta_y": self.beta_y,
+                f"{self.name}_beta_t": self.beta_t,
             }
 
         def extract_semantic_feat(self, tensor_x):
diff --git a/domainlab/models/model_jigen.py b/domainlab/models/model_jigen.py
index 43cb6ea98..2d382293f 100644
--- a/domainlab/models/model_jigen.py
+++ b/domainlab/models/model_jigen.py
@@ -81,14 +81,14 @@ def list_str_multiplier_na(self):
             """
             list of multipliers which match the order in cal_reg_loss
             """
-            return ["alpha"]
+            return [self.name + "_alpha"]
 
         @property
         def dict_multiplier(self):
             """
             dictionary of multipliers
             """
-            return {"alpha": self.alpha}
+            return {f"{self.name}_alpha": self.alpha}
 
         def dset_decoration_args_algo(self, args, ddset):
             """

From bc3c808b7f8f0f057c275f26d9e53dbea02d0934 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 28 May 2024 16:56:38 +0200
Subject: [PATCH 102/273] ci running, exiting with 0, removing prints

---
 run_benchmark_standalone.sh | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index 86e9a8d47..e15469e2f 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -45,11 +45,6 @@ snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk"
 # second submit the jobs, make sure you have more than 4 cores on your laptop, otherwise adjust the cores
 snakemake --config yaml_file="$CONFIGFILE" --rerun-incomplete --resources nvidia_gpu="$NUMBER_GPUS" --cores 4 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
 
-
-snakemake_exit_code=${PIPESTATUS[0]}
-echo "Snakemake exited with code: $snakemake_exit_code"
-exit $snakemake_exit_code
-
 # snakemake --rerun-incomplete --cores 1 -s "domainlab/exp_protocol/benchmark.smk" --configfile "examples/yaml/demo_benchmark.yaml"
 # snakemake -np -s "domainlab/exp_protocol/benchmark.smk" --configfile "examples/yaml/demo_benchmark.yaml"
 

From 5d2fb8222cbe9e0e5081f8389acc07c2c0f4778a Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 11 Jun 2024 11:25:20 +0200
Subject: [PATCH 103/273] Fixed codacity

---
 docs/doc_usage_cmd.md | 11 ++++++++---
 1 file changed, 8 insertions(+), 3 deletions(-)

diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index dfb92b3ca..3c6e53176 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -21,7 +21,9 @@ To run DomainLab, the minimum necessary parameters are:
 ### Advanced Configuration
 
 - **Learning Rate (`--lr`):** Set the training learning rate.
-- **Regularization (`--gamma_reg`):** Sets the weight of the regularization loss. This parameter can be configured either as a single value applied to individual classes, or using a dictionary to specify different weights for different models and trainers.
+- **Regularization (`--gamma_reg`):** Sets the weight of the regularization loss. 
+This parameter can be configured either as a single value applied to individual classes, 
+or using a dictionary to specify different weights for different models and trainers.
 
   - **Command Line Usage:**
     - For a single value: `python script.py --gamma_reg=0.1`
@@ -32,13 +34,16 @@ To run DomainLab, the minimum necessary parameters are:
       ```yaml
       gamma_reg: 0.1
       ```
+
     - For different values:
       ```yaml
       gamma_reg:
-        default: 0.1 # every other instance that is not listed below will get this value assigned
         dann: 0.05
         diva: 0.2
-      ```- **Early Stopping (`--es`):** Steps for early stopping.
+        default: 0.1 # value for every other instance
+      ```  
+
+- **Early Stopping (`--es`):** Steps for early stopping.
 - **Random Seed (`--seed`):** Seed for reproducibility.
 - **CUDA Options (`--nocu`, `--device`):** Configure CUDA usage and device settings.
 - **Generated Images (`--gen`):** Option to save generated images.

From 7124cc7774d65c926678f4de84debd9711c95668 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 11 Jun 2024 11:52:20 +0200
Subject: [PATCH 104/273] Fixed codacity

---
 domainlab/models/model_dann.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/domainlab/models/model_dann.py b/domainlab/models/model_dann.py
index 08e1fb74f..b940c5d71 100644
--- a/domainlab/models/model_dann.py
+++ b/domainlab/models/model_dann.py
@@ -79,6 +79,9 @@ def reset_aux_net(self):
 
         @property
         def list_str_multiplier_na(self):
+            """
+            name of the multiplier
+            """
             return [self.name + "_alpha"]
 
         def hyper_update(self, epoch, fun_scheduler):

From 570e8a86826ec31353fe883d6a670e1f2d51583a Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@gpusrv12.scidom.de>
Date: Tue, 11 Jun 2024 13:03:37 +0200
Subject: [PATCH 105/273] fixed codacity

---
 docs/doc_usage_cmd.md | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index 3c6e53176..ee814fdd3 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -21,9 +21,11 @@ To run DomainLab, the minimum necessary parameters are:
 ### Advanced Configuration
 
 - **Learning Rate (`--lr`):** Set the training learning rate.
-- **Regularization (`--gamma_reg`):** Sets the weight of the regularization loss. 
-This parameter can be configured either as a single value applied to individual classes, 
-or using a dictionary to specify different weights for different models and trainers.
+- **Regularization (`--gamma_reg`):** Sets the weight of the regularization
+ loss. This parameter can be configured either as
+ a single value applied to individual classes,
+ or using a dictionary to specify different
+ weights for different models and trainers.
 
   - **Command Line Usage:**
     - For a single value: `python script.py --gamma_reg=0.1`
@@ -31,11 +33,13 @@ or using a dictionary to specify different weights for different models and trai
 
   - **YAML Configuration:**
     - For a single value:
+
       ```yaml
       gamma_reg: 0.1
       ```
 
     - For different values:
+
       ```yaml
       gamma_reg:
         dann: 0.05

From d2ac388dfe1fe0d1deef4016fb6af127cba4294f Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 11 Jun 2024 13:12:30 +0200
Subject: [PATCH 106/273] retrigger run

---
 docs/doc_usage_cmd.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index f7547ae80..ac9a0e48c 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -33,6 +33,7 @@ To run DomainLab, the minimum necessary parameters are:
       gamma_reg: 0.1
       ```
     - For different values:
+    
       ```yaml
       gamma_reg:
         default: 0.1 # every other instance that is not listed below will get this value assigned

From 4f1347a9c850f70adcb9276e6aad59530f0440de Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 11 Jun 2024 15:38:50 +0200
Subject: [PATCH 107/273] fixed codacity

---
 domainlab/models/model_erm.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index 5e491a5b7..bc4f6e45f 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -54,13 +54,12 @@ def convert4backpack(self):
             self.net_classifier = extend(self.net_classifier,  use_converter=True)
 
         def hyper_update(self, _epoch, _fun_scheduler):
-            """hyper_update.
+            """
+            Method necessary to combine with hyperparameter scheduler
 
             :param epoch:
             :param fun_scheduler:
             """
-            """Method necessary to combine with hyperparameter scheduler"""
-            return
 
         def hyper_init(self, functor_scheduler, trainer=None):
             """

From f2fa952ba2f020adeac830abddd4774e3a5d9054 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 11 Jun 2024 16:07:53 +0200
Subject: [PATCH 108/273] fixed codacity

---
 domainlab/models/model_erm.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index bc4f6e45f..4dc4c03f3 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -53,7 +53,7 @@ def convert4backpack(self):
             self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
             self.net_classifier = extend(self.net_classifier,  use_converter=True)
 
-        def hyper_update(self, _epoch, _fun_scheduler):
+        def hyper_update(self, epoch, fun_scheduler): # noqa: F841  # pylint: disable=unused-argument
             """
             Method necessary to combine with hyperparameter scheduler
 

From 279f5102ea62d508eb9fe5b4a11ddf714c8170e2 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 11 Jun 2024 16:16:05 +0200
Subject: [PATCH 109/273] Added test for erm functions

---
 tests/test_fbopt.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/tests/test_fbopt.py b/tests/test_fbopt.py
index 1e2859291..cbf9b8d98 100644
--- a/tests/test_fbopt.py
+++ b/tests/test_fbopt.py
@@ -27,6 +27,12 @@ def test_diva_fbopt():
     args = "--te_d=caltech --task=mini_vlcs --debug --bs=2 --model=diva --gamma_y=1.0 --trainer=fbopt --nname=alexnet --epos=3"
     utils_test_algo(args)
 
+def test_erm_fbopt():
+    """
+    erm
+    """
+    args = "--te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm --trainer=fbopt --nname=alexnet --epos=3"
+    utils_test_algo(args)
 
 def test_forcesetpoint_fbopt():
     """

From f8f4f0edaecabe37349ae52eab5881b330e8d30d Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 11 Jun 2024 16:31:30 +0200
Subject: [PATCH 110/273] Disabling line too long for argument

---
 domainlab/models/model_erm.py | 2 +-
 tests/test_fbopt.py           | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index 4dc4c03f3..4ccec7a50 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -53,7 +53,7 @@ def convert4backpack(self):
             self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
             self.net_classifier = extend(self.net_classifier,  use_converter=True)
 
-        def hyper_update(self, epoch, fun_scheduler): # noqa: F841  # pylint: disable=unused-argument
+        def hyper_update(self, epoch, fun_scheduler): # pylint: disable=unused-argument
             """
             Method necessary to combine with hyperparameter scheduler
 
diff --git a/tests/test_fbopt.py b/tests/test_fbopt.py
index cbf9b8d98..c442bf090 100644
--- a/tests/test_fbopt.py
+++ b/tests/test_fbopt.py
@@ -31,7 +31,7 @@ def test_erm_fbopt():
     """
     erm
     """
-    args = "--te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm --trainer=fbopt --nname=alexnet --epos=3"
+    args = "--te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm --trainer=fbopt --nname=alexnet --epos=3" # pylint: disable=line-too-long
     utils_test_algo(args)
 
 def test_forcesetpoint_fbopt():

From 31f90fcafc7936896c5e55e2b99928ae7207a772 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 25 Jun 2024 10:01:09 +0200
Subject: [PATCH 111/273] Saving initial model

---
 domainlab/exp/exp_main.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/domainlab/exp/exp_main.py b/domainlab/exp/exp_main.py
index 12ecea5f5..3d60ac520 100755
--- a/domainlab/exp/exp_main.py
+++ b/domainlab/exp/exp_main.py
@@ -59,6 +59,7 @@ def __init__(self, args, task=None, model=None, observer=None, visitor=AggWriter
         # visitor must be initialized last after trainer is initialized
         self.experiment_duration = None
         self.model.set_saver(self.visitor)
+        self.model.save()
 
     def execute(self, num_epochs=None):
         """

From 5a99aa68c43d7e0af3230f9c29f97217240176d8 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 25 Jun 2024 10:28:10 +0200
Subject: [PATCH 112/273] Renamed common benchmark file

---
 run_benchmark_slurm.sh                                          | 2 +-
 run_benchmark_standalone.sh                                     | 2 +-
 .../{common_benchmark_functions.sh => sh_benchmark_utils.sh}    | 0
 3 files changed, 2 insertions(+), 2 deletions(-)
 rename scripts/{common_benchmark_functions.sh => sh_benchmark_utils.sh} (100%)

diff --git a/run_benchmark_slurm.sh b/run_benchmark_slurm.sh
index cdf889a87..66e6a0464 100755
--- a/run_benchmark_slurm.sh
+++ b/run_benchmark_slurm.sh
@@ -1,7 +1,7 @@
 #!/bin/bash
 
 # Source the common functions script
-source scripts/common_benchmark_functions.sh
+source scripts/sh_benchmark_utils.sh
 
 # CONFIGFILE="examples/yaml/test_helm_benchmark.yaml"
 CONFIGFILE=$1
diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index e15469e2f..297f8f5df 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -3,7 +3,7 @@
 set -e
 
 # Source the common functions script
-source scripts/common_benchmark_functions.sh
+source scripts/sh_benchmark_utils.sh
 
 CONFIGFILE=$1
 logfile=$(create_log_file)
diff --git a/scripts/common_benchmark_functions.sh b/scripts/sh_benchmark_utils.sh
similarity index 100%
rename from scripts/common_benchmark_functions.sh
rename to scripts/sh_benchmark_utils.sh

From 88e383d43780f91eecb8be2a5376447fdc4897ae Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 25 Jun 2024 18:30:37 +0200
Subject: [PATCH 113/273] Specified pip version

---
 .github/workflows/ci.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index f1a4fa9b6..fe57dc0d5 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -26,7 +26,7 @@ jobs:
         python setup.py install
     - name: Install Python Poetry
       run: |
-        python -m pip install --upgrade pip
+        python -m pip install --upgrade pip==24.0
         pip install poetry
         poetry install --with dev
     - name: test if api works

From c672a0422488814080e856420479a057a996dc08 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 25 Jun 2024 18:36:47 +0200
Subject: [PATCH 114/273] Specified pip version

---
 .github/workflows/ci.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index fe57dc0d5..9c1aec884 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -20,7 +20,7 @@ jobs:
         python-version: 3.10.7
     - name: Install dependencies
       run: |
-        python -m pip install --upgrade pip
+        python -m pip install --upgrade pip==24.0
         pip install -r requirements.txt
         pip install pytest pytest-cov pytest-shell
         python setup.py install

From 13af9f0b3f05143a93ae8968eabb300bbeb41a75 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 27 Jun 2024 15:36:03 +0200
Subject: [PATCH 115/273] Update pyproject.toml for   version lower than 70 of
 setup tools

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index 2f44de78a..27303d5bd 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -9,6 +9,7 @@ authors = ["Xudong Sun <smilesun.east@gmail.com>", "Carla Feistner", "Alexej Gos
 
 [tool.poetry.dependencies]
 python = "^3.9"
+setuptools = "^69.5.1"
 numpy = "^1.23.4"
 matplotlib = "^3.6.1"
 seaborn = "0.12.2"

From 1220cc1d5d535db4de1d91837b97bf3942565db0 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 27 Jun 2024 15:48:18 +0200
Subject: [PATCH 116/273] delete poetry lock

---
 poetry.lock | 1561 ---------------------------------------------------
 1 file changed, 1561 deletions(-)
 delete mode 100644 poetry.lock

diff --git a/poetry.lock b/poetry.lock
deleted file mode 100644
index 6e8b0c48e..000000000
--- a/poetry.lock
+++ /dev/null
@@ -1,1561 +0,0 @@
-[[package]]
-name = "atomicwrites"
-version = "1.4.1"
-description = "Atomic file writes."
-category = "dev"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-
-[[package]]
-name = "attrs"
-version = "23.2.0"
-description = "Classes Without Boilerplate"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-
-[package.extras]
-cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[tests]", "pre-commit"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
-tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
-tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
-
-[[package]]
-name = "backpack-for-pytorch"
-version = "1.6.0"
-description = "BackPACK: Packing more into backprop"
-category = "main"
-optional = false
-python-versions = ">=3.8"
-
-[package.dependencies]
-einops = ">=0.3.0,<1.0.0"
-torch = ">=1.9.0"
-torchvision = ">=0.7.0"
-unfoldNd = ">=0.2.0,<1.0.0"
-
-[package.extras]
-docs = ["matplotlib", "memory-profiler", "sphinx-gallery", "sphinx-rtd-theme", "tabulate"]
-lint = ["black", "darglint", "flake8", "flake8-bugbear", "flake8-comprehensions", "flake8-tidy-imports", "isort", "mccabe", "pep8-naming", "pycodestyle", "pydocstyle", "pyflakes"]
-test = ["coveralls", "pytest (>=4.5.0,<5.0.0)", "pytest-benchmark (>=3.2.2,<4.0.0)", "pytest-cov", "pytest-optional-tests (>=0.1.1)", "scipy"]
-
-[[package]]
-name = "beautifulsoup4"
-version = "4.12.3"
-description = "Screen-scraping library"
-category = "main"
-optional = false
-python-versions = ">=3.6.0"
-
-[package.dependencies]
-soupsieve = ">1.2"
-
-[package.extras]
-cchardet = ["cchardet"]
-chardet = ["chardet"]
-charset-normalizer = ["charset-normalizer"]
-html5lib = ["html5lib"]
-lxml = ["lxml"]
-
-[[package]]
-name = "certifi"
-version = "2023.11.17"
-description = "Python package for providing Mozilla's CA Bundle."
-category = "main"
-optional = false
-python-versions = ">=3.6"
-
-[[package]]
-name = "charset-normalizer"
-version = "3.3.2"
-description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
-category = "main"
-optional = false
-python-versions = ">=3.7.0"
-
-[[package]]
-name = "colorama"
-version = "0.4.6"
-description = "Cross-platform colored terminal text."
-category = "main"
-optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
-
-[[package]]
-name = "contourpy"
-version = "1.2.0"
-description = "Python library for calculating contours of 2D quadrilateral grids"
-category = "main"
-optional = false
-python-versions = ">=3.9"
-
-[package.dependencies]
-numpy = ">=1.20,<2.0"
-
-[package.extras]
-bokeh = ["bokeh", "selenium"]
-docs = ["furo", "sphinx (>=7.2)", "sphinx-copybutton"]
-mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.6.1)", "types-Pillow"]
-test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
-test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
-
-[[package]]
-name = "coverage"
-version = "7.4.1"
-description = "Code coverage measurement for Python"
-category = "dev"
-optional = false
-python-versions = ">=3.8"
-
-[package.dependencies]
-tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.11.0a6\" and extra == \"toml\""}
-
-[package.extras]
-toml = ["tomli"]
-
-[[package]]
-name = "cycler"
-version = "0.12.1"
-description = "Composable style cycles"
-category = "main"
-optional = false
-python-versions = ">=3.8"
-
-[package.extras]
-docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
-tests = ["pytest", "pytest-cov", "pytest-xdist"]
-
-[[package]]
-name = "einops"
-version = "0.7.0"
-description = "A new flavour of deep learning operations"
-category = "main"
-optional = false
-python-versions = ">=3.8"
-
-[[package]]
-name = "filelock"
-version = "3.13.1"
-description = "A platform independent file lock."
-category = "main"
-optional = false
-python-versions = ">=3.8"
-
-[package.extras]
-docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.24)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
-typing = ["typing-extensions (>=4.8)"]
-
-[[package]]
-name = "fonttools"
-version = "4.47.2"
-description = "Tools to manipulate font files"
-category = "main"
-optional = false
-python-versions = ">=3.8"
-
-[package.extras]
-all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "pycairo", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=15.1.0)", "xattr", "zopfli (>=0.1.4)"]
-graphite = ["lz4 (>=1.7.4.2)"]
-interpolatable = ["munkres", "pycairo", "scipy"]
-lxml = ["lxml (>=4.0,<5)"]
-pathops = ["skia-pathops (>=0.5.0)"]
-plot = ["matplotlib"]
-repacker = ["uharfbuzz (>=0.23.0)"]
-symfont = ["sympy"]
-type1 = ["xattr"]
-ufo = ["fs (>=2.2.0,<3)"]
-unicode = ["unicodedata2 (>=15.1.0)"]
-woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
-
-[[package]]
-name = "gdown"
-version = "4.7.3"
-description = "Google Drive direct download of big files."
-category = "main"
-optional = false
-python-versions = "*"
-
-[package.dependencies]
-beautifulsoup4 = "*"
-filelock = "*"
-requests = {version = "*", extras = ["socks"]}
-six = "*"
-tqdm = "*"
-
-[[package]]
-name = "idna"
-version = "3.6"
-description = "Internationalized Domain Names in Applications (IDNA)"
-category = "main"
-optional = false
-python-versions = ">=3.5"
-
-[[package]]
-name = "importlib-resources"
-version = "6.1.1"
-description = "Read resources from Python packages"
-category = "main"
-optional = false
-python-versions = ">=3.8"
-
-[package.dependencies]
-zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-ruff", "zipp (>=3.17)"]
-
-[[package]]
-name = "iniconfig"
-version = "2.0.0"
-description = "brain-dead simple config-ini parsing"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-
-[[package]]
-name = "itermate"
-version = "1.0.2"
-description = "Iterator-tools for functional programming."
-category = "dev"
-optional = false
-python-versions = "*"
-
-[[package]]
-name = "joblib"
-version = "1.3.2"
-description = "Lightweight pipelining with Python functions"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-
-[[package]]
-name = "kiwisolver"
-version = "1.4.5"
-description = "A fast implementation of the Cassowary constraint solver"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-
-[[package]]
-name = "markdown-it-py"
-version = "3.0.0"
-description = "Python port of markdown-it. Markdown parsing, done right!"
-category = "main"
-optional = false
-python-versions = ">=3.8"
-
-[package.dependencies]
-mdurl = ">=0.1,<1.0"
-
-[package.extras]
-benchmarking = ["psutil", "pytest", "pytest-benchmark"]
-code_style = ["pre-commit (>=3.0,<4.0)"]
-compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0,<2.0)", "mistune (>=2.0,<3.0)", "panflute (>=2.3,<3.0)"]
-linkify = ["linkify-it-py (>=1,<3)"]
-plugins = ["mdit-py-plugins"]
-profiling = ["gprof2dot"]
-rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
-testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
-
-[[package]]
-name = "matplotlib"
-version = "3.8.2"
-description = "Python plotting package"
-category = "main"
-optional = false
-python-versions = ">=3.9"
-
-[package.dependencies]
-contourpy = ">=1.0.1"
-cycler = ">=0.10"
-fonttools = ">=4.22.0"
-importlib-resources = {version = ">=3.2.0", markers = "python_version < \"3.10\""}
-kiwisolver = ">=1.3.1"
-numpy = ">=1.21,<2"
-packaging = ">=20.0"
-pillow = ">=8"
-pyparsing = ">=2.3.1"
-python-dateutil = ">=2.7"
-
-[[package]]
-name = "mdurl"
-version = "0.1.2"
-description = "Markdown URL utilities"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-
-[[package]]
-name = "numpy"
-version = "1.26.3"
-description = "Fundamental package for array computing in Python"
-category = "main"
-optional = false
-python-versions = ">=3.9"
-
-[[package]]
-name = "packaging"
-version = "23.2"
-description = "Core utilities for Python packages"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-
-[[package]]
-name = "pandas"
-version = "1.5.3"
-description = "Powerful data structures for data analysis, time series, and statistics"
-category = "main"
-optional = false
-python-versions = ">=3.8"
-
-[package.dependencies]
-numpy = [
-    {version = ">=1.20.3", markers = "python_version < \"3.10\""},
-    {version = ">=1.21.0", markers = "python_version >= \"3.10\""},
-    {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
-]
-python-dateutil = ">=2.8.1"
-pytz = ">=2020.1"
-
-[package.extras]
-test = ["hypothesis (>=5.5.3)", "pytest (>=6.0)", "pytest-xdist (>=1.31)"]
-
-[[package]]
-name = "pillow"
-version = "9.5.0"
-description = "Python Imaging Library (Fork)"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-
-[package.extras]
-docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-removed-in", "sphinxext-opengraph"]
-tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
-
-[[package]]
-name = "pluggy"
-version = "1.4.0"
-description = "plugin and hook calling mechanisms for python"
-category = "dev"
-optional = false
-python-versions = ">=3.8"
-
-[package.extras]
-dev = ["pre-commit", "tox"]
-testing = ["pytest", "pytest-benchmark"]
-
-[[package]]
-name = "py"
-version = "1.11.0"
-description = "library with cross-python path, ini-parsing, io, code, log facilities"
-category = "dev"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
-
-[[package]]
-name = "Pygments"
-version = "2.17.2"
-description = "Pygments is a syntax highlighting package written in Python."
-category = "main"
-optional = false
-python-versions = ">=3.7"
-
-[package.extras]
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-    {file = "torch-1.12.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:6cf6f54b43c0c30335428195589bd00e764a6d27f3b9ba637aaa8c11aaf93073"},
-    {file = "torch-1.12.1-cp39-cp39-win_amd64.whl", hash = "sha256:f00c721f489089dc6364a01fd84906348fe02243d0af737f944fddb36003400d"},
-    {file = "torch-1.12.1-cp39-none-macosx_10_9_x86_64.whl", hash = "sha256:bfec2843daa654f04fda23ba823af03e7b6f7650a873cdb726752d0e3718dada"},
-    {file = "torch-1.12.1-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:69fe2cae7c39ccadd65a123793d30e0db881f1c1927945519c5c17323131437e"},
-]
-torchmetrics = [
-    {file = "torchmetrics-0.10.3-py3-none-any.whl", hash = "sha256:b12cf92897545e24a825b0d168888c0f3052700c2901e2d4f7d90b252bc4a343"},
-    {file = "torchmetrics-0.10.3.tar.gz", hash = "sha256:9e6ab66175f2dc13e246c37485b2c27c77931dfe47fc2b81c76217b8efdc1e57"},
-]
-torchvision = [
-    {file = "torchvision-0.13.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:19286a733c69dcbd417b86793df807bd227db5786ed787c17297741a9b0d0fc7"},
-    {file = "torchvision-0.13.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:08f592ea61836ebeceb5c97f4d7a813b9d7dc651bbf7ce4401563ccfae6a21fc"},
-    {file = "torchvision-0.13.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:ef5fe3ec1848123cd0ec74c07658192b3147dcd38e507308c790d5943e87b88c"},
-    {file = "torchvision-0.13.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:099874088df104d54d8008f2a28539ca0117b512daed8bf3c2bbfa2b7ccb187a"},
-    {file = "torchvision-0.13.1-cp310-cp310-win_amd64.whl", hash = "sha256:8e4d02e4d8a203e0c09c10dfb478214c224d080d31efc0dbf36d9c4051f7f3c6"},
-    {file = "torchvision-0.13.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:5e631241bee3661de64f83616656224af2e3512eb2580da7c08e08b8c965a8ac"},
-    {file = "torchvision-0.13.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:899eec0b9f3b99b96d6f85b9aa58c002db41c672437677b553015b9135b3be7e"},
-    {file = "torchvision-0.13.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:83e9e2457f23110fd53b0177e1bc621518d6ea2108f570e853b768ce36b7c679"},
-    {file = "torchvision-0.13.1-cp37-cp37m-win_amd64.whl", hash = "sha256:7552e80fa222252b8b217a951c85e172a710ea4cad0ae0c06fbb67addece7871"},
-    {file = "torchvision-0.13.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:f230a1a40ed70d51e463ce43df243ec520902f8725de2502e485efc5eea9d864"},
-    {file = "torchvision-0.13.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:e9a563894f9fa40692e24d1aa58c3ef040450017cfed3598ff9637f404f3fe3b"},
-    {file = "torchvision-0.13.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:7cb789ceefe6dcd0dc8eeda37bfc45efb7cf34770eac9533861d51ca508eb5b3"},
-    {file = "torchvision-0.13.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:87c137f343197769a51333076e66bfcd576301d2cd8614b06657187c71b06c4f"},
-    {file = "torchvision-0.13.1-cp38-cp38-win_amd64.whl", hash = "sha256:4d8bf321c4380854ef04613935fdd415dce29d1088a7ff99e06e113f0efe9203"},
-    {file = "torchvision-0.13.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:0298bae3b09ac361866088434008d82b99d6458fe8888c8df90720ef4b347d44"},
-    {file = "torchvision-0.13.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c5ed609c8bc88c575226400b2232e0309094477c82af38952e0373edef0003fd"},
-    {file = "torchvision-0.13.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:3567fb3def829229ec217c1e38f08c5128ff7fb65854cac17ebac358ff7aa309"},
-    {file = "torchvision-0.13.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:b167934a5943242da7b1e59318f911d2d253feeca0d13ad5d832b58eed943401"},
-    {file = "torchvision-0.13.1-cp39-cp39-win_amd64.whl", hash = "sha256:0e77706cc90462653620e336bb90daf03d7bf1b88c3a9a3037df8d111823a56e"},
-]
-tqdm = [
-    {file = "tqdm-4.66.1-py3-none-any.whl", hash = "sha256:d302b3c5b53d47bce91fea46679d9c3c6508cf6332229aa1e7d8653723793386"},
-    {file = "tqdm-4.66.1.tar.gz", hash = "sha256:d88e651f9db8d8551a62556d3cff9e3034274ca5d66e93197cf2490e2dcb69c7"},
-]
-typing-extensions = [
-    {file = "typing_extensions-4.9.0-py3-none-any.whl", hash = "sha256:af72aea155e91adfc61c3ae9e0e342dbc0cba726d6cba4b6c72c1f34e47291cd"},
-    {file = "typing_extensions-4.9.0.tar.gz", hash = "sha256:23478f88c37f27d76ac8aee6c905017a143b0b1b886c3c9f66bc2fd94f9f5783"},
-]
-unfoldNd = [
-    {file = "unfoldNd-0.2.1-py3-none-any.whl", hash = "sha256:5d9a7f23e9004127486eb8c58f18025529b106ad407e6271ab57f13d910a7458"},
-    {file = "unfoldNd-0.2.1.tar.gz", hash = "sha256:3d91e0e6006d1ab45702db4b36f28e6150aef11c96d46331a273efe963e5efef"},
-]
-urllib3 = [
-    {file = "urllib3-2.1.0-py3-none-any.whl", hash = "sha256:55901e917a5896a349ff771be919f8bd99aff50b79fe58fec595eb37bbc56bb3"},
-    {file = "urllib3-2.1.0.tar.gz", hash = "sha256:df7aa8afb0148fa78488e7899b2c59b5f4ffcfa82e6c54ccb9dd37c1d7b52d54"},
-]
-where = [
-    {file = "where-1.0.2-py2.py3-none-any.whl", hash = "sha256:66abc8edf95be7516e949d08a771f25acacff708ef481618562ab484fe5bc63e"},
-    {file = "where-1.0.2.zip", hash = "sha256:325ef3a492a26189a47819f7375bc146887d39edd36fce132e86514334803fb1"},
-]
-zipp = [
-    {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"},
-    {file = "zipp-3.17.0.tar.gz", hash = "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"},
-]

From c546ae945874d22aaaa04552fc7749fd37cc0581 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Mon, 1 Jul 2024 15:29:20 +0200
Subject: [PATCH 117/273] update requirments.txt using poetry

---
 requirements.txt | 53 ++++++++++++++++++++++++------------------------
 1 file changed, 27 insertions(+), 26 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index 88c294a6e..fc2fc3fd3 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,45 +1,46 @@
 backpack-for-pytorch==1.6.0 ; python_version >= "3.9" and python_version < "4.0"
 beautifulsoup4==4.12.3 ; python_version >= "3.9" and python_version < "4.0"
-certifi==2023.11.17 ; python_version >= "3.9" and python_version < "4.0"
+certifi==2024.6.2 ; python_version >= "3.9" and python_version < "4.0"
 charset-normalizer==3.3.2 ; python_version >= "3.9" and python_version < "4.0"
 colorama==0.4.6 ; python_version >= "3.9" and python_version < "4.0" and platform_system == "Windows"
-contourpy==1.2.0 ; python_version >= "3.9" and python_version < "4.0"
+contourpy==1.2.1 ; python_version >= "3.9" and python_version < "4.0"
 cycler==0.12.1 ; python_version >= "3.9" and python_version < "4.0"
-einops==0.7.0 ; python_version >= "3.9" and python_version < "4.0"
-filelock==3.13.1 ; python_version >= "3.9" and python_version < "4.0"
-fonttools==4.47.2 ; python_version >= "3.9" and python_version < "4.0"
+einops==0.8.0 ; python_version >= "3.9" and python_version < "4.0"
+filelock==3.15.4 ; python_version >= "3.9" and python_version < "4.0"
+fonttools==4.53.0 ; python_version >= "3.9" and python_version < "4.0"
 gdown==4.7.3 ; python_version >= "3.9" and python_version < "4.0"
-idna==3.6 ; python_version >= "3.9" and python_version < "4.0"
-importlib-resources==6.1.1 ; python_version >= "3.9" and python_version < "3.10"
-joblib==1.3.2 ; python_version >= "3.9" and python_version < "4.0"
+idna==3.7 ; python_version >= "3.9" and python_version < "4.0"
+importlib-resources==6.4.0 ; python_version >= "3.9" and python_version < "3.10"
+joblib==1.4.2 ; python_version >= "3.9" and python_version < "4.0"
 kiwisolver==1.4.5 ; python_version >= "3.9" and python_version < "4.0"
 markdown-it-py==3.0.0 ; python_version >= "3.9" and python_version < "4.0"
-matplotlib==3.8.2 ; python_version >= "3.9" and python_version < "4.0"
+matplotlib==3.9.0 ; python_version >= "3.9" and python_version < "4.0"
 mdurl==0.1.2 ; python_version >= "3.9" and python_version < "4.0"
-numpy==1.26.3 ; python_version < "4.0" and python_version >= "3.9"
-packaging==23.2 ; python_version >= "3.9" and python_version < "4.0"
+numpy==1.26.4 ; python_version < "4.0" and python_version >= "3.9"
+packaging==24.1 ; python_version >= "3.9" and python_version < "4.0"
 pandas==1.5.3 ; python_version >= "3.9" and python_version < "4.0"
 pillow==9.5.0 ; python_version >= "3.9" and python_version < "4.0"
-pygments==2.17.2 ; python_version >= "3.9" and python_version < "4.0"
-pyparsing==3.1.1 ; python_version >= "3.9" and python_version < "4.0"
+pygments==2.18.0 ; python_version >= "3.9" and python_version < "4.0"
+pyparsing==3.1.2 ; python_version >= "3.9" and python_version < "4.0"
 pysocks==1.7.1 ; python_version >= "3.9" and python_version < "4.0"
-python-dateutil==2.8.2 ; python_version >= "3.9" and python_version < "4.0"
-pytz==2023.4 ; python_version >= "3.9" and python_version < "4.0"
+python-dateutil==2.9.0.post0 ; python_version >= "3.9" and python_version < "4.0"
+pytz==2024.1 ; python_version >= "3.9" and python_version < "4.0"
 pyyaml==6.0.1 ; python_version >= "3.9" and python_version < "4.0"
-requests==2.31.0 ; python_version >= "3.9" and python_version < "4.0"
-requests[socks]==2.31.0 ; python_version >= "3.9" and python_version < "4.0"
-rich==13.7.0 ; python_version >= "3.9" and python_version < "4.0"
-scikit-learn==1.4.0 ; python_version >= "3.9" and python_version < "4.0"
-scipy==1.12.0 ; python_version >= "3.9" and python_version < "4.0"
+requests==2.32.3 ; python_version >= "3.9" and python_version < "4.0"
+requests[socks]==2.32.3 ; python_version >= "3.9" and python_version < "4.0"
+rich==13.7.1 ; python_version >= "3.9" and python_version < "4.0"
+scikit-learn==1.5.0 ; python_version >= "3.9" and python_version < "4.0"
+scipy==1.13.1 ; python_version >= "3.9" and python_version < "4.0"
 seaborn==0.12.2 ; python_version >= "3.9" and python_version < "4.0"
+setuptools==69.5.1 ; python_version >= "3.9" and python_version < "4.0"
 six==1.16.0 ; python_version >= "3.9" and python_version < "4.0"
 soupsieve==2.5 ; python_version >= "3.9" and python_version < "4.0"
-threadpoolctl==3.2.0 ; python_version >= "3.9" and python_version < "4.0"
+threadpoolctl==3.5.0 ; python_version >= "3.9" and python_version < "4.0"
 torch==1.12.1 ; python_version >= "3.9" and python_version < "4.0"
 torchmetrics==0.10.3 ; python_version >= "3.9" and python_version < "4.0"
 torchvision==0.13.1 ; python_version >= "3.9" and python_version < "4.0"
-tqdm==4.66.1 ; python_version >= "3.9" and python_version < "4.0"
-typing-extensions==4.9.0 ; python_version >= "3.9" and python_version < "4.0"
-unfoldnd==0.2.1 ; python_version >= "3.9" and python_version < "4.0"
-urllib3==2.1.0 ; python_version >= "3.9" and python_version < "4.0"
-zipp==3.17.0 ; python_version >= "3.9" and python_version < "3.10"
+tqdm==4.66.4 ; python_version >= "3.9" and python_version < "4.0"
+typing-extensions==4.12.2 ; python_version >= "3.9" and python_version < "4.0"
+unfoldnd==0.2.2 ; python_version >= "3.9" and python_version < "4.0"
+urllib3==2.2.2 ; python_version >= "3.9" and python_version < "4.0"
+zipp==3.19.2 ; python_version >= "3.9" and python_version < "3.10"

From 3b91f7054265222bb13adee8273ffc66400a23fc Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 2 Jul 2024 10:28:28 +0200
Subject: [PATCH 118/273] Update pyproject.toml

---
 pyproject.toml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 27303d5bd..07416486a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -11,8 +11,8 @@ authors = ["Xudong Sun <smilesun.east@gmail.com>", "Carla Feistner", "Alexej Gos
 python = "^3.9"
 setuptools = "^69.5.1"
 numpy = "^1.23.4"
-matplotlib = "^3.6.1"
-seaborn = "0.12.2"
+matplotlib = "^3.9.0"
+seaborn = "^0.13.2"
 torchmetrics = "^0.10.0"
 torch = "^1.12.0"
 torchvision = "^0.13.0"

From e67e212c0db298704143b51931a7d20ff85587fd Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 2 Jul 2024 10:55:20 +0200
Subject: [PATCH 119/273] Removed explicit pip version in ci, added comment
 about user starting seed and added comments to the utils function for the
 benchmark script

---
 .github/workflows/ci.yml      | 4 ++--
 run_benchmark_slurm.sh        | 7 ++++++-
 run_benchmark_standalone.sh   | 7 ++++++-
 scripts/sh_benchmark_utils.sh | 3 +++
 4 files changed, 17 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 9c1aec884..f1a4fa9b6 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -20,13 +20,13 @@ jobs:
         python-version: 3.10.7
     - name: Install dependencies
       run: |
-        python -m pip install --upgrade pip==24.0
+        python -m pip install --upgrade pip
         pip install -r requirements.txt
         pip install pytest pytest-cov pytest-shell
         python setup.py install
     - name: Install Python Poetry
       run: |
-        python -m pip install --upgrade pip==24.0
+        python -m pip install --upgrade pip
         pip install poetry
         poetry install --with dev
     - name: test if api works
diff --git a/run_benchmark_slurm.sh b/run_benchmark_slurm.sh
index 66e6a0464..91f316f45 100755
--- a/run_benchmark_slurm.sh
+++ b/run_benchmark_slurm.sh
@@ -9,7 +9,12 @@ logfile=$(create_log_file)
 echo "Configuration file: $CONFIGFILE"
 echo "verbose log: $logfile"
 
-# Configuring DOMAINLAB_CUDA_START_SEED
+# Check if the second argument is empty and provide feedback
+if [ -z "$2" ]; then
+    echo "argument 2: DOMAINLAB_CUDA_START_SEED empty, will set to 0"
+fi
+# Set DOMAINLAB_CUDA_START_SEED to the second command-line argument if provided,
+# otherwise, default to 0.
 DOMAINLAB_CUDA_START_SEED=${2:-0}
 export DOMAINLAB_CUDA_START_SEED
 echo "argument 2: DOMAINLAB_CUDA_START_SEED=$DOMAINLAB_CUDA_START_SEED"
diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index 297f8f5df..72214b340 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -10,7 +10,12 @@ logfile=$(create_log_file)
 echo "Configuration file: $CONFIGFILE"
 echo "verbose log: $logfile"
 
-# Configuring DOMAINLAB_CUDA_START_SEED
+# Check if the second argument is empty and provide feedback
+if [ -z "$2" ]; then
+    echo "argument 2: DOMAINLAB_CUDA_START_SEED empty, will set to 0"
+fi
+# Set DOMAINLAB_CUDA_START_SEED to the second command-line argument if provided,
+# otherwise, default to 0.
 DOMAINLAB_CUDA_START_SEED=${2:-0}
 export DOMAINLAB_CUDA_START_SEED
 echo "argument 2: DOMAINLAB_CUDA_START_SEED=$DOMAINLAB_CUDA_START_SEED"
diff --git a/scripts/sh_benchmark_utils.sh b/scripts/sh_benchmark_utils.sh
index 9253f8ebc..ef1b05876 100644
--- a/scripts/sh_benchmark_utils.sh
+++ b/scripts/sh_benchmark_utils.sh
@@ -2,10 +2,12 @@
 
 # This script contains common functions used in multiple scripts
 
+# Function to generate a timestamp
 timestamp() {
     date +"%Y-%m-%d_%H-%M-%S"
 }
 
+# Function to create a log file with a timestamp in the name
 create_log_file() {
     local logdir="zoutput/logs"
     mkdir -p "$logdir"
@@ -13,6 +15,7 @@ create_log_file() {
     echo "$logfile"
 }
 
+# Function to extract the output directory from a config file and append a timestamp to it
 extract_output_dir() {
     local config_file=$1
     local output_dir=$(awk '/output_dir:/ {print $2}' "$config_file")

From 1198eeb452cfbec047161e3d9a8186fb638a6018 Mon Sep 17 00:00:00 2001
From: Matteo Wohlrapp <matteo.wohlrapp@hpc-build01.scidom.de>
Date: Tue, 2 Jul 2024 12:33:36 +0200
Subject: [PATCH 120/273] Corrected doc for gamma_reg, added docstring to call
 method in argparser and specified input types

---
 docs/doc_usage_cmd.md   |  4 +++-
 domainlab/arg_parser.py | 16 +++++++++++++++-
 2 files changed, 18 insertions(+), 2 deletions(-)

diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index ee814fdd3..28325b5af 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -43,9 +43,11 @@ To run DomainLab, the minimum necessary parameters are:
       ```yaml
       gamma_reg:
         dann: 0.05
-        diva: 0.2
+        dial: 0.2
         default: 0.1 # value for every other instance
       ```  
+Gamma reg is available for the trainers, as well as the 
+dann and jigen model. 
 
 - **Early Stopping (`--es`):** Steps for early stopping.
 - **Random Seed (`--seed`):** Seed for reproducibility.
diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index 32faa48be..1b386c698 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -15,8 +15,22 @@
 class ParseValuesOrKeyValuePairs(argparse.Action):
     """Class used for arg parsing where values are provided in a key value format"""
 
-    def __call__(self, parser, namespace, values, option_string=None):
+    def __call__(self, parser: argparse.ArgumentParser,
+    namespace: argparse.Namespace, values: str, option_string: str = None):
+        """
+            Handle parsing of key value pairs, or a single value instead
+
+            Args:
+                parser (argparse.ArgumentParser): The ArgumentParser object.
+                namespace (argparse.Namespace): The namespace object to store parsed values.
+                values (str): The string containing key=value pairs or a single float value.
+                option_string (str, optional): The option string that triggered this action (unused).
+
+            Raises:
+                ValueError: If the values cannot be parsed to float.
+        """
         if "=" in values:
+            my_dict = {}        if "=" in values:
             my_dict = {}
             for kv in values.split(","):
                 k, v = kv.split("=")

From d1ccf46511628a8a440328851acbd6a2a0bb50ec Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 2 Jul 2024 12:37:58 +0200
Subject: [PATCH 121/273] Update task_pacs_aug.py, update path of PACS

---
 examples/tasks/task_pacs_aug.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/tasks/task_pacs_aug.py b/examples/tasks/task_pacs_aug.py
index e971bea8c..f57b03fc6 100644
--- a/examples/tasks/task_pacs_aug.py
+++ b/examples/tasks/task_pacs_aug.py
@@ -11,9 +11,9 @@
 from domainlab.tasks.utils_task import ImSize
 
 # change this to absolute directory where you have the raw images from PACS,
-G_PACS_RAW_PATH = "domainlab/zdata/pacs/PACS"
+G_PACS_RAW_PATH = "data/pacs/PACS"
 # domainlab repository contain already the file names in
-# domainlab/zdata/pacs_split folder of domainlab
+# domainlab/zdata/pacs_split folder of domainlab, but PACS dataset is too big to put into domainlab folder
 
 
 def get_task(na=None):

From 6acdfdd23429f581f09a70182c94287ab1bfd00b Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 2 Jul 2024 12:39:18 +0200
Subject: [PATCH 122/273] Update pacs_fbopt_fishr_erm.yaml

---
 examples/benchmark/pacs_fbopt_fishr_erm.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/benchmark/pacs_fbopt_fishr_erm.yaml b/examples/benchmark/pacs_fbopt_fishr_erm.yaml
index 721833e7b..f3c10eb2b 100644
--- a/examples/benchmark/pacs_fbopt_fishr_erm.yaml
+++ b/examples/benchmark/pacs_fbopt_fishr_erm.yaml
@@ -4,7 +4,7 @@ output_dir: zoutput/benchmarks/benchmark_fbopt_fishr_erm_pacs
 
 sampling_seed: 0
 startseed: 0
-endseed: 2
+endseed: 0
 
 test_domains:
   - sketch

From d60a789d1257b8449c34ae8bce0ef978c2e9e82d Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 2 Jul 2024 12:40:20 +0200
Subject: [PATCH 123/273] Update pacs_fbopt_fishr_erm.yaml

---
 examples/benchmark/pacs_fbopt_fishr_erm.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/benchmark/pacs_fbopt_fishr_erm.yaml b/examples/benchmark/pacs_fbopt_fishr_erm.yaml
index f3c10eb2b..781a2518e 100644
--- a/examples/benchmark/pacs_fbopt_fishr_erm.yaml
+++ b/examples/benchmark/pacs_fbopt_fishr_erm.yaml
@@ -13,8 +13,8 @@ domainlab_args:
   tpath: examples/tasks/task_pacs_aug.py
   dmem: False
   lr: 5e-5
-  epos: 500
-  epos_min: 200
+  epos: 10
+  epos_min: 2
   es: 5
   bs: 32
   san_check: False

From 976c25a5571d7ae9ba3dac9619bba96b186ffc1d Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 2 Jul 2024 12:59:08 +0200
Subject: [PATCH 124/273] Update task_pacs_aug.py, fix codacy

---
 examples/tasks/task_pacs_aug.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/examples/tasks/task_pacs_aug.py b/examples/tasks/task_pacs_aug.py
index f57b03fc6..0d334a45a 100644
--- a/examples/tasks/task_pacs_aug.py
+++ b/examples/tasks/task_pacs_aug.py
@@ -13,7 +13,8 @@
 # change this to absolute directory where you have the raw images from PACS,
 G_PACS_RAW_PATH = "data/pacs/PACS"
 # domainlab repository contain already the file names in
-# domainlab/zdata/pacs_split folder of domainlab, but PACS dataset is too big to put into domainlab folder
+# domainlab/zdata/pacs_split folder of domainlab, 
+# but PACS dataset is too big to put into domainlab folder
 
 
 def get_task(na=None):

From 97d93209dd7f36124778f324cd4f8a29ea9b714f Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 2 Jul 2024 13:48:03 +0200
Subject: [PATCH 125/273] Update arg_parser.py, update documentation , remove
 diva gamma_reg

---
 domainlab/arg_parser.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index 32faa48be..ce981e9f0 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -51,7 +51,10 @@ def mk_parser_main():
     parser.add_argument(
         "--gamma_reg",
         default=0.1,
-        help="weight of regularization loss, can specify per model as 'dann=1.0,diva=2.0'",
+        help="weight of regularization loss in the form of $$\ell(\cdot) + \mu \times R(\cdot)$$ \
+        can specify per model as 'default=3.0, dann=1.0,jigen=2.0', where default refer to gamma for trainer \
+        note diva is implemented $$\ell(\cdot) + \mu \times R(\cdot)$$ \
+        so diva does not have gamma_reg",
         action=ParseValuesOrKeyValuePairs
     )
 

From 05d228b6bc200856e9d3c312a12f840336a57595 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 2 Jul 2024 13:55:22 +0200
Subject: [PATCH 126/273] Update doc_usage_cmd.md, remove diva gamma_reg in doc

---
 docs/doc_usage_cmd.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index ee814fdd3..eba5720a1 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -29,7 +29,7 @@ To run DomainLab, the minimum necessary parameters are:
 
   - **Command Line Usage:**
     - For a single value: `python script.py --gamma_reg=0.1`
-    - For multiple values: `python script.py --gamma_reg='default=0.1,dann=0.05,diva=0.2'`
+    - For multiple values: `python script.py --gamma_reg='default=0.1,dann=0.05,jigen=0.2'`
 
   - **YAML Configuration:**
     - For a single value:

From 5c0f6b1ff091709d5cd1b2c43ca7d7e2e16ecd02 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 2 Jul 2024 13:56:06 +0200
Subject: [PATCH 127/273] Update doc_usage_cmd.md

---
 docs/doc_usage_cmd.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/doc_usage_cmd.md b/docs/doc_usage_cmd.md
index eba5720a1..e8b4f121b 100644
--- a/docs/doc_usage_cmd.md
+++ b/docs/doc_usage_cmd.md
@@ -43,7 +43,7 @@ To run DomainLab, the minimum necessary parameters are:
       ```yaml
       gamma_reg:
         dann: 0.05
-        diva: 0.2
+        jigen: 0.2
         default: 0.1 # value for every other instance
       ```  
 

From 31ce1ecb4f193a11052aa6798b57361d3c56046e Mon Sep 17 00:00:00 2001
From: MatteoWohlrapp <matteo@wohlrapp.online>
Date: Tue, 2 Jul 2024 15:09:11 +0200
Subject: [PATCH 128/273] fixed argparser syntax, renamed argument

---
 domainlab/arg_parser.py                     | 1 -
 domainlab/utils/hyperparameter_retrieval.py | 6 +++---
 2 files changed, 3 insertions(+), 4 deletions(-)

diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index 3abd471bb..1b8593e8f 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -30,7 +30,6 @@ def __call__(self, parser: argparse.ArgumentParser,
                 ValueError: If the values cannot be parsed to float.
         """
         if "=" in values:
-            my_dict = {}        if "=" in values:
             my_dict = {}
             for kv in values.split(","):
                 k, v = kv.split("=")
diff --git a/domainlab/utils/hyperparameter_retrieval.py b/domainlab/utils/hyperparameter_retrieval.py
index 9b3c97e7e..5a1960e2e 100644
--- a/domainlab/utils/hyperparameter_retrieval.py
+++ b/domainlab/utils/hyperparameter_retrieval.py
@@ -2,14 +2,14 @@
 retrieval for hyperparameters
 """
 
-def get_gamma_reg(args, model_name):
+def get_gamma_reg(args, component_name):
     """
     Retrieves either a shared gamma regularization, or individual ones for each specified object
     """
     gamma_reg = args.gamma_reg
     if isinstance(gamma_reg, dict):
-        if model_name in gamma_reg:
-            return gamma_reg[model_name]
+        if component_name in gamma_reg:
+            return gamma_reg[component_name]
         if 'default' in gamma_reg:
             return gamma_reg['default']
         raise ValueError("""If a gamma_reg dict is specified,

From 6392ac5c27b9e1df2fcb68da6c1fca55dd118e65 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 2 Jul 2024 15:36:39 +0200
Subject: [PATCH 129/273] Update vlcs_diva_mldg_dial.yaml

---
 examples/conf/vlcs_diva_mldg_dial.yaml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/examples/conf/vlcs_diva_mldg_dial.yaml b/examples/conf/vlcs_diva_mldg_dial.yaml
index 39286b66b..e24cfd22e 100644
--- a/examples/conf/vlcs_diva_mldg_dial.yaml
+++ b/examples/conf/vlcs_diva_mldg_dial.yaml
@@ -7,7 +7,8 @@ epos: 1                             # number of epochs
 trainer: mldg_dial                  # combine trainer MLDG and DIAL
 gamma_reg: 
   default: 1.0
-  dann: 1.5     
+  dann: 1.5
+# in this case, mldg and dial get the default gamma_reg value 1.0
 gamma_y: 700000.0                   # hyperparameter of diva
 gamma_d: 100000.0                   # hyperparameter of diva
 npath: examples/nets/resnet.py      # neural network for class classification

From 0d629194fa559e63abbc6c1eadbd0685d87f1c2a Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 2 Jul 2024 15:45:05 +0200
Subject: [PATCH 130/273] Update test_hyperparameter_retrieval.py, comments in
 unit test

---
 tests/test_hyperparameter_retrieval.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/tests/test_hyperparameter_retrieval.py b/tests/test_hyperparameter_retrieval.py
index cfc7b28f9..2295f0489 100644
--- a/tests/test_hyperparameter_retrieval.py
+++ b/tests/test_hyperparameter_retrieval.py
@@ -29,7 +29,9 @@ def test_get_gamma_reg_dict_value():
     args = parser.parse_args(['--gamma_reg', 'default=5.0,dann=1.0,jigen=2.0'])
     assert get_gamma_reg(args, 'dann') == 1.0
     assert get_gamma_reg(args, 'jigen') == 2.0
-    assert get_gamma_reg(args, 'nonexistent') == 5.0
+    assert get_gamma_reg(args, 'nonexistent') == 5.0  # if we implement other model/trainers, 
+    # since not specified in command line arguments, the new model/trainer called "nonexistent" should 
+    # get the default value 5.0. 
 
 def test_exception():
     """Test to not specify a default value"""

From bdf84c281b58946be0a3eff5dde54230c486bb06 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 2 Jul 2024 16:38:46 +0200
Subject: [PATCH 131/273] style

---
 tests/test_hyperparameter_retrieval.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/tests/test_hyperparameter_retrieval.py b/tests/test_hyperparameter_retrieval.py
index 2295f0489..a9a141329 100644
--- a/tests/test_hyperparameter_retrieval.py
+++ b/tests/test_hyperparameter_retrieval.py
@@ -29,9 +29,11 @@ def test_get_gamma_reg_dict_value():
     args = parser.parse_args(['--gamma_reg', 'default=5.0,dann=1.0,jigen=2.0'])
     assert get_gamma_reg(args, 'dann') == 1.0
     assert get_gamma_reg(args, 'jigen') == 2.0
-    assert get_gamma_reg(args, 'nonexistent') == 5.0  # if we implement other model/trainers, 
-    # since not specified in command line arguments, the new model/trainer called "nonexistent" should 
-    # get the default value 5.0. 
+    assert get_gamma_reg(args, 'nonexistent') == 5.0  # if we implement other
+    # model/trainers,
+    # since not specified in command line arguments, the new model/trainer
+    # called "nonexistent" should
+    # get the default value 5.0.
 
 def test_exception():
     """Test to not specify a default value"""

From 8d6a356369c154c187d90aef55c6da5158166d3b Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 5 Jul 2024 17:06:22 +0200
Subject: [PATCH 132/273] use commandline to specify enviornemnt variable

---
 run_benchmark_slurm.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/run_benchmark_slurm.sh b/run_benchmark_slurm.sh
index 72b8bbd83..36aeb7c8d 100755
--- a/run_benchmark_slurm.sh
+++ b/run_benchmark_slurm.sh
@@ -32,4 +32,4 @@ echo "Number of GPUs: $NUMBER_GPUS"
 echo "Results will be stored in: $results_dir"
 
 # Helmholtz
-snakemake --profile "examples/yaml/slurm" --config yaml_file="$CONFIGFILE" --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
\ No newline at end of file
+snakemake --config logdir="zoutput/benchmark/logs" --profile "examples/yaml/slurm" --config yaml_file="$CONFIGFILE" --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"

From 8182f5b4c9d7e4b1eb627062c2ffe5fb1450121e Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 5 Jul 2024 17:07:43 +0200
Subject: [PATCH 133/273] {log_dir}

---
 examples/yaml/slurm/config.yaml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/examples/yaml/slurm/config.yaml b/examples/yaml/slurm/config.yaml
index e180df74d..fb229c922 100644
--- a/examples/yaml/slurm/config.yaml
+++ b/examples/yaml/slurm/config.yaml
@@ -1,6 +1,6 @@
 # This yaml file has been adapted from https://github.com/jdblischak/smk-simple-slurm
 cluster:
-  mkdir -p zoutput/slurm_logs/{rule} &&
+  mkdir -p zoutput/{log_dir}/{rule} &&
   sbatch
     --partition=gpu_p
     --qos=gpu_normal
@@ -10,8 +10,8 @@ cluster:
     -c 2
     --mem=160G
     --job-name=smk-{rule}-{wildcards}
-    --output=zoutput/slurm_logs/{rule}/{rule}-{wildcards}-%j.out
-    --error=zoutput/slurm_logs/{rule}/{rule}-{wildcards}-%j.err
+    --output=zoutput/{log_dir}/{rule}/{rule}-{wildcards}-%j.out
+    --error=zoutput/{log_dir}/{rule}/{rule}-{wildcards}-%j.err
 default-resources:
   - partition=gpu_p
   - qos=gpu_normal

From 422aaa513257bf1e2d4f37e011735b84f13c96fc Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Mon, 8 Jul 2024 15:36:40 +0200
Subject: [PATCH 134/273] define resources in each rule

---
 domainlab/exp_protocol/benchmark.smk | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/domainlab/exp_protocol/benchmark.smk b/domainlab/exp_protocol/benchmark.smk
index fcc9eb4f3..d33f29a59 100644
--- a/domainlab/exp_protocol/benchmark.smk
+++ b/domainlab/exp_protocol/benchmark.smk
@@ -72,6 +72,8 @@ rule parameter_sampling:
         expand("{path}", path=config_path)
     output:
         dest=expand("{output_dir}/hyperparameters.csv", output_dir=config["output_dir"])
+    resources:
+        log_dir="slurm_logs_test"
     params:
         sampling_seed=os.environ["DOMAINLAB_CUDA_HYPERPARAM_SEED"]
     run:
@@ -107,6 +109,8 @@ rule parameter_sampling:
 rule run_experiment:
     input:
         param_file=rules.parameter_sampling.output
+    resources:
+        log_dir="slurm_logs_test"
     output:
         # snakemake keyword temporary for temporary directory
         # like f-string in python {index} is generated in the run block as wildcards
@@ -159,6 +163,8 @@ rule agg_results:
     # put different csv file in a big csv file
     input:
         exp_results=experiment_result_files
+    resources:
+        log_dir="slurm_logs_test"
     output:
         out_file=expand("{output_dir}/results.csv", output_dir=config["output_dir"])
     run:

From 75d3aca73b8951acbbdda061c3f9dd129b451433 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 11 Jul 2024 11:54:08 +0200
Subject: [PATCH 135/273] slurm custom dir works

---
 examples/yaml/slurm/config.yaml | 6 +++---
 run_benchmark_slurm.sh          | 5 ++++-
 2 files changed, 7 insertions(+), 4 deletions(-)

diff --git a/examples/yaml/slurm/config.yaml b/examples/yaml/slurm/config.yaml
index fb229c922..6775d8a75 100644
--- a/examples/yaml/slurm/config.yaml
+++ b/examples/yaml/slurm/config.yaml
@@ -1,6 +1,6 @@
 # This yaml file has been adapted from https://github.com/jdblischak/smk-simple-slurm
 cluster:
-  mkdir -p zoutput/{log_dir}/{rule} &&
+  mkdir -p $logdir/{rule} &&
   sbatch
     --partition=gpu_p
     --qos=gpu_normal
@@ -10,8 +10,8 @@ cluster:
     -c 2
     --mem=160G
     --job-name=smk-{rule}-{wildcards}
-    --output=zoutput/{log_dir}/{rule}/{rule}-{wildcards}-%j.out
-    --error=zoutput/{log_dir}/{rule}/{rule}-{wildcards}-%j.err
+    --output=zoutput/$logdir/{rule}/{rule}-{wildcards}-%j.out
+    --error=zoutput/$logdir/{rule}/{rule}-{wildcards}-%j.err
 default-resources:
   - partition=gpu_p
   - qos=gpu_normal
diff --git a/run_benchmark_slurm.sh b/run_benchmark_slurm.sh
index 36aeb7c8d..5ad2b94ff 100755
--- a/run_benchmark_slurm.sh
+++ b/run_benchmark_slurm.sh
@@ -32,4 +32,7 @@ echo "Number of GPUs: $NUMBER_GPUS"
 echo "Results will be stored in: $results_dir"
 
 # Helmholtz
-snakemake --config logdir="zoutput/benchmark/logs" --profile "examples/yaml/slurm" --config yaml_file="$CONFIGFILE" --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"
+export logdir="${results_dir}/slurm_logs/"
+echo "slurm logs going into ${logdir}"
+# snakemake --config logdir="zoutput/benchmark/logs" does not seem to work
+snakemake --profile "examples/yaml/slurm" --config yaml_file="$CONFIGFILE" --keep-going --keep-incomplete --notemp --cores 3 -s "domainlab/exp_protocol/benchmark.smk" --configfile "$CONFIGFILE" --config output_dir="$results_dir" 2>&1 | tee "$logfile"

From eb445cb93cf5c42b532e03b74d5636a293cb343a Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 11 Jul 2024 14:44:29 +0200
Subject: [PATCH 136/273] Update benchmark.smk

---
 domainlab/exp_protocol/benchmark.smk | 10 ++++------
 1 file changed, 4 insertions(+), 6 deletions(-)

diff --git a/domainlab/exp_protocol/benchmark.smk b/domainlab/exp_protocol/benchmark.smk
index d33f29a59..84661ee61 100644
--- a/domainlab/exp_protocol/benchmark.smk
+++ b/domainlab/exp_protocol/benchmark.smk
@@ -72,8 +72,8 @@ rule parameter_sampling:
         expand("{path}", path=config_path)
     output:
         dest=expand("{output_dir}/hyperparameters.csv", output_dir=config["output_dir"])
-    resources:
-        log_dir="slurm_logs_test"
+    # resources:
+    #    log_dir="slurm_logs_test"
     params:
         sampling_seed=os.environ["DOMAINLAB_CUDA_HYPERPARAM_SEED"]
     run:
@@ -109,8 +109,6 @@ rule parameter_sampling:
 rule run_experiment:
     input:
         param_file=rules.parameter_sampling.output
-    resources:
-        log_dir="slurm_logs_test"
     output:
         # snakemake keyword temporary for temporary directory
         # like f-string in python {index} is generated in the run block as wildcards
@@ -163,8 +161,8 @@ rule agg_results:
     # put different csv file in a big csv file
     input:
         exp_results=experiment_result_files
-    resources:
-        log_dir="slurm_logs_test"
+    # resources:
+    #    log_dir="slurm_logs_test"
     output:
         out_file=expand("{output_dir}/results.csv", output_dir=config["output_dir"])
     run:

From bac7907ca513a450c416bac898165ff3f210c687 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 11 Jul 2024 14:47:16 +0200
Subject: [PATCH 137/273] Update config.yaml

---
 examples/yaml/slurm/config.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/yaml/slurm/config.yaml b/examples/yaml/slurm/config.yaml
index 6775d8a75..642367adc 100644
--- a/examples/yaml/slurm/config.yaml
+++ b/examples/yaml/slurm/config.yaml
@@ -10,8 +10,8 @@ cluster:
     -c 2
     --mem=160G
     --job-name=smk-{rule}-{wildcards}
-    --output=zoutput/$logdir/{rule}/{rule}-{wildcards}-%j.out
-    --error=zoutput/$logdir/{rule}/{rule}-{wildcards}-%j.err
+    --output=$logdir/{rule}/{rule}-{wildcards}-%j.out
+    --error=$logdir/{rule}/{rule}-{wildcards}-%j.err
 default-resources:
   - partition=gpu_p
   - qos=gpu_normal

From d72a8e45b205eefcd01468d7160244e04d7211c4 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 11 Jul 2024 14:58:44 +0200
Subject: [PATCH 138/273] update doc

---
 docs/doc_benchmark.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/doc_benchmark.md b/docs/doc_benchmark.md
index 41b19bffb..ec73fb36e 100644
--- a/docs/doc_benchmark.md
+++ b/docs/doc_benchmark.md
@@ -74,10 +74,10 @@ hyperparameter sampling and pytorch.
 The following script will help to find out which job has failed and the error message, so that you could direct to the
 specific log file
 ```cluster
-bash ./sh_list_error.sh ./zoutput/slurm_logs
+bash ./sh_list_error.sh ./zoutput/benchmarks/[output folder of the sepcifed benchmark in the yaml file]/slurm_logs
 ```
 #### Map between slurm job id and sampled hyperparameter index
-suppose the slurm job id is 14144163, one could the corresponding log file in `./zoutput/slurm_logs` folder via
+suppose the slurm job id is 14144163, one could the corresponding log file in `./zoutput/[output folder of the sepcifed benchmark in the yaml file]/slurm_logs` folder via
 `find . | grep -i "14144163"`
 
 the results can be

From e4a09bd12a6682f4186439d843d472fbaa7c5adc Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 11 Jul 2024 15:04:39 +0200
Subject: [PATCH 139/273] 0.6.5 slrum logs custom dir

---
 pyproject.toml | 2 +-
 setup.py       | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 07416486a..fa64c0b81 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "domainlab"
-version = "0.6.4"
+version = "0.6.5"
 readme = "README.md"
 repository = "https://github.com/marrlab/DomainLab"
 homepage = "https://marrlab.github.io/DomainLab/"
diff --git a/setup.py b/setup.py
index c56a64115..3738e48e7 100644
--- a/setup.py
+++ b/setup.py
@@ -38,7 +38,7 @@ def copy_dir(dir_path="zdata"):
     package_data={
         "zdata": [f for f in copy_dir()],
     },
-    version="0.6.4",
+    version="0.6.5",
     description="Library of modular domain generalization for deep learning",
     url="https://github.com/marrlab/DomainLab",
     author="Xudong Sun, et.al.",

From 1aa3d200e3818023d003cf6026a05e6de3986a3d Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 12 Jul 2024 14:42:44 +0200
Subject: [PATCH 140/273]  let snakemake lmajor jog file be in benchmark
 directory

---
 run_benchmark_slurm.sh        | 6 ++++--
 scripts/sh_benchmark_utils.sh | 2 +-
 2 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/run_benchmark_slurm.sh b/run_benchmark_slurm.sh
index 5ad2b94ff..81bcc2583 100755
--- a/run_benchmark_slurm.sh
+++ b/run_benchmark_slurm.sh
@@ -5,9 +5,7 @@ source scripts/sh_benchmark_utils.sh
 
 # CONFIGFILE="examples/yaml/test_helm_benchmark.yaml"
 CONFIGFILE=$1
-logfile=$(create_log_file)
 echo "Configuration file: $CONFIGFILE"
-echo "verbose log: $logfile"
 
 # Check if the second argument is empty and provide feedback
 if [ -z "$2" ]; then
@@ -31,6 +29,10 @@ echo "Hyperparameter seed is: $DOMAINLAB_CUDA_HYPERPARAM_SEED"
 echo "Number of GPUs: $NUMBER_GPUS"
 echo "Results will be stored in: $results_dir"
 
+logfile=$(create_log_file "$results_dir")
+echo "verbose log: $logfile"
+
+
 # Helmholtz
 export logdir="${results_dir}/slurm_logs/"
 echo "slurm logs going into ${logdir}"
diff --git a/scripts/sh_benchmark_utils.sh b/scripts/sh_benchmark_utils.sh
index ef1b05876..b8b214949 100644
--- a/scripts/sh_benchmark_utils.sh
+++ b/scripts/sh_benchmark_utils.sh
@@ -9,7 +9,7 @@ timestamp() {
 
 # Function to create a log file with a timestamp in the name
 create_log_file() {
-    local logdir="zoutput/logs"
+    local logdir="$1/snakemake_scheduler_logs"
     mkdir -p "$logdir"
     local logfile="$logdir/$(timestamp).out"
     echo "$logfile"

From a5e539181f9334d6384ef9137bde0dd1b93d54b9 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Fri, 12 Jul 2024 15:54:52 +0200
Subject: [PATCH 141/273] Update run_benchmark_standalone.sh

---
 run_benchmark_standalone.sh | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index 72214b340..8fa57c577 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -6,9 +6,7 @@ set -e
 source scripts/sh_benchmark_utils.sh
 
 CONFIGFILE=$1
-logfile=$(create_log_file)
 echo "Configuration file: $CONFIGFILE"
-echo "verbose log: $logfile"
 
 # Check if the second argument is empty and provide feedback
 if [ -z "$2" ]; then
@@ -37,6 +35,9 @@ echo "Hyperparameter seed is: $DOMAINLAB_CUDA_HYPERPARAM_SEED"
 echo "Number of GPUs: $NUMBER_GPUS"
 echo "Results will be stored in: $results_dir"
 
+logfile=$(create_log_file "$results_dir")
+echo "verbose log: $logfile"
+
 # -n: dry-run  (A dry run is a software testing process where the effects of a possible failure are intentionally mitigated, For example, there is rsync utility for transfer data over some interface, but user can try rsync with dry-run option to check syntax and test communication without data transferring.)
 # -p: print shell commands
 # -d: specify working directory. This should be the DomainLab dir

From 99ed0f11597d314cfbb3a188b7ae20cad948e107 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Fri, 12 Jul 2024 16:31:38 +0200
Subject: [PATCH 142/273] Update run_benchmark_standalone.sh

---
 run_benchmark_standalone.sh | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/run_benchmark_standalone.sh b/run_benchmark_standalone.sh
index 8fa57c577..b9a65dd66 100755
--- a/run_benchmark_standalone.sh
+++ b/run_benchmark_standalone.sh
@@ -38,6 +38,9 @@ echo "Results will be stored in: $results_dir"
 logfile=$(create_log_file "$results_dir")
 echo "verbose log: $logfile"
 
+# copy yaml file into the results folder
+cp $CONFIGFILE $results_dir
+
 # -n: dry-run  (A dry run is a software testing process where the effects of a possible failure are intentionally mitigated, For example, there is rsync utility for transfer data over some interface, but user can try rsync with dry-run option to check syntax and test communication without data transferring.)
 # -p: print shell commands
 # -d: specify working directory. This should be the DomainLab dir

From 7f7b4104f321f457327a4eb0e917c9d489a9d3ea Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sat, 13 Jul 2024 00:12:41 +0200
Subject: [PATCH 143/273] Update config.yaml: outputFolderAsJobName

---
 examples/yaml/slurm/config.yaml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/examples/yaml/slurm/config.yaml b/examples/yaml/slurm/config.yaml
index 642367adc..27f75a2d1 100644
--- a/examples/yaml/slurm/config.yaml
+++ b/examples/yaml/slurm/config.yaml
@@ -1,6 +1,8 @@
 # This yaml file has been adapted from https://github.com/jdblischak/smk-simple-slurm
 cluster:
   mkdir -p $logdir/{rule} &&
+  export parentfolder=$(dirname "$logdir") &&
+  export outputfolder=$(basename "$parentfolder")" &&
   sbatch
     --partition=gpu_p
     --qos=gpu_normal
@@ -9,7 +11,7 @@ cluster:
     -t 48:00:00
     -c 2
     --mem=160G
-    --job-name=smk-{rule}-{wildcards}
+    --job-name=outputfolder-{rule}-{wildcards}
     --output=$logdir/{rule}/{rule}-{wildcards}-%j.out
     --error=$logdir/{rule}/{rule}-{wildcards}-%j.err
 default-resources:

From c2d0427472e6d64c423b7bf6c6e96f77464db299 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sat, 13 Jul 2024 00:34:17 +0200
Subject: [PATCH 144/273] .

---
 examples/yaml/slurm/config.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/yaml/slurm/config.yaml b/examples/yaml/slurm/config.yaml
index 27f75a2d1..cc0f6901a 100644
--- a/examples/yaml/slurm/config.yaml
+++ b/examples/yaml/slurm/config.yaml
@@ -2,7 +2,7 @@
 cluster:
   mkdir -p $logdir/{rule} &&
   export parentfolder=$(dirname "$logdir") &&
-  export outputfolder=$(basename "$parentfolder")" &&
+  export outputfolder=$(basename "$parentfolder") &&
   sbatch
     --partition=gpu_p
     --qos=gpu_normal
@@ -11,7 +11,7 @@ cluster:
     -t 48:00:00
     -c 2
     --mem=160G
-    --job-name=outputfolder-{rule}-{wildcards}
+    --job-name=$outputfolder-{rule}-{wildcards}
     --output=$logdir/{rule}/{rule}-{wildcards}-%j.out
     --error=$logdir/{rule}/{rule}-{wildcards}-%j.err
 default-resources:

From ee30859df8f2a9af404696547b7209b98fdfa37d Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sat, 13 Jul 2024 00:41:47 +0200
Subject: [PATCH 145/273] Create slurm_status.sh

---
 slurm_status.sh | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 slurm_status.sh

diff --git a/slurm_status.sh b/slurm_status.sh
new file mode 100644
index 000000000..d60bbcdd9
--- /dev/null
+++ b/slurm_status.sh
@@ -0,0 +1 @@
+squeue --format="%.8i %.4P %.54j %.1u %.8T %.8M %.8l %.6D %R" -u $1

From 7d53d7e69be0796f3613db97937eb659ce4e0081 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sat, 13 Jul 2024 00:42:19 +0200
Subject: [PATCH 146/273] chmod slurm_status

---
 slurm_status.sh | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 mode change 100644 => 100755 slurm_status.sh

diff --git a/slurm_status.sh b/slurm_status.sh
old mode 100644
new mode 100755

From d6e5091ae4f38d2ee69e8b730bb8ab130fde0b14 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sat, 13 Jul 2024 00:59:54 +0200
Subject: [PATCH 147/273] .

---
 tests/dset_mnist_color_solo_default_test.py   | 32 +++++++++----------
 ...t_poly_domains_mnist_color_default_test.py |  2 +-
 2 files changed, 17 insertions(+), 17 deletions(-)

diff --git a/tests/dset_mnist_color_solo_default_test.py b/tests/dset_mnist_color_solo_default_test.py
index 76e32bfdb..454f305e8 100644
--- a/tests/dset_mnist_color_solo_default_test.py
+++ b/tests/dset_mnist_color_solo_default_test.py
@@ -6,45 +6,45 @@ def test_color_mnist():
     """
     test_color_mnist
     """
-    dset = DsetMNISTColorSoloDefault(0, "zout")
-    plot_ds(dset, "zout/color_solo.png")
+    dset = DsetMNISTColorSoloDefault(0, "zoutput")
+    plot_ds(dset, "zoutput/color_solo.png")
     ds_list = []
     for i in range(10):
-        ds_list.append(DsetMNISTColorSoloDefault(i, "zout"))
-    plot_ds_list(ds_list, "zout/color_0_9.png")
+        ds_list.append(DsetMNISTColorSoloDefault(i, "zoutput"))
+    plot_ds_list(ds_list, "zoutput/color_0_9.png")
 
 
 def test_color_mnist2():
     """
     test_color_mnist
     """
-    dset = DsetMNISTColorSoloDefault(0, "zout", flag_rand_color=True)
-    plot_ds(dset, "zout/color_solo.png")
+    dset = DsetMNISTColorSoloDefault(0, "zoutput", flag_rand_color=True)
+    plot_ds(dset, "zoutput/color_solo.png")
     ds_list = []
     for i in range(10):
-        ds_list.append(DsetMNISTColorSoloDefault(i, "zout"))
-    plot_ds_list(ds_list, "zout/color_0_9.png")
+        ds_list.append(DsetMNISTColorSoloDefault(i, "zoutput"))
+    plot_ds_list(ds_list, "zoutput/color_0_9.png")
 
 
 def test_color_mnist3():
     """
     test_color_mnist
     """
-    dset = DsetMNISTColorSoloDefault(0, "zout", color_scheme="num", raw_split="test")
-    plot_ds(dset, "zout/color_solo.png")
+    dset = DsetMNISTColorSoloDefault(0, "zoutput", color_scheme="num", raw_split="test")
+    plot_ds(dset, "zoutput/color_solo.png")
     ds_list = []
     for i in range(10):
-        ds_list.append(DsetMNISTColorSoloDefault(i, "zout"))
-    plot_ds_list(ds_list, "zout/color_0_9.png")
+        ds_list.append(DsetMNISTColorSoloDefault(i, "zoutput"))
+    plot_ds_list(ds_list, "zoutput/color_0_9.png")
 
 
 def test_color_mnist4():
     """
     test_color_mnist
     """
-    dset = DsetMNISTColorSoloDefault(0, "zout", color_scheme="back", raw_split="test")
-    plot_ds(dset, "zout/color_solo.png")
+    dset = DsetMNISTColorSoloDefault(0, "zoutput", color_scheme="back", raw_split="test")
+    plot_ds(dset, "zoutput/color_solo.png")
     ds_list = []
     for i in range(10):
-        ds_list.append(DsetMNISTColorSoloDefault(i, "zout"))
-    plot_ds_list(ds_list, "zout/color_0_9.png")
+        ds_list.append(DsetMNISTColorSoloDefault(i, "zoutput"))
+    plot_ds_list(ds_list, "zoutput/color_0_9.png")
diff --git a/tests/dset_poly_domains_mnist_color_default_test.py b/tests/dset_poly_domains_mnist_color_default_test.py
index 1e0661eca..b4c7d71fc 100644
--- a/tests/dset_poly_domains_mnist_color_default_test.py
+++ b/tests/dset_poly_domains_mnist_color_default_test.py
@@ -7,5 +7,5 @@
 
 
 def test_color_mnist():
-    dset = DsetMNISTColorMix(n_domains=3, path="./output/")
+    dset = DsetMNISTColorMix(n_domains=3, path="./zoutput/testsoutput")
     plot_ds(dset, "color_mix.png")

From 3dfd3a4427386d0aa05a98e60ed3e0a35b6c619b Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sat, 13 Jul 2024 01:07:58 +0200
Subject: [PATCH 148/273] Update ci.yml, rm -rf instead rm -r

---
 .github/workflows/ci.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index f1a4fa9b6..9d93b8530 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -32,7 +32,7 @@ jobs:
     - name: test if api works
       run: poetry run python examples/api/jigen_dann_transformer.py
     - name: Generate coverage report
-      run: rm -r zoutput && poetry run pytest --cov=domainlab tests/ --cov-report=xml
+      run: rm -rf zoutput && poetry run pytest --cov=domainlab tests/ --cov-report=xml
     - name: Upload coverage to Codecov
       uses: codecov/codecov-action@v1
       with:
@@ -42,7 +42,7 @@ jobs:
       env:
         CODECOV_TOKEN: 02ecb3ac-b7ce-4ea4-90a2-961c3d1a1030
     - name: check if readme yaml works
-      run: rm -r zoutput && python main_out.py -c ./examples/conf/vlcs_diva_mldg_dial.yaml
+      run: rm -rf zoutput && python main_out.py -c ./examples/conf/vlcs_diva_mldg_dial.yaml
     - name: test if examples in markdown works
       run: bash -x -v scripts/ci_run_examples.sh
     - name: test if benchmark works

From bfc8f13fbd248459826c7ae836a00d24ae3a6851 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sat, 13 Jul 2024 01:15:48 +0200
Subject: [PATCH 149/273] Update benchmark.smk

---
 domainlab/exp_protocol/benchmark.smk | 1 +
 1 file changed, 1 insertion(+)

diff --git a/domainlab/exp_protocol/benchmark.smk b/domainlab/exp_protocol/benchmark.smk
index 84661ee61..974c69cd7 100644
--- a/domainlab/exp_protocol/benchmark.smk
+++ b/domainlab/exp_protocol/benchmark.smk
@@ -109,6 +109,7 @@ rule parameter_sampling:
 rule run_experiment:
     input:
         param_file=rules.parameter_sampling.output
+    shell: "cat {input}"
     output:
         # snakemake keyword temporary for temporary directory
         # like f-string in python {index} is generated in the run block as wildcards

From a9f358e51074ebf191495bb790358f1e1b5efc82 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sat, 13 Jul 2024 01:21:13 +0200
Subject: [PATCH 150/273] Update a_observer.py: rm str_msel since plays no rule

---
 domainlab/algos/observers/a_observer.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/domainlab/algos/observers/a_observer.py b/domainlab/algos/observers/a_observer.py
index bdad57360..cbf8a86e0 100644
--- a/domainlab/algos/observers/a_observer.py
+++ b/domainlab/algos/observers/a_observer.py
@@ -13,7 +13,6 @@ def __init__(self):
         self.task = None
         self.device = None
         self.epo_te = None
-        self.str_msel = None
         self.keep_model = None
         self.loader_te = None
         self.loader_tr = None
@@ -26,7 +25,6 @@ def set_task(self, task, args, device):
         self.task = task
         self.device = device
         self.epo_te = args.epo_te
-        self.str_msel = args.msel  # FIXME: consistent with self.model_sel?
         self.keep_model = args.keep_model
         self.loader_te = self.task.loader_te
         self.loader_tr = self.task.loader_tr

From b673fbba23b8bf9bc6ecb2327c9af1e1b1ec0f18 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sat, 13 Jul 2024 01:32:28 +0200
Subject: [PATCH 151/273] Update doc_benchmark.md

---
 docs/doc_benchmark.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/docs/doc_benchmark.md b/docs/doc_benchmark.md
index ec73fb36e..908e7e487 100644
--- a/docs/doc_benchmark.md
+++ b/docs/doc_benchmark.md
@@ -98,6 +98,7 @@ via `tree -L 2` in `zoutput/benchmarks/[name of the benchmark defined in configu
 ```
 ├── commit.txt
 ├── config.txt
+├── [slurm_logs/]
 ├── graphics
 │   ├── diva_fbopt_full
 │   ├── radar_dist.png
@@ -163,7 +164,7 @@ Note that the cvs file must have the same form as the one generated by the fully
 
 
 
-| param_index | task | algo | epos | te_d | seed | params | acc | precision | recall | specificity | f1 | auroc |
+| param_index | method | algo | epos | te_d | seed | params | acc | precision | recall | specificity | f1 | auroc |
 |---|---|---|---|---|---|---|---|---|---|---|---|---|
 | 0 | ... | ... | ... | ... | ... | {'param1': p1, ...} | ... | ... | ... | ... | ... | ... |
 | 1 | ... | ... | ... | ... | ... | {'param1': p2, ...} | ... | ... | ... | ... | ... | ... |

From 3ca86addddd0920a77804955d510e5bf7b022691 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sun, 14 Jul 2024 23:30:46 +0200
Subject: [PATCH 152/273] Update benchmark.smk

---
 domainlab/exp_protocol/benchmark.smk | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/domainlab/exp_protocol/benchmark.smk b/domainlab/exp_protocol/benchmark.smk
index 974c69cd7..b54d8314c 100644
--- a/domainlab/exp_protocol/benchmark.smk
+++ b/domainlab/exp_protocol/benchmark.smk
@@ -109,7 +109,6 @@ rule parameter_sampling:
 rule run_experiment:
     input:
         param_file=rules.parameter_sampling.output
-    shell: "cat {input}"
     output:
         # snakemake keyword temporary for temporary directory
         # like f-string in python {index} is generated in the run block as wildcards
@@ -123,6 +122,7 @@ rule run_experiment:
     resources:
         nvidia_gpu=1
     run:
+        shell("cat {input}")
         from domainlab.exp_protocol.run_experiment import run_experiment
         # import sys
         # pos = None

From 1c683ba4055e6a3990d9948ef51624b7ec9133e9 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 16 Jul 2024 16:59:17 +0200
Subject: [PATCH 153/273] Update pacs_fbopt_dial_diva.yaml

---
 examples/benchmark/pacs_fbopt_dial_diva.yaml | 12 +++++-------
 1 file changed, 5 insertions(+), 7 deletions(-)

diff --git a/examples/benchmark/pacs_fbopt_dial_diva.yaml b/examples/benchmark/pacs_fbopt_dial_diva.yaml
index 3ac91d67d..02c664f71 100644
--- a/examples/benchmark/pacs_fbopt_dial_diva.yaml
+++ b/examples/benchmark/pacs_fbopt_dial_diva.yaml
@@ -35,10 +35,10 @@ Shared params:
     step: 0.05
     distribution: uniform
 
-  k_i_gain:
-    min: 0.0001
-    max: 0.01
-    num: 2
+  k_i_gain_ratio:
+    min: 0.01
+    max: 0.90
+    num: 3
     step: 0.0001
     distribution: uniform
   
@@ -78,11 +78,9 @@ dial_fbopt:
   trainer: fbopt_dial
   shared:
     - ini_setpoint_ratio
-    - k_i_gain
+    - k_i_gain_ratio
     - dial_lr 
     - dial_epsilon
-    - gamma_y
-    - gamma_d
 
 dial:
   model: diva

From 2a408ecdf1c73e1b5ee5def6a64a510565229574 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 12:52:31 +0200
Subject: [PATCH 154/273] doc for IRM

---
 docs/docIRM.md | 29 +++++++++++++++++++++++++++++
 1 file changed, 29 insertions(+)
 create mode 100644 docs/docIRM.md

diff --git a/docs/docIRM.md b/docs/docIRM.md
new file mode 100644
index 000000000..e6e419555
--- /dev/null
+++ b/docs/docIRM.md
@@ -0,0 +1,29 @@
+# Invariant Risk Minimization (IRM)
+
+Decompose a classification task into feature extraction $$\Phi(\cdot)$$ and classificaiton layer $$w(\cdot)$$, then the task loss is
+
+$$\ell^{(d)} (w \circ \Phi) = \mathbb{E}_{(X, Y) \sim \mathcal{D}_d}[\ell(w \circ \Phi(X), Y)]$$
+where we use $$\ell$$ to denote the cross entropy for a classification task, and $$\mathcal{D}_d$$ for distribution of domain $d$.
+
+The idea of IRM is to choose classifier $w$ to be in the intersection of optimal classifiers for each domain $$d$$.
+
+$$w \in \argmin_{\bar{w}} \ell^{(d)}(\bar{w} \circ \Phi) \quad \forall d$$
+
+regardless of feature extractor $$\Phi(\cdot)$$, this serves as a constraint on the choice of classifiers $w$.
+
+The feature extractor $$\Phi(\cdot)$$ then get optimized under this constraint.
+
+Thus IRM forms a bi-level optimization by jointly optimize $$\Phi$$ and $$w$$ which is hard to solve, so in practice IRMv1 is used. 
+
+## IRMv1
+
+In DomainLab, we write the loss function as $$\ell(\cdot) + \lambda R(\cdot)$$, which result in the optmization below:
+
+$$\min_{\Phi, w} \sum_{d} \ell^{(d)}(w \circ \Phi) + \lambda \sum_{d} \|\nabla_{w|w=1.0} \ell^{(d)}(w \circ \Phi)\|^2$$
+
+where $\lambda$ is a hyperparameter that controls the trade-off between the empirical risk and the penalty. One interpretation can be the penalty encourages the representation $\Phi$ to be small evaluated at $w = 1.0$ across all domains.
+
+In practice, one could simply divide one mini-batch into two subsets, let $i$ and $j$ to index these two subsets, multiply  subset $i$ and subset $j$ forms an unbiased estimation of the L2 norm of gradient.
+In detail: the squared gradient norm via inner product between $$\\nabla_{w|w=1} \\ell(w\\dot \\Phi(X^{(d, i)}), Y^{(d, i)})$$ of dimension dim(Grad) with $$\\nabla_{w|w=1} \\ell(w\\dot \\Phi(X^{(d, j)}), Y^{(d, j)})$$ of dimension dim(Grad) For more details, see section 3.2 and Appendix D of : Arjovsky et al., “Invariant Risk Minimization.”
+
+

From 9f73d67b226ced8dbb5bbcf92b895feed7ad9b3b Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 15:52:04 +0200
Subject: [PATCH 155/273] simple expoential moving aveage

---
 domainlab/algos/trainers/train_ema.py | 26 ++++++++++++++++++++++++++
 1 file changed, 26 insertions(+)
 create mode 100644 domainlab/algos/trainers/train_ema.py

diff --git a/domainlab/algos/trainers/train_ema.py b/domainlab/algos/trainers/train_ema.py
new file mode 100644
index 000000000..e71bc6da1
--- /dev/null
+++ b/domainlab/algos/trainers/train_ema.py
@@ -0,0 +1,26 @@
+import torch
+
+
+class MovingAverage:
+    def __init__(self, rho):
+        self.rho = rho
+        self.dict_para_ema_persist = {}
+        self._iter = 0
+
+    def update(self, dict_data):
+        dict_ema_para_curr_iter = {}
+        for key, data in dict_data.items():
+            data = data.view(1, -1)  # make it rank 1 tensor (a.k.a. vector)
+            if self._iter == 0:
+                previous_data = torch.zeros_like(data)
+            else:
+                previous_data = self.dict_para_ema_persist[key]
+
+            local_data_convex = self.rho * previous_data + (1 - self.rho) * data
+            # correction by 1/(1 - self.rho)
+            # so that the gradients amplitude backpropagated in data is independent of self.rho
+            dict_ema_para_curr_iter[key] = local_data_convex / (1 - self.rho)
+            self.dict_para_ema_persist[key] = local_data_convex.clone().detach()  # used as previous data
+
+        self._iter += 1
+        return dict_ema_para_curr_iter

From 97112a2827d08bad5bdc8ce5ed3476706726a3c9 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 16:57:37 +0200
Subject: [PATCH 156/273] move avarage rho set w.r.t. epoch

---
 domainlab/algos/trainers/a_trainer.py   |  6 ++-
 domainlab/algos/trainers/train_ema.py   | 71 ++++++++++++++++++++-----
 domainlab/algos/trainers/zoo_trainer.py |  2 +
 3 files changed, 64 insertions(+), 15 deletions(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index f5fce7c16..8af15bf25 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -84,6 +84,10 @@ def __init__(self, successor_node=None, extend=None):
         self.inner_trainer = None
         self.loader_tr_source_target = None
         self.flag_initialized = False
+        # moving average
+        self.ma_weight_previous_model_params = None
+        self._ma_dict_para_persist = {}
+        self._ma_iter = 0
 
     @property
     def model(self):
@@ -261,7 +265,7 @@ def dset_decoration_args_algo(self, args, ddset):
 
     def print_parameters(self):
         """
-        Function to print all parameters of the object. 
+        Function to print all parameters of the object.
         Can be used to print the parameters of any child class
         """
         params = vars(self)
diff --git a/domainlab/algos/trainers/train_ema.py b/domainlab/algos/trainers/train_ema.py
index e71bc6da1..118a5bfe9 100644
--- a/domainlab/algos/trainers/train_ema.py
+++ b/domainlab/algos/trainers/train_ema.py
@@ -1,26 +1,69 @@
+"""
+simple exponential moving average of each layers, after each epoch,
+trainer=ma_trainer2_trainer3
+always set ma to be outer most
+
+Paper:
+Ensemble of Averages: Improving Model Selection and
+Boosting Performance in Domain Generalization
+Devansh Arpit, Huan Wang, Yingbo Zhou, Caiming Xiong
+Salesforce Research, USA
+"""
+
 import torch
+from domainlab.algos.trainers.train_basic import TrainerBasic
 
 
-class MovingAverage:
-    def __init__(self, rho):
-        self.rho = rho
-        self.dict_para_ema_persist = {}
-        self._iter = 0
+class TrainerMA(TrainerBasic):
+    """
+    initializer of this class goes to one block/section in the abstract class
+    initializer, otherwise it will break the class inheritance.
+    """
+    def move_average(self, dict_data, epoch):
+        """
+        for each epoch, convex combine the weights for each layer
+        """
+        if self.ma_weight_previous_model_params is None:
+            """
+            Paper:
+            Ensemble of Averages: Improving Model Selection and
+            Boosting Performance in Domain Generalization
+            Devansh Arpit, Huan Wang, Yingbo Zhou, Caiming Xiong
+            Salesforce Research, USA
 
-    def update(self, dict_data):
+            """
+            if epoch < 2:
+                # see https://arxiv.org/pdf/2110.10832#page=13.16, figure 5
+                self.ma_weight_previous_model_params = 0
+            else:
+                self.ma_weight_previous_model_params = epoch / (epoch + 1)
+            # weight on previous model decrease as training goes on
         dict_ema_para_curr_iter = {}
         for key, data in dict_data.items():
-            data = data.view(1, -1)  # make it rank 1 tensor (a.k.a. vector)
-            if self._iter == 0:
+            # data = data.view(1, -1)  # make it rank 1 tensor (a.k.a. vector)
+            if self._ma_iter == 0:
                 previous_data = torch.zeros_like(data)
             else:
-                previous_data = self.dict_para_ema_persist[key]
+                previous_data = self._ma_dict_para_persist[key]
 
-            local_data_convex = self.rho * previous_data + (1 - self.rho) * data
+            local_data_convex = \
+                self.ma_weight_previous_model_params * previous_data + \
+                (1 - self.ma_weight_previous_model_params) * data
             # correction by 1/(1 - self.rho)
-            # so that the gradients amplitude backpropagated in data is independent of self.rho
-            dict_ema_para_curr_iter[key] = local_data_convex / (1 - self.rho)
-            self.dict_para_ema_persist[key] = local_data_convex.clone().detach()  # used as previous data
+            # so that the gradients amplitude backpropagated in data is
+            # independent of self.rho
+            dict_ema_para_curr_iter[key] = \
+                local_data_convex / (1 - self.ma_weight_previous_model_params)
+            self._ma_dict_para_persist[key] = \
+                local_data_convex.clone().detach()  # used as previous data
 
-        self._iter += 1
+        self._ma_iter += 1
         return dict_ema_para_curr_iter
+
+    def after_epoch(self, epoch):
+        torch_model = self.get_model()
+        dict_para = torch_model.state_dict()  # only for trainable parameters
+        new_dict_para = self.move_average(dict_para, epoch)
+        # without deepcopy, this seems to work
+        torch_model.load_state_dict(new_dict_para)
+        super().after_epoch(epoch)
diff --git a/domainlab/algos/trainers/zoo_trainer.py b/domainlab/algos/trainers/zoo_trainer.py
index 1800e307c..e4a8c7bd5 100644
--- a/domainlab/algos/trainers/zoo_trainer.py
+++ b/domainlab/algos/trainers/zoo_trainer.py
@@ -2,6 +2,7 @@
 select trainer
 """
 from domainlab.algos.trainers.train_basic import TrainerBasic
+from domainlab.algos.trainers.train_ema import TrainerMA
 from domainlab.algos.trainers.train_dial import TrainerDIAL
 from domainlab.algos.trainers.train_hyper_scheduler import TrainerHyperScheduler
 from domainlab.algos.trainers.train_matchdg import TrainerMatchDG
@@ -46,6 +47,7 @@ def __call__(self, lst_candidates=None, default=None, lst_excludes=None):
             )
 
         chain = TrainerBasic(None)
+        chain = TrainerMA(chain)
         chain = TrainerDIAL(chain)
         chain = TrainerMatchDG(chain)
         chain = TrainerMLDG(chain)

From bbac2b51cade112de5d7bd61a7f6a58fc34161c5 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 17:11:02 +0200
Subject: [PATCH 157/273] rmove if

---
 domainlab/algos/trainers/train_ema.py | 22 +++++++---------------
 1 file changed, 7 insertions(+), 15 deletions(-)

diff --git a/domainlab/algos/trainers/train_ema.py b/domainlab/algos/trainers/train_ema.py
index 118a5bfe9..10bb7e786 100644
--- a/domainlab/algos/trainers/train_ema.py
+++ b/domainlab/algos/trainers/train_ema.py
@@ -22,22 +22,14 @@ class TrainerMA(TrainerBasic):
     def move_average(self, dict_data, epoch):
         """
         for each epoch, convex combine the weights for each layer
+        Paper:
+        Ensemble of Averages: Improving Model Selection and
+        Boosting Performance in Domain Generalization
+        Devansh Arpit, Huan Wang, Yingbo Zhou, Caiming Xiong
+        Salesforce Research, USA
         """
-        if self.ma_weight_previous_model_params is None:
-            """
-            Paper:
-            Ensemble of Averages: Improving Model Selection and
-            Boosting Performance in Domain Generalization
-            Devansh Arpit, Huan Wang, Yingbo Zhou, Caiming Xiong
-            Salesforce Research, USA
-
-            """
-            if epoch < 2:
-                # see https://arxiv.org/pdf/2110.10832#page=13.16, figure 5
-                self.ma_weight_previous_model_params = 0
-            else:
-                self.ma_weight_previous_model_params = epoch / (epoch + 1)
-            # weight on previous model decrease as training goes on
+        self.ma_weight_previous_model_params = epoch / (epoch + 1)
+        # weight on previous model decrease as training goes on
         dict_ema_para_curr_iter = {}
         for key, data in dict_data.items():
             # data = data.view(1, -1)  # make it rank 1 tensor (a.k.a. vector)

From 8e8827c2c4c07a24264b298887d8de803205b8fe Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 17:14:59 +0200
Subject: [PATCH 158/273] .

---
 docs/docMA.md | 8 ++++++++
 1 file changed, 8 insertions(+)
 create mode 100644 docs/docMA.md

diff --git a/docs/docMA.md b/docs/docMA.md
new file mode 100644
index 000000000..991f5ad77
--- /dev/null
+++ b/docs/docMA.md
@@ -0,0 +1,8 @@
+# Simple Moving Average
+For each epoch, convex combine the weights for each layey from Paper: Ensemble of Averages: Improving Model Selection and
+Boosting Performance in Domain Generalization, Devansh Arpit, Huan Wang, Yingbo Zhou, Caiming Xiong, Salesforce Research, USA
+
+Example:
+```
+python main_out.py --te_d 0 1 --tr_d 3 5 --task=mnistcolor10 --epos=2 --bs=2 --model=erm --nname=conv_bn_pool_2 --trainer=ma
+``` 

From 2e66bbafa5c368f73b70ff437d577f00633fc45f Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 17:18:03 +0200
Subject: [PATCH 159/273] unit test move average

---
 tests/test_ma.py | 12 ++++++++++++
 1 file changed, 12 insertions(+)
 create mode 100644 tests/test_ma.py

diff --git a/tests/test_ma.py b/tests/test_ma.py
new file mode 100644
index 000000000..31b82ac3d
--- /dev/null
+++ b/tests/test_ma.py
@@ -0,0 +1,12 @@
+"""
+unit and end-end test for deep all, mldg
+"""
+from tests.utils_test import utils_test_algo
+
+
+def test_deepall_mldg():
+    """
+    train DeepAll with MLDG
+    """
+    args = "--te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm --trainer=ma --nname=alexnet"
+    utils_test_algo(args)

From 3d4a00b3cdd90e8ebe24ae9c462427d9ef5bcc63 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 17:19:28 +0200
Subject: [PATCH 160/273] add irm to doc

---
 docs/index.rst | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/index.rst b/docs/index.rst
index 96c8c7fe6..332084d98 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -19,6 +19,7 @@ Welcome to domainlab's documentation!
    docDIAL
    docFishr
    doc_mldg
+   docIRM
 
 
 Indices and tables

From 21361d8a130ba5b49216c8c6804617a5c256337c Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 17:24:27 +0200
Subject: [PATCH 161/273] .

---
 docs/docIRM.md | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/docs/docIRM.md b/docs/docIRM.md
index e6e419555..6be3a3ca0 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -1,19 +1,19 @@
 # Invariant Risk Minimization (IRM)
 
-Decompose a classification task into feature extraction $$\Phi(\cdot)$$ and classificaiton layer $$w(\cdot)$$, then the task loss is
+Decompose a classification task into feature extraction $\Phi(\cdot)$ and classificaiton layer $w(\cdot)$, then the task loss is
 
-$$\ell^{(d)} (w \circ \Phi) = \mathbb{E}_{(X, Y) \sim \mathcal{D}_d}[\ell(w \circ \Phi(X), Y)]$$
-where we use $$\ell$$ to denote the cross entropy for a classification task, and $$\mathcal{D}_d$$ for distribution of domain $d$.
+$\ell^{(d)} (w \circ \Phi) = \mathbb{E}_{(X, Y) \sim \mathcal{D}_d}[\ell(w \circ \Phi(X), Y)]$
+where we use $\ell$ to denote the cross entropy for a classification task, and $\mathcal{D}_d$ for distribution of domain $d$.
 
 The idea of IRM is to choose classifier $w$ to be in the intersection of optimal classifiers for each domain $$d$$.
 
-$$w \in \argmin_{\bar{w}} \ell^{(d)}(\bar{w} \circ \Phi) \quad \forall d$$
+$$w \in {\argmin}_{\bar{w}} \ell^{(d)}(\bar{w} \circ \Phi) \quad \forall d$$
 
 regardless of feature extractor $$\Phi(\cdot)$$, this serves as a constraint on the choice of classifiers $w$.
 
-The feature extractor $$\Phi(\cdot)$$ then get optimized under this constraint.
+The feature extractor $\Phi(\cdot)$ then get optimized under this constraint.
 
-Thus IRM forms a bi-level optimization by jointly optimize $$\Phi$$ and $$w$$ which is hard to solve, so in practice IRMv1 is used. 
+Thus IRM forms a bi-level optimization by jointly optimize $\Phi$ and $w$ which is hard to solve, so in practice IRMv1 is used. 
 
 ## IRMv1
 
@@ -24,6 +24,6 @@ $$\min_{\Phi, w} \sum_{d} \ell^{(d)}(w \circ \Phi) + \lambda \sum_{d} \|\nabla_{
 where $\lambda$ is a hyperparameter that controls the trade-off between the empirical risk and the penalty. One interpretation can be the penalty encourages the representation $\Phi$ to be small evaluated at $w = 1.0$ across all domains.
 
 In practice, one could simply divide one mini-batch into two subsets, let $i$ and $j$ to index these two subsets, multiply  subset $i$ and subset $j$ forms an unbiased estimation of the L2 norm of gradient.
-In detail: the squared gradient norm via inner product between $$\\nabla_{w|w=1} \\ell(w\\dot \\Phi(X^{(d, i)}), Y^{(d, i)})$$ of dimension dim(Grad) with $$\\nabla_{w|w=1} \\ell(w\\dot \\Phi(X^{(d, j)}), Y^{(d, j)})$$ of dimension dim(Grad) For more details, see section 3.2 and Appendix D of : Arjovsky et al., “Invariant Risk Minimization.”
+In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \\ell(w\\dot \\Phi(X^{(d, i)}), Y^{(d, i)})$ of dimension dim(Grad) with $\nabla_{w|w=1} \\ell(w\\dot \\Phi(X^{(d, j)}), Y^{(d, j)})$ of dimension dim(Grad) For more details, see section 3.2 and Appendix D of : Arjovsky et al., “Invariant Risk Minimization.”
 
 

From 8737551afa5a6a4eac49a4634cf7380e030d36d1 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 17:27:16 +0200
Subject: [PATCH 162/273] .

---
 docs/docIRM.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/docIRM.md b/docs/docIRM.md
index 6be3a3ca0..f71a2f368 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -24,6 +24,6 @@ $$\min_{\Phi, w} \sum_{d} \ell^{(d)}(w \circ \Phi) + \lambda \sum_{d} \|\nabla_{
 where $\lambda$ is a hyperparameter that controls the trade-off between the empirical risk and the penalty. One interpretation can be the penalty encourages the representation $\Phi$ to be small evaluated at $w = 1.0$ across all domains.
 
 In practice, one could simply divide one mini-batch into two subsets, let $i$ and $j$ to index these two subsets, multiply  subset $i$ and subset $j$ forms an unbiased estimation of the L2 norm of gradient.
-In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \\ell(w\\dot \\Phi(X^{(d, i)}), Y^{(d, i)})$ of dimension dim(Grad) with $\nabla_{w|w=1} \\ell(w\\dot \\Phi(X^{(d, j)}), Y^{(d, j)})$ of dimension dim(Grad) For more details, see section 3.2 and Appendix D of : Arjovsky et al., “Invariant Risk Minimization.”
+In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \ell(w \circ \Phi(X^{(d, i)}), Y^{(d, i)})$ of dimension dim(Grad) with $\nabla_{w|w=1} \ell(w \circ \Phi(X^{(d, j)}), Y^{(d, j)})$ of dimension dim(Grad) For more details, see section 3.2 and Appendix D of : Arjovsky et al., “Invariant Risk Minimization.”
 
 

From fd118a6952c7f7f36fcc8945af5925f223bd945b Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 17:29:26 +0200
Subject: [PATCH 163/273] .

---
 docs/docIRM.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/docIRM.md b/docs/docIRM.md
index f71a2f368..955ff14a3 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -1,4 +1,4 @@
-# Invariant Risk Minimization (IRM)
+# Trainer IRM (Invariant Risk Minimization)
 
 Decompose a classification task into feature extraction $\Phi(\cdot)$ and classificaiton layer $w(\cdot)$, then the task loss is
 

From 10442ba8c3158aa9a8a66a94f7f2db59c02e38f6 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 18 Jul 2024 21:40:33 +0200
Subject: [PATCH 164/273] better yaml for dial_diva

---
 examples/benchmark/pacs_fbopt_dial_diva.yaml | 19 ++++++++++---------
 1 file changed, 10 insertions(+), 9 deletions(-)

diff --git a/examples/benchmark/pacs_fbopt_dial_diva.yaml b/examples/benchmark/pacs_fbopt_dial_diva.yaml
index 02c664f71..ca2cf3921 100644
--- a/examples/benchmark/pacs_fbopt_dial_diva.yaml
+++ b/examples/benchmark/pacs_fbopt_dial_diva.yaml
@@ -29,7 +29,7 @@ domainlab_args:
 
 Shared params:
   ini_setpoint_ratio:
-    min: 0.5
+    min: 0.9
     max: 0.99
     num: 2
     step: 0.05
@@ -76,17 +76,18 @@ Shared params:
 dial_fbopt:
   model: diva
   trainer: fbopt_dial
+  gamma_y: 1.0
   shared:
     - ini_setpoint_ratio
     - k_i_gain_ratio
     - dial_lr 
     - dial_epsilon
 
-dial:
-  model: diva
-  trainer: dial
-  shared:
-    - dial_lr 
-    - dial_epsilon
-    - gamma_y
-    - gamma_d
+# dial:
+# model: diva
+# trainer: dial
+# shared:
+# - dial_lr 
+# - dial_epsilon
+# - gamma_y
+# - gamma_d

From 1df808a151b72a198344df8f0ffec7a4b2f71222 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sat, 20 Jul 2024 08:09:57 +0200
Subject: [PATCH 165/273] ma in index

---
 docs/index.rst | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/docs/index.rst b/docs/index.rst
index 332084d98..548cd5f84 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -1,3 +1,4 @@
+
 .. domainlab documentation master file, created by
    sphinx-quickstart on Tue Jul 26 16:30:46 2022.
    You can adapt this file completely to your liking, but it should at least
@@ -20,6 +21,7 @@ Welcome to domainlab's documentation!
    docFishr
    doc_mldg
    docIRM
+   docMA
 
 
 Indices and tables

From 1005760fabf46bbbfc16a9705e72605053a8d594 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 24 Jul 2024 16:32:12 +0200
Subject: [PATCH 166/273] estimate scale ratio at begin

---
 domainlab/algos/trainers/train_basic.py | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/domainlab/algos/trainers/train_basic.py b/domainlab/algos/trainers/train_basic.py
index 7e6d7cac7..c0a363ec9 100644
--- a/domainlab/algos/trainers/train_basic.py
+++ b/domainlab/algos/trainers/train_basic.py
@@ -24,6 +24,19 @@ def before_tr(self):
         check the performance of randomly initialized weight
         """
         self.model.evaluate(self.loader_te, self.device)
+        list_accum_reg_loss = []
+        loss_task_agg = 0
+        for ind_batch, (tensor_x, tensor_y, tensor_d, *others) in enumerate(
+            self.loader_tr
+        ):
+            list_reg_loss, _ = \
+                self.cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
+            if ind_batch == 0:
+                list_accum_reg_loss = list_reg_loss
+            list_accum_reg_loss = [reg_loss_accum + reg_loss \
+                                   for reg_loss_accum, reg_loss in
+                                   zip(list_accum_reg_loss, list_reg_loss)]
+            loss_task = self.model.cal_task_loss(tensor_x, tensor_y)
 
     def before_epoch(self):
         """

From 209a137186f46cb5e8e8294310ab2ea5f40d963d Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 25 Jul 2024 12:17:00 +0200
Subject: [PATCH 167/273] ratio estimation done

---
 domainlab/algos/trainers/a_trainer.py         | 50 +++++++++++++++----
 domainlab/algos/trainers/train_basic.py       | 18 +------
 .../algos/trainers/train_hyper_scheduler.py   |  1 +
 3 files changed, 43 insertions(+), 26 deletions(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 8af15bf25..cddfc24cf 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -3,6 +3,7 @@
 """
 import abc
 
+import torch
 from torch import optim
 
 from domainlab.compos.pcr.p_chain_handler import AbstractChainNodeHandler
@@ -88,6 +89,8 @@ def __init__(self, successor_node=None, extend=None):
         self.ma_weight_previous_model_params = None
         self._ma_dict_para_persist = {}
         self._ma_iter = 0
+        #
+        self.list_reg_over_task_ratio = None
 
     @property
     def model(self):
@@ -184,11 +187,37 @@ def after_batch(self, epoch, ind_batch):
         """
         return
 
-    @abc.abstractmethod
     def before_tr(self):
         """
         before training, probe model performance
         """
+        list_accum_reg_loss = []
+        loss_task_agg = 0
+        for ind_batch, (tensor_x, tensor_y, tensor_d, *others) in enumerate(
+            self.loader_tr
+        ):
+            tensor_x, tensor_y, tensor_d = (
+                tensor_x.to(self.device),
+                tensor_y.to(self.device),
+                tensor_d.to(self.device),
+            )
+            list_reg_loss_tensor, _ = \
+                self.cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
+            list_reg_loss_tensor = [torch.sum(tensor).detach().item()
+                                    for tensor in list_reg_loss_tensor]
+            if ind_batch == 0:
+                list_accum_reg_loss = list_reg_loss_tensor
+            else:
+                list_accum_reg_loss = [reg_loss_accum_tensor + reg_loss_tensor
+                                       for reg_loss_accum_tensor,
+                                       reg_loss_tensor in
+                                       zip(list_accum_reg_loss,
+                                           list_reg_loss_tensor)]
+            tensor_loss_task = self.model.cal_task_loss(tensor_x, tensor_y)
+            tensor_loss_task = torch.sum(tensor_loss_task).detach().item()
+            loss_task_agg += tensor_loss_task
+        self.list_reg_over_task_ratio = [reg_loss / loss_task_agg
+                                         for reg_loss in list_accum_reg_loss]
 
     def post_tr(self):
         """
@@ -233,19 +262,20 @@ def cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         combine losses of current trainer with self._model.cal_reg_loss, which
         can be either a trainer or a model
         """
-        list_reg_model, list_mu_model = self.decoratee.cal_reg_loss(
-            tensor_x, tensor_y, tensor_d, others
-        )
-        assert len(list_reg_model) == len(list_mu_model)
+        list_reg_loss_model_tensor, list_mu_model = \
+            self.decoratee.cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
+        assert len(list_reg_loss_model_tensor) == len(list_mu_model)
 
-        list_reg_trainer, list_mu_trainer = self._cal_reg_loss(
+        list_reg_loss_trainer_tensor, list_mu_trainer = self._cal_reg_loss(
             tensor_x, tensor_y, tensor_d, others
         )
-        assert len(list_reg_trainer) == len(list_mu_trainer)
-
-        list_loss = list_reg_model + list_reg_trainer
+        assert len(list_reg_loss_trainer_tensor) == len(list_mu_trainer)
+        # extend the length of list: extend number of regularization loss
+        # tensor: the element of list is tensor
+        list_loss_tensor = list_reg_loss_model_tensor + \
+            list_reg_loss_trainer_tensor
         list_mu = list_mu_model + list_mu_trainer
-        return list_loss, list_mu
+        return list_loss_tensor, list_mu
 
     def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         """
diff --git a/domainlab/algos/trainers/train_basic.py b/domainlab/algos/trainers/train_basic.py
index c0a363ec9..406879b07 100644
--- a/domainlab/algos/trainers/train_basic.py
+++ b/domainlab/algos/trainers/train_basic.py
@@ -4,10 +4,8 @@
 import math
 from operator import add
 
-import torch
-
 from domainlab import g_tensor_batch_agg
-from domainlab.algos.trainers.a_trainer import AbstractTrainer, mk_opt
+from domainlab.algos.trainers.a_trainer import AbstractTrainer
 
 
 def list_divide(list_val, scalar):
@@ -24,19 +22,7 @@ def before_tr(self):
         check the performance of randomly initialized weight
         """
         self.model.evaluate(self.loader_te, self.device)
-        list_accum_reg_loss = []
-        loss_task_agg = 0
-        for ind_batch, (tensor_x, tensor_y, tensor_d, *others) in enumerate(
-            self.loader_tr
-        ):
-            list_reg_loss, _ = \
-                self.cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
-            if ind_batch == 0:
-                list_accum_reg_loss = list_reg_loss
-            list_accum_reg_loss = [reg_loss_accum + reg_loss \
-                                   for reg_loss_accum, reg_loss in
-                                   zip(list_accum_reg_loss, list_reg_loss)]
-            loss_task = self.model.cal_task_loss(tensor_x, tensor_y)
+        super().before_tr()
 
     def before_epoch(self):
         """
diff --git a/domainlab/algos/trainers/train_hyper_scheduler.py b/domainlab/algos/trainers/train_hyper_scheduler.py
index 2e60bf5e8..0a89e7691 100644
--- a/domainlab/algos/trainers/train_hyper_scheduler.py
+++ b/domainlab/algos/trainers/train_hyper_scheduler.py
@@ -54,6 +54,7 @@ def before_tr(self):
                 total_steps=self.aconf.warmup,
                 flag_update_epoch=True,
             )
+        super().before_tr()
 
     def tr_epoch(self, epoch):
         """

From ad6e7f44738da99e1e3c0a2ab8daa760ee8ea39a Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 25 Jul 2024 12:29:34 +0200
Subject: [PATCH 168/273] reg over task ratio inserted

---
 domainlab/algos/trainers/train_basic.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/train_basic.py b/domainlab/algos/trainers/train_basic.py
index 406879b07..02d0c9f29 100644
--- a/domainlab/algos/trainers/train_basic.py
+++ b/domainlab/algos/trainers/train_basic.py
@@ -94,8 +94,11 @@ def cal_loss(self, tensor_x, tensor_y, tensor_d, others):
         list_reg_tr_batch, list_mu_tr = self.cal_reg_loss(
             tensor_x, tensor_y, tensor_d, others
         )
+        list_mu_tr_normalized = \
+            [mu / reg_over_task_ratio for (mu, reg_over_task_ratio)
+             in zip(list_mu_tr, self.list_reg_over_task_ratio)]
         tensor_batch_reg_loss_penalized = self.model.list_inner_product(
-            list_reg_tr_batch, list_mu_tr
+            list_reg_tr_batch, list_mu_tr_normalized
         )
         assert len(tensor_batch_reg_loss_penalized.shape) == 1
         loss_erm_agg = g_tensor_batch_agg(loss_task)

From 9cb3e093410b83809d18a38858858494a040b626 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 25 Jul 2024 13:28:02 +0200
Subject: [PATCH 169/273] .

---
 domainlab/algos/trainers/train_basic.py | 9 ++++++---
 domainlab/algos/trainers/train_mldg.py  | 1 +
 2 files changed, 7 insertions(+), 3 deletions(-)

diff --git a/domainlab/algos/trainers/train_basic.py b/domainlab/algos/trainers/train_basic.py
index 02d0c9f29..363157d86 100644
--- a/domainlab/algos/trainers/train_basic.py
+++ b/domainlab/algos/trainers/train_basic.py
@@ -94,9 +94,12 @@ def cal_loss(self, tensor_x, tensor_y, tensor_d, others):
         list_reg_tr_batch, list_mu_tr = self.cal_reg_loss(
             tensor_x, tensor_y, tensor_d, others
         )
-        list_mu_tr_normalized = \
-            [mu / reg_over_task_ratio for (mu, reg_over_task_ratio)
-             in zip(list_mu_tr, self.list_reg_over_task_ratio)]
+
+        list_mu_tr_normalized = list_mu_tr
+        if self.list_reg_over_task_ratio:
+            list_mu_tr_normalized = \
+                [mu / reg_over_task_ratio for (mu, reg_over_task_ratio)
+                 in zip(list_mu_tr, self.list_reg_over_task_ratio)]
         tensor_batch_reg_loss_penalized = self.model.list_inner_product(
             list_reg_tr_batch, list_mu_tr_normalized
         )
diff --git a/domainlab/algos/trainers/train_mldg.py b/domainlab/algos/trainers/train_mldg.py
index e91310adf..2c7376636 100644
--- a/domainlab/algos/trainers/train_mldg.py
+++ b/domainlab/algos/trainers/train_mldg.py
@@ -35,6 +35,7 @@ def before_tr(self):
             flag_accept=False,
         )
         self.prepare_ziped_loader()
+        super().before_tr()
 
     def prepare_ziped_loader(self):
         """

From b90c79af8755b12e2f78ee4627dd26702d4bb805 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 25 Jul 2024 15:19:18 +0200
Subject: [PATCH 170/273] fix divide by zero

---
 domainlab/algos/trainers/train_basic.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/train_basic.py b/domainlab/algos/trainers/train_basic.py
index 363157d86..55c3802c9 100644
--- a/domainlab/algos/trainers/train_basic.py
+++ b/domainlab/algos/trainers/train_basic.py
@@ -98,7 +98,8 @@ def cal_loss(self, tensor_x, tensor_y, tensor_d, others):
         list_mu_tr_normalized = list_mu_tr
         if self.list_reg_over_task_ratio:
             list_mu_tr_normalized = \
-                [mu / reg_over_task_ratio for (mu, reg_over_task_ratio)
+                [mu / reg_over_task_ratio if reg_over_task_ratio != 0
+                 else mu for (mu, reg_over_task_ratio)
                  in zip(list_mu_tr, self.list_reg_over_task_ratio)]
         tensor_batch_reg_loss_penalized = self.model.list_inner_product(
             list_reg_tr_batch, list_mu_tr_normalized

From a78d84e68da3fb94f22252e4639d1fe2f802d1d2 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 25 Jul 2024 15:37:14 +0200
Subject: [PATCH 171/273] Update train_ema.py

---
 domainlab/algos/trainers/train_ema.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/train_ema.py b/domainlab/algos/trainers/train_ema.py
index 10bb7e786..90f5a1a75 100644
--- a/domainlab/algos/trainers/train_ema.py
+++ b/domainlab/algos/trainers/train_ema.py
@@ -29,7 +29,8 @@ def move_average(self, dict_data, epoch):
         Salesforce Research, USA
         """
         self.ma_weight_previous_model_params = epoch / (epoch + 1)
-        # weight on previous model decrease as training goes on
+        # 1/2, 2/3, 3/4, 4/5, 
+        # weight on previous model converges to 1 as training goes on
         dict_ema_para_curr_iter = {}
         for key, data in dict_data.items():
             # data = data.view(1, -1)  # make it rank 1 tensor (a.k.a. vector)

From a5f0f0774e14541faa7bc10a3d9e04666cb93069 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 25 Jul 2024 15:53:35 +0200
Subject: [PATCH 172/273] fix bug in ema

---
 domainlab/algos/trainers/a_trainer.py |  2 +-
 domainlab/algos/trainers/train_ema.py | 30 +++++++++++++++------------
 2 files changed, 18 insertions(+), 14 deletions(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 8af15bf25..177a2b28e 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -86,7 +86,7 @@ def __init__(self, successor_node=None, extend=None):
         self.flag_initialized = False
         # moving average
         self.ma_weight_previous_model_params = None
-        self._ma_dict_para_persist = {}
+        self._dict_previous_para_persist = {}
         self._ma_iter = 0
 
     @property
diff --git a/domainlab/algos/trainers/train_ema.py b/domainlab/algos/trainers/train_ema.py
index 90f5a1a75..8b57368b0 100644
--- a/domainlab/algos/trainers/train_ema.py
+++ b/domainlab/algos/trainers/train_ema.py
@@ -29,29 +29,33 @@ def move_average(self, dict_data, epoch):
         Salesforce Research, USA
         """
         self.ma_weight_previous_model_params = epoch / (epoch + 1)
-        # 1/2, 2/3, 3/4, 4/5, 
+        # 1/2, 2/3, 3/4, 4/5,
         # weight on previous model converges to 1 as training goes on
-        dict_ema_para_curr_iter = {}
+        dict_return_ema_para_curr_iter = {}
         for key, data in dict_data.items():
             # data = data.view(1, -1)  # make it rank 1 tensor (a.k.a. vector)
             if self._ma_iter == 0:
                 previous_data = torch.zeros_like(data)
+                local_data_convex = data
             else:
-                previous_data = self._ma_dict_para_persist[key]
-
-            local_data_convex = \
-                self.ma_weight_previous_model_params * previous_data + \
-                (1 - self.ma_weight_previous_model_params) * data
-            # correction by 1/(1 - self.rho)
+                previous_data = self._dict_previous_para_persist[key]
+                local_data_convex = \
+                    self.ma_weight_previous_model_params * previous_data + \
+                    (1 - self.ma_weight_previous_model_params) * data
+            # correction by 1/(1 - self.ma_weight_previous_model_params)
             # so that the gradients amplitude backpropagated in data is
-            # independent of self.rho
-            dict_ema_para_curr_iter[key] = \
-                local_data_convex / (1 - self.ma_weight_previous_model_params)
-            self._ma_dict_para_persist[key] = \
+            # independent of self.ma_weight_previous_model_params
+            # We did not do this because 1-rho will be almost zero as
+            # epochs goes on, which will expand the neural network weights
+            # to overflow
+            # dict_return_ema_para_curr_iter[key] = \
+            #    local_data_convex / (1 - self.ma_weight_previous_model_params)
+            dict_return_ema_para_curr_iter[key] = local_data_convex
+            self._dict_previous_para_persist[key] = \
                 local_data_convex.clone().detach()  # used as previous data
 
         self._ma_iter += 1
-        return dict_ema_para_curr_iter
+        return dict_return_ema_para_curr_iter
 
     def after_epoch(self, epoch):
         torch_model = self.get_model()

From d7a4ed39d3ad94cba5304d53b1a8a8a0afb14080 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 25 Jul 2024 16:37:45 +0200
Subject: [PATCH 173/273] first version causal irl

---
 domainlab/algos/trainers/train_causIRL.py | 75 +++++++++++++++++++++++
 domainlab/algos/trainers/zoo_trainer.py   |  2 +
 tests/test_causal_irl.py                  | 13 ++++
 3 files changed, 90 insertions(+)
 create mode 100644 domainlab/algos/trainers/train_causIRL.py
 create mode 100644 tests/test_causal_irl.py

diff --git a/domainlab/algos/trainers/train_causIRL.py b/domainlab/algos/trainers/train_causIRL.py
new file mode 100644
index 000000000..139223c58
--- /dev/null
+++ b/domainlab/algos/trainers/train_causIRL.py
@@ -0,0 +1,75 @@
+"""
+Alex, Xudong
+"""
+import numpy as np
+import torch
+from domainlab.algos.trainers.train_basic import TrainerBasic
+
+
+class TrainerCausIRL(TrainerBasic):
+    def my_cdist(self, x1, x2):
+        x1_norm = x1.pow(2).sum(dim=-1, keepdim=True)
+        x2_norm = x2.pow(2).sum(dim=-1, keepdim=True)
+        res = torch.addmm(x2_norm.transpose(-2, -1),
+                          x1,
+                          x2.transpose(-2, -1), alpha=-2).add_(x1_norm)
+        return res.clamp_min_(1e-30)
+
+    def gaussian_kernel(self, x, y, gamma=[0.001, 0.01, 0.1, 1, 10, 100,
+                                           1000]):
+        D = self.my_cdist(x, y)
+        K = torch.zeros_like(D)
+
+        for g in gamma:
+            K.add_(torch.exp(D.mul(-g)))
+
+        return K
+
+    def mmd(self, x, y):
+        if self.kernel_type == "gaussian":
+            Kxx = self.gaussian_kernel(x, x).mean()
+            Kyy = self.gaussian_kernel(y, y).mean()
+            Kxy = self.gaussian_kernel(x, y).mean()
+            return Kxx + Kyy - 2 * Kxy
+        else:
+            mean_x = x.mean(0, keepdim=True)
+            mean_y = y.mean(0, keepdim=True)
+            cent_x = x - mean_x
+            cent_y = y - mean_y
+            cova_x = (cent_x.t() @ cent_x) / (len(x) - 1)
+            cova_y = (cent_y.t() @ cent_y) / (len(y) - 1)
+
+            mean_diff = (mean_x - mean_y).pow(2).mean()
+            cova_diff = (cova_x - cova_y).pow(2).mean()
+
+            return mean_diff + cova_diff
+
+
+    def tr_batch(self, tensor_x, tensor_y, tensor_d, others, ind_batch, epoch):
+        """
+        optimize neural network one step upon a mini-batch of data
+        """
+        self.kernel_type = "gaussian"
+        self.before_batch(epoch, ind_batch)
+        tensor_x, tensor_y, tensor_d = (
+            tensor_x.to(self.device),
+            tensor_y.to(self.device),
+            tensor_d.to(self.device),
+        )
+        self.optimizer.zero_grad()
+
+        features = self.get_model().extract_semantic_feat(tensor_x)
+
+        pos_batch_break = np.random.randint(0, tensor_x.shape[0])
+        first = features[:pos_batch_break]
+        second = features[pos_batch_break:]
+        if len(first) > 1 and len(second) > 1:
+            penalty = torch.nan_to_num(self.mmd(first, second))
+        else:
+            penalty = torch.tensor(0)
+        loss = self.cal_loss(tensor_x, tensor_y, tensor_d, others)
+        loss = loss + penalty
+        loss.backward()
+        self.optimizer.step()
+        self.after_batch(epoch, ind_batch)
+        self.counter_batch += 1
diff --git a/domainlab/algos/trainers/zoo_trainer.py b/domainlab/algos/trainers/zoo_trainer.py
index e4a8c7bd5..22445c76d 100644
--- a/domainlab/algos/trainers/zoo_trainer.py
+++ b/domainlab/algos/trainers/zoo_trainer.py
@@ -9,6 +9,7 @@
 from domainlab.algos.trainers.train_mldg import TrainerMLDG
 from domainlab.algos.trainers.train_fishr import TrainerFishr
 from domainlab.algos.trainers.train_irm import TrainerIRM
+from domainlab.algos.trainers.train_causIRL import TrainerCausIRL
 
 
 class TrainerChainNodeGetter(object):
@@ -54,6 +55,7 @@ def __call__(self, lst_candidates=None, default=None, lst_excludes=None):
         chain = TrainerFishr(chain)
         chain = TrainerIRM(chain)
         chain = TrainerHyperScheduler(chain)
+        chain = TrainerCausIRL(chain)
         node = chain.handle(self.request)
         head = node
         while self._list_str_trainer:
diff --git a/tests/test_causal_irl.py b/tests/test_causal_irl.py
new file mode 100644
index 000000000..0c1ea513d
--- /dev/null
+++ b/tests/test_causal_irl.py
@@ -0,0 +1,13 @@
+"""
+ end-end test
+"""
+from tests.utils_test import utils_test_algo
+
+
+def test_causal_irl():
+    """
+    causal irl
+    """
+    args = "--te_d 0 --tr_d 3 7 --bs=32 --debug --task=mnistcolor10 \
+        --model=erm --nname=conv_bn_pool_2 --trainer=causirl"
+    utils_test_algo(args)

From c2ad38a0c36e69596d41eed9c04966eb35660b37 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 25 Jul 2024 18:00:22 +0200
Subject: [PATCH 174/273] Update exp_main.py

---
 domainlab/exp/exp_main.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/domainlab/exp/exp_main.py b/domainlab/exp/exp_main.py
index 3d60ac520..ca2b6a535 100755
--- a/domainlab/exp/exp_main.py
+++ b/domainlab/exp/exp_main.py
@@ -59,7 +59,7 @@ def __init__(self, args, task=None, model=None, observer=None, visitor=AggWriter
         # visitor must be initialized last after trainer is initialized
         self.experiment_duration = None
         self.model.set_saver(self.visitor)
-        self.model.save()
+        self.visitor.save()   # self.model.save() cause CI infinite loop? 
 
     def execute(self, num_epochs=None):
         """

From c9242cd265188305d50c46aaff9c0ec5be3eda08 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 25 Jul 2024 18:06:42 +0200
Subject: [PATCH 175/273] Update exp_main.py

---
 domainlab/exp/exp_main.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/domainlab/exp/exp_main.py b/domainlab/exp/exp_main.py
index ca2b6a535..a033bb734 100755
--- a/domainlab/exp/exp_main.py
+++ b/domainlab/exp/exp_main.py
@@ -59,13 +59,13 @@ def __init__(self, args, task=None, model=None, observer=None, visitor=AggWriter
         # visitor must be initialized last after trainer is initialized
         self.experiment_duration = None
         self.model.set_saver(self.visitor)
-        self.visitor.save()   # self.model.save() cause CI infinite loop? 
-
+        
     def execute(self, num_epochs=None):
         """
         train model
         check performance by loading persisted model
         """
+        self.model.save()  # cause CI infinite loop when put in initializer? 
         if num_epochs is None:
             num_epochs = self.epochs + 1
         t_0 = datetime.datetime.now()

From f5efc7617b3452e122b570aab0b7552d85796a18 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 25 Jul 2024 18:10:24 +0200
Subject: [PATCH 176/273] Update train_basic.py

---
 domainlab/algos/trainers/train_basic.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/domainlab/algos/trainers/train_basic.py b/domainlab/algos/trainers/train_basic.py
index 55c3802c9..179848467 100644
--- a/domainlab/algos/trainers/train_basic.py
+++ b/domainlab/algos/trainers/train_basic.py
@@ -97,6 +97,7 @@ def cal_loss(self, tensor_x, tensor_y, tensor_d, others):
 
         list_mu_tr_normalized = list_mu_tr
         if self.list_reg_over_task_ratio:
+            assert len(list_mu_tr) == len(self.list_reg_over_task_ratio)
             list_mu_tr_normalized = \
                 [mu / reg_over_task_ratio if reg_over_task_ratio != 0
                  else mu for (mu, reg_over_task_ratio)

From 55bba059dbfde5ac6144a22829e1c90a17d22b38 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 25 Jul 2024 22:20:45 +0200
Subject: [PATCH 177/273] Update ci.yml, pytest config

---
 .github/workflows/ci.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 9d93b8530..86ca0b445 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -32,7 +32,7 @@ jobs:
     - name: test if api works
       run: poetry run python examples/api/jigen_dann_transformer.py
     - name: Generate coverage report
-      run: rm -rf zoutput && poetry run pytest --cov=domainlab tests/ --cov-report=xml
+      run: rm -rf zoutput && poetry run pytest --maxfail=1 -vvv --tb=short --cov=domainlab tests/ --cov-report=xml
     - name: Upload coverage to Codecov
       uses: codecov/codecov-action@v1
       with:

From aa53b31ffd419f6ea11a2f4a0ca054feb1a8a280 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 26 Jul 2024 00:20:19 +0200
Subject: [PATCH 178/273] torch no_grad for ratio calculation

---
 domainlab/algos/trainers/a_trainer.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index d02cf1729..24554fee2 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -191,6 +191,10 @@ def before_tr(self):
         """
         before training, probe model performance
         """
+        with torch.no_grad():
+            self.cal_reg_loss_over_task_loss_ratio()
+
+    def cal_reg_loss_over_task_loss_ratio(self):
         list_accum_reg_loss = []
         loss_task_agg = 0
         for ind_batch, (tensor_x, tensor_y, tensor_d, *others) in enumerate(

From bc4c4edccd97dad5069d52a82c44184bbc532d28 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Fri, 26 Jul 2024 00:27:22 +0200
Subject: [PATCH 179/273] remove torch_no_grad:  dial, dann need grad

---
 domainlab/algos/trainers/a_trainer.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 24554fee2..2d9673dba 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -191,8 +191,7 @@ def before_tr(self):
         """
         before training, probe model performance
         """
-        with torch.no_grad():
-            self.cal_reg_loss_over_task_loss_ratio()
+        self.cal_reg_loss_over_task_loss_ratio()
 
     def cal_reg_loss_over_task_loss_ratio(self):
         list_accum_reg_loss = []

From f5a2a5859cd23233722a0a07b3ac5847db93ac45 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 26 Jul 2024 00:56:05 +0200
Subject: [PATCH 180/273] matteo change

---
 domainlab/models/model_erm.py | 27 ++++++++++++++++++++++++++-
 1 file changed, 26 insertions(+), 1 deletion(-)

diff --git a/domainlab/models/model_erm.py b/domainlab/models/model_erm.py
index 6ee9c23f9..4ccec7a50 100644
--- a/domainlab/models/model_erm.py
+++ b/domainlab/models/model_erm.py
@@ -10,7 +10,6 @@
 except:
     backpack = None
 
-
 def mk_erm(parent_class=AModelClassif, **kwargs):
     """
     Instantiate a Deepall (ERM) model
@@ -53,4 +52,30 @@ def convert4backpack(self):
             """
             self._net_invar_feat = extend(self._net_invar_feat, use_converter=True)
             self.net_classifier = extend(self.net_classifier,  use_converter=True)
+
+        def hyper_update(self, epoch, fun_scheduler): # pylint: disable=unused-argument
+            """
+            Method necessary to combine with hyperparameter scheduler
+
+            :param epoch:
+            :param fun_scheduler:
+            """
+
+        def hyper_init(self, functor_scheduler, trainer=None):
+            """
+            initiate a scheduler object via class name and things inside this model
+
+            :param functor_scheduler: the class name of the scheduler
+            """
+            return functor_scheduler(
+                trainer=trainer
+            )
+
+        @property
+        def list_str_multiplier_na(self):
+            """
+            list of multipliers which match the order in cal_reg_loss
+            """
+            return []
+
     return ModelERM

From d7365f46dcaaf42b6e9c6b35dbfc837297ba6c9e Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 26 Jul 2024 01:01:39 +0200
Subject: [PATCH 181/273] codacy

---
 domainlab/algos/trainers/train_causIRL.py | 18 +++++++++++++++---
 1 file changed, 15 insertions(+), 3 deletions(-)

diff --git a/domainlab/algos/trainers/train_causIRL.py b/domainlab/algos/trainers/train_causIRL.py
index 139223c58..bb8fa8399 100644
--- a/domainlab/algos/trainers/train_causIRL.py
+++ b/domainlab/algos/trainers/train_causIRL.py
@@ -7,7 +7,13 @@
 
 
 class TrainerCausIRL(TrainerBasic):
+    """
+    causal matching
+    """
     def my_cdist(self, x1, x2):
+        """
+        distance for Gaussian
+        """
         x1_norm = x1.pow(2).sum(dim=-1, keepdim=True)
         x2_norm = x2.pow(2).sum(dim=-1, keepdim=True)
         res = torch.addmm(x2_norm.transpose(-2, -1),
@@ -17,15 +23,21 @@ def my_cdist(self, x1, x2):
 
     def gaussian_kernel(self, x, y, gamma=[0.001, 0.01, 0.1, 1, 10, 100,
                                            1000]):
-        D = self.my_cdist(x, y)
-        K = torch.zeros_like(D)
+        """
+        kernel for MMD
+        """
+        dist = self.my_cdist(x, y)
+        K = torch.zeros_like(dist)
 
         for g in gamma:
-            K.add_(torch.exp(D.mul(-g)))
+            K.add_(torch.exp(dist.mul(-g)))
 
         return K
 
     def mmd(self, x, y):
+        """
+        maximum mean discrepancy
+        """
         if self.kernel_type == "gaussian":
             Kxx = self.gaussian_kernel(x, x).mean()
             Kyy = self.gaussian_kernel(y, y).mean()

From 15d776d62acc1e0d1c0fc91bc47a030b6be1e63f Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 26 Jul 2024 08:48:44 +0200
Subject: [PATCH 182/273] by default no ratio estimation

---
 domainlab/algos/trainers/a_trainer.py | 2 ++
 domainlab/arg_parser.py               | 9 +++++++++
 2 files changed, 11 insertions(+)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 2d9673dba..e62fb1fdd 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -199,6 +199,8 @@ def cal_reg_loss_over_task_loss_ratio(self):
         for ind_batch, (tensor_x, tensor_y, tensor_d, *others) in enumerate(
             self.loader_tr
         ):
+            if ind_batch >= self.aconf.nb4ratio:
+                break
             tensor_x, tensor_y, tensor_d = (
                 tensor_x.to(self.device),
                 tensor_y.to(self.device),
diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index 1b8593e8f..ead22cd47 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -113,6 +113,15 @@ def mk_parser_main():
                         Set to 0 to turn warmup off.",
     )
 
+    parser.add_argument(
+        "-nb4ratio",
+        "--nb4reg_over_task_ratio",
+        type=int,
+        default=0,
+        help="number of batches for estimating reg loss over task loss ratio \
+        default 0",
+    )
+
     parser.add_argument("--debug", action="store_true", default=False)
     parser.add_argument("--dmem", action="store_true", default=False)
     parser.add_argument(

From 589c428671a3fe3d53d26651d669d053bd21049d Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 26 Jul 2024 08:53:52 +0200
Subject: [PATCH 183/273] .

---
 domainlab/algos/trainers/a_trainer.py | 2 +-
 domainlab/arg_parser.py               | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index e62fb1fdd..67120a1b6 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -199,7 +199,7 @@ def cal_reg_loss_over_task_loss_ratio(self):
         for ind_batch, (tensor_x, tensor_y, tensor_d, *others) in enumerate(
             self.loader_tr
         ):
-            if ind_batch >= self.aconf.nb4ratio:
+            if ind_batch >= self.aconf.nb4reg_over_task_ratio:
                 break
             tensor_x, tensor_y, tensor_d = (
                 tensor_x.to(self.device),
diff --git a/domainlab/arg_parser.py b/domainlab/arg_parser.py
index ead22cd47..cf9028cda 100644
--- a/domainlab/arg_parser.py
+++ b/domainlab/arg_parser.py
@@ -117,9 +117,9 @@ def mk_parser_main():
         "-nb4ratio",
         "--nb4reg_over_task_ratio",
         type=int,
-        default=0,
+        default=1,
         help="number of batches for estimating reg loss over task loss ratio \
-        default 0",
+        default 1",
     )
 
     parser.add_argument("--debug", action="store_true", default=False)

From 885fe0f23e7bec69084c29357a303e36946c8b33 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 26 Jul 2024 09:16:39 +0200
Subject: [PATCH 184/273] replicate irm loss to batch size

---
 domainlab/algos/trainers/train_irm.py |  5 +++--
 tests/test_irm.py                     | 11 +++++++++++
 2 files changed, 14 insertions(+), 2 deletions(-)

diff --git a/domainlab/algos/trainers/train_irm.py b/domainlab/algos/trainers/train_irm.py
index 0da2d0bde..90b16396e 100644
--- a/domainlab/algos/trainers/train_irm.py
+++ b/domainlab/algos/trainers/train_irm.py
@@ -66,5 +66,6 @@ def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         loss_2 = F.cross_entropy(phi[1::2] * dummy_w_scale, y[1::2])
         grad_1 = autograd.grad(loss_1, [dummy_w_scale], create_graph=True)[0]
         grad_2 = autograd.grad(loss_2, [dummy_w_scale], create_graph=True)[0]
-        loss_irm = torch.sum(grad_1 * grad_2)
-        return [loss_irm], [self.aconf.gamma_reg]
+        loss_irm_scalar = torch.sum(grad_1 * grad_2)  # scalar
+        loss_irm_tensor = loss_irm_scalar.expand(tensor_x.shape[0])
+        return [loss_irm_tensor], [self.aconf.gamma_reg]
diff --git a/tests/test_irm.py b/tests/test_irm.py
index 5ed8b4ceb..235b9e4ce 100644
--- a/tests/test_irm.py
+++ b/tests/test_irm.py
@@ -13,6 +13,17 @@ def test_irm():
     utils_test_algo(args)
 
 
+def test_irm_scheduler():
+    """
+    train with Invariant Risk Minimization
+    """
+    args = "--te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm \
+        --trainer=hyperscheduler_irm --nname=alexnet"
+    utils_test_algo(args)
+
+
+
+
 def test_irm_mnist():
     """
     train with Invariant Risk Minimization

From c5999461897b89b78511a7e3f07719e3b996407b Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 26 Jul 2024 12:05:52 +0200
Subject: [PATCH 185/273] clean test msel oracle

---
 tests/test_msel_oracle.py | 112 +++++++++-----------------------------
 1 file changed, 25 insertions(+), 87 deletions(-)

diff --git a/tests/test_msel_oracle.py b/tests/test_msel_oracle.py
index 8a28567b0..3eaef27d2 100644
--- a/tests/test_msel_oracle.py
+++ b/tests/test_msel_oracle.py
@@ -17,6 +17,15 @@
 from domainlab.utils.utils_cuda import get_device
 
 
+def mk_model(task):
+    backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
+    num_final_in = backbone.fc.in_features
+    backbone.fc = nn.Linear(num_final_in, task.dim_y)
+
+    # specify model to use
+    model = mk_erm(list_str_y=task.list_str_y)(backbone)
+    return model
+
 def mk_exp(
     task,
     model,
@@ -70,10 +79,7 @@ def mk_exp(
     return exp
 
 
-def test_msel_oracle():
-    """
-    return trainer, model, observer
-    """
+def mk_task():
     task = mk_task_dset(isize=ImSize(3, 28, 28), dim_y=10, taskna="custom_task")
     task.add_domain(
         name="domain1",
@@ -90,8 +96,15 @@ def test_msel_oracle():
         dset_tr=DsetMNISTColorSoloDefault(4),
         dset_val=DsetMNISTColorSoloDefault(5),
     )
+    return task
+
 
+def test_msel_oracle():
+    """
+    return trainer, model, observer
+    """
     # specify backbone to use
+    task = mk_task()
     backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
     num_final_in = backbone.fc.in_features
     backbone.fc = nn.Linear(num_final_in, task.dim_y)
@@ -110,24 +123,8 @@ def test_msel_oracle1():
     """
     return trainer, model, observer
     """
-    task = mk_task_dset(isize=ImSize(3, 28, 28), dim_y=10, taskna="custom_task")
-    task.add_domain(
-        name="domain1",
-        dset_tr=DsetMNISTColorSoloDefault(0),
-        dset_val=DsetMNISTColorSoloDefault(1),
-    )
-    task.add_domain(
-        name="domain2",
-        dset_tr=DsetMNISTColorSoloDefault(2),
-        dset_val=DsetMNISTColorSoloDefault(3),
-    )
-    task.add_domain(
-        name="domain3",
-        dset_tr=DsetMNISTColorSoloDefault(4),
-        dset_val=DsetMNISTColorSoloDefault(5),
-    )
-
-    # specify backbone to use
+    task = mk_task()
+   # specify backbone to use
     backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
     num_final_in = backbone.fc.in_features
     backbone.fc = nn.Linear(num_final_in, task.dim_y)
@@ -150,23 +147,7 @@ def test_msel_oracle2():
     """
     return trainer, model, observer
     """
-    task = mk_task_dset(isize=ImSize(3, 28, 28), dim_y=10, taskna="custom_task")
-    task.add_domain(
-        name="domain1",
-        dset_tr=DsetMNISTColorSoloDefault(0),
-        dset_val=DsetMNISTColorSoloDefault(1),
-    )
-    task.add_domain(
-        name="domain2",
-        dset_tr=DsetMNISTColorSoloDefault(2),
-        dset_val=DsetMNISTColorSoloDefault(3),
-    )
-    task.add_domain(
-        name="domain3",
-        dset_tr=DsetMNISTColorSoloDefault(4),
-        dset_val=DsetMNISTColorSoloDefault(5),
-    )
-
+    task = mk_task()
     # specify backbone to use
     backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
     num_final_in = backbone.fc.in_features
@@ -184,30 +165,8 @@ def test_msel_oracle3():
     """
     return trainer, model, observer
     """
-    task = mk_task_dset(isize=ImSize(3, 28, 28), dim_y=10, taskna="custom_task")
-    task.add_domain(
-        name="domain1",
-        dset_tr=DsetMNISTColorSoloDefault(0),
-        dset_val=DsetMNISTColorSoloDefault(1),
-    )
-    task.add_domain(
-        name="domain2",
-        dset_tr=DsetMNISTColorSoloDefault(2),
-        dset_val=DsetMNISTColorSoloDefault(3),
-    )
-    task.add_domain(
-        name="domain3",
-        dset_tr=DsetMNISTColorSoloDefault(4),
-        dset_val=DsetMNISTColorSoloDefault(5),
-    )
-
-    # specify backbone to use
-    backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
-    num_final_in = backbone.fc.in_features
-    backbone.fc = nn.Linear(num_final_in, task.dim_y)
-
-    # specify model to use
-    model = mk_erm(list_str_y=task.list_str_y)(backbone)
+    task = mk_task()
+    model = mk_model(task)
 
     exp = mk_exp(
         task,
@@ -226,30 +185,9 @@ def test_msel_oracle4():
     """
     return trainer, model, observer
     """
-    task = mk_task_dset(isize=ImSize(3, 28, 28), dim_y=10, taskna="custom_task")
-    task.add_domain(
-        name="domain1",
-        dset_tr=DsetMNISTColorSoloDefault(0),
-        dset_val=DsetMNISTColorSoloDefault(1),
-    )
-    task.add_domain(
-        name="domain2",
-        dset_tr=DsetMNISTColorSoloDefault(2),
-        dset_val=DsetMNISTColorSoloDefault(3),
-    )
-    task.add_domain(
-        name="domain3",
-        dset_tr=DsetMNISTColorSoloDefault(4),
-        dset_val=DsetMNISTColorSoloDefault(5),
-    )
-
+    task = mk_task()
+    model = mk_model(task)
     # specify backbone to use
-    backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
-    num_final_in = backbone.fc.in_features
-    backbone.fc = nn.Linear(num_final_in, task.dim_y)
-
-    # specify model to use
-    model = mk_erm(list_str_y=task.list_str_y)(backbone)
     exp = mk_exp(
         task,
         model,
@@ -261,5 +199,5 @@ def test_msel_oracle4():
     )
     exp.execute(num_epochs=2)
     exp.trainer.observer.model_sel.msel.best_loss = 0
-    exp.trainer.observer.model_sel.msel.update(epoch = 1, clear_counter=True)
+    exp.trainer.observer.model_sel.msel.update(epoch=1, clear_counter=True)
     del exp

From a5057072d494aedcea989684a09c47d7ff56c18a Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 26 Jul 2024 12:26:22 +0200
Subject: [PATCH 186/273] .

---
 tests/test_msel_oracle.py | 27 +++------------------------
 1 file changed, 3 insertions(+), 24 deletions(-)

diff --git a/tests/test_msel_oracle.py b/tests/test_msel_oracle.py
index 3eaef27d2..551860149 100644
--- a/tests/test_msel_oracle.py
+++ b/tests/test_msel_oracle.py
@@ -105,13 +105,7 @@ def test_msel_oracle():
     """
     # specify backbone to use
     task = mk_task()
-    backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
-    num_final_in = backbone.fc.in_features
-    backbone.fc = nn.Linear(num_final_in, task.dim_y)
-
-    # specify model to use
-    model = mk_erm(list_str_y=task.list_str_y)(backbone)
-
+    model = mk_model(task)
     # make trainer for model
     exp = mk_exp(task, model, trainer="mldg", test_domain="domain1", batchsize=32)
     exp.execute(num_epochs=2)
@@ -124,16 +118,7 @@ def test_msel_oracle1():
     return trainer, model, observer
     """
     task = mk_task()
-   # specify backbone to use
-    backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
-    num_final_in = backbone.fc.in_features
-    backbone.fc = nn.Linear(num_final_in, task.dim_y)
-
-    # specify model to use
-    model = mk_erm(list_str_y=task.list_str_y)(backbone)
-
-    # make trainer for model
-
+    model = mk_model(task)
     exp = mk_exp(
         task, model, trainer="mldg", test_domain="domain1", batchsize=32, alone=False
     )
@@ -148,13 +133,7 @@ def test_msel_oracle2():
     return trainer, model, observer
     """
     task = mk_task()
-    # specify backbone to use
-    backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
-    num_final_in = backbone.fc.in_features
-    backbone.fc = nn.Linear(num_final_in, task.dim_y)
-
-    # specify model to use
-    model = mk_erm(list_str_y=task.list_str_y)(backbone)
+    model = mk_model(task)
 
     # make trainer for model
     exp = mk_exp(task, model, trainer="mldg", test_domain="domain1", batchsize=32)

From 8efecac6af9df0da6877652d23cecd809a78da3d Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 26 Jul 2024 12:57:22 +0200
Subject: [PATCH 187/273] decrease batch size for msel_orcale test

---
 tests/test_msel_oracle.py | 11 +++++------
 1 file changed, 5 insertions(+), 6 deletions(-)

diff --git a/tests/test_msel_oracle.py b/tests/test_msel_oracle.py
index 551860149..8bcf37a92 100644
--- a/tests/test_msel_oracle.py
+++ b/tests/test_msel_oracle.py
@@ -66,7 +66,6 @@ def mk_exp(
 
     parser = mk_parser_main()
     conf = parser.parse_args(str_arg.split())
-    device = get_device(conf)
     if alone:
         model_sel = MSelOracleVisitor()
     else:
@@ -107,7 +106,7 @@ def test_msel_oracle():
     task = mk_task()
     model = mk_model(task)
     # make trainer for model
-    exp = mk_exp(task, model, trainer="mldg", test_domain="domain1", batchsize=32)
+    exp = mk_exp(task, model, trainer="mldg", test_domain="domain1", batchsize=2)
     exp.execute(num_epochs=2)
 
     del exp
@@ -120,7 +119,7 @@ def test_msel_oracle1():
     task = mk_task()
     model = mk_model(task)
     exp = mk_exp(
-        task, model, trainer="mldg", test_domain="domain1", batchsize=32, alone=False
+        task, model, trainer="mldg", test_domain="domain1", batchsize=2, alone=False
     )
 
     exp.execute(num_epochs=2)
@@ -136,7 +135,7 @@ def test_msel_oracle2():
     model = mk_model(task)
 
     # make trainer for model
-    exp = mk_exp(task, model, trainer="mldg", test_domain="domain1", batchsize=32)
+    exp = mk_exp(task, model, trainer="mldg", test_domain="domain1", batchsize=2)
     exp.execute(num_epochs=2)
 
 
@@ -152,7 +151,7 @@ def test_msel_oracle3():
         model,
         trainer="mldg",
         test_domain="domain1",
-        batchsize=32,
+        batchsize=2,
         alone=False,
         force_best_val=True,
     )
@@ -172,7 +171,7 @@ def test_msel_oracle4():
         model,
         trainer="mldg",
         test_domain="domain1",
-        batchsize=32,
+        batchsize=2,
         alone=False,
         msel_loss_tr=True,
     )

From 235832abf4e185d67f3779d36ad64818c7f8d8a8 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 26 Jul 2024 15:21:53 +0200
Subject: [PATCH 188/273] split msel_oracle test

---
 tests/test_msel_oracle.py  | 119 +------------------------------------
 tests/test_msel_oracle2.py |  26 ++++++++
 tests/utils_task_model.py  |  94 +++++++++++++++++++++++++++++
 3 files changed, 121 insertions(+), 118 deletions(-)
 create mode 100644 tests/test_msel_oracle2.py
 create mode 100644 tests/utils_task_model.py

diff --git a/tests/test_msel_oracle.py b/tests/test_msel_oracle.py
index 8bcf37a92..b8941f496 100644
--- a/tests/test_msel_oracle.py
+++ b/tests/test_msel_oracle.py
@@ -1,102 +1,7 @@
 """
 executing mk_exp multiple times will cause deep copy to be called multiple times, pytest will show process got killed.
 """
-from torch import nn
-from torchvision import models as torchvisionmodels
-from torchvision.models import ResNet50_Weights
-
-from domainlab.algos.msels.c_msel_oracle import MSelOracleVisitor
-from domainlab.algos.msels.c_msel_val import MSelValPerf
-from domainlab.algos.observers.b_obvisitor import ObVisitor
-from domainlab.arg_parser import mk_parser_main
-from domainlab.dsets.dset_mnist_color_solo_default import DsetMNISTColorSoloDefault
-from domainlab.exp.exp_main import Exp
-from domainlab.models.model_erm import mk_erm
-from domainlab.tasks.task_dset import mk_task_dset
-from domainlab.tasks.utils_task import ImSize
-from domainlab.utils.utils_cuda import get_device
-
-
-def mk_model(task):
-    backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
-    num_final_in = backbone.fc.in_features
-    backbone.fc = nn.Linear(num_final_in, task.dim_y)
-
-    # specify model to use
-    model = mk_erm(list_str_y=task.list_str_y)(backbone)
-    return model
-
-def mk_exp(
-    task,
-    model,
-    trainer: str,
-    test_domain: str,
-    batchsize: int,
-    alone=True,
-    force_best_val=False,
-    msel_loss_tr=False,
-):
-    """
-    Creates a custom experiment. The user can specify the input parameters.
-
-    Input Parameters:
-        - task: create a task to a custom dataset by importing "mk_task_dset"
-        function from
-        "domainlab.tasks.task_dset". For more explanation on the input params
-        refer to the
-        documentation found in "domainlab.tasks.task_dset.py".
-        - model: create a model [NameOfModel] by importing "mk_[NameOfModel]"
-        function from
-        "domainlab.models.model_[NameOfModel]". For a concrete example and
-        explanation of the input
-        params refer to the documentation found in
-        "domainlab.models.model_[NameOfModel].py"
-        - trainer: string,
-        - test_domain: string,
-        - batch size: int
-
-    Returns: experiment
-    """
-
-    str_arg = f"--model=apimodel --trainer={trainer} \
-        --te_d={test_domain} --bs={batchsize}"
-    if msel_loss_tr:
-        str_arg = f"--model=apimodel --trainer={trainer} \
-            --te_d={test_domain} --bs={batchsize} --msel=loss_tr"
-
-    parser = mk_parser_main()
-    conf = parser.parse_args(str_arg.split())
-    if alone:
-        model_sel = MSelOracleVisitor()
-    else:
-        model_sel = MSelOracleVisitor(MSelValPerf(max_es=0))
-        if force_best_val:
-            model_sel.msel._best_val_acc = 1.0
-    observer = ObVisitor(model_sel)
-    exp = Exp(conf, task, model=model, observer=observer)
-    model_sel.update(epoch=1, clear_counter=True)
-    return exp
-
-
-def mk_task():
-    task = mk_task_dset(isize=ImSize(3, 28, 28), dim_y=10, taskna="custom_task")
-    task.add_domain(
-        name="domain1",
-        dset_tr=DsetMNISTColorSoloDefault(0),
-        dset_val=DsetMNISTColorSoloDefault(1),
-    )
-    task.add_domain(
-        name="domain2",
-        dset_tr=DsetMNISTColorSoloDefault(2),
-        dset_val=DsetMNISTColorSoloDefault(3),
-    )
-    task.add_domain(
-        name="domain3",
-        dset_tr=DsetMNISTColorSoloDefault(4),
-        dset_val=DsetMNISTColorSoloDefault(5),
-    )
-    return task
-
+from tests.utils_task_model import mk_exp, mk_model, mk_task
 
 def test_msel_oracle():
     """
@@ -157,25 +62,3 @@ def test_msel_oracle3():
     )
     exp.execute(num_epochs=2)
     del exp
-
-
-def test_msel_oracle4():
-    """
-    return trainer, model, observer
-    """
-    task = mk_task()
-    model = mk_model(task)
-    # specify backbone to use
-    exp = mk_exp(
-        task,
-        model,
-        trainer="mldg",
-        test_domain="domain1",
-        batchsize=2,
-        alone=False,
-        msel_loss_tr=True,
-    )
-    exp.execute(num_epochs=2)
-    exp.trainer.observer.model_sel.msel.best_loss = 0
-    exp.trainer.observer.model_sel.msel.update(epoch=1, clear_counter=True)
-    del exp
diff --git a/tests/test_msel_oracle2.py b/tests/test_msel_oracle2.py
new file mode 100644
index 000000000..0f3245305
--- /dev/null
+++ b/tests/test_msel_oracle2.py
@@ -0,0 +1,26 @@
+"""
+executing mk_exp multiple times will cause deep copy to be called multiple times, pytest will show process got killed.
+"""
+from tests.utils_task_model import mk_exp, mk_model, mk_task
+
+
+def test_msel_oracle4():
+    """
+    return trainer, model, observer
+    """
+    task = mk_task()
+    model = mk_model(task)
+    # specify backbone to use
+    exp = mk_exp(
+        task,
+        model,
+        trainer="mldg",
+        test_domain="domain1",
+        batchsize=2,
+        alone=False,
+        msel_loss_tr=True,
+    )
+    exp.execute(num_epochs=2)
+    exp.trainer.observer.model_sel.msel.best_loss = 0
+    exp.trainer.observer.model_sel.msel.update(epoch=1, clear_counter=True)
+    del exp
diff --git a/tests/utils_task_model.py b/tests/utils_task_model.py
new file mode 100644
index 000000000..4fa70796a
--- /dev/null
+++ b/tests/utils_task_model.py
@@ -0,0 +1,94 @@
+from torch import nn
+from torchvision import models as torchvisionmodels
+from torchvision.models import ResNet50_Weights
+
+from domainlab.algos.msels.c_msel_oracle import MSelOracleVisitor
+from domainlab.algos.msels.c_msel_val import MSelValPerf
+from domainlab.algos.observers.b_obvisitor import ObVisitor
+from domainlab.arg_parser import mk_parser_main
+from domainlab.dsets.dset_mnist_color_solo_default import DsetMNISTColorSoloDefault
+from domainlab.exp.exp_main import Exp
+from domainlab.models.model_erm import mk_erm
+from domainlab.tasks.task_dset import mk_task_dset
+from domainlab.tasks.utils_task import ImSize
+
+
+def mk_model(task):
+    backbone = torchvisionmodels.resnet.resnet50(weights=ResNet50_Weights.IMAGENET1K_V2)
+    num_final_in = backbone.fc.in_features
+    backbone.fc = nn.Linear(num_final_in, task.dim_y)
+
+    # specify model to use
+    model = mk_erm(list_str_y=task.list_str_y)(backbone)
+    return model
+
+def mk_exp(
+    task,
+    model,
+    trainer: str,
+    test_domain: str,
+    batchsize: int,
+    alone=True,
+    force_best_val=False,
+    msel_loss_tr=False,
+):
+    """
+    Creates a custom experiment. The user can specify the input parameters.
+
+    Input Parameters:
+        - task: create a task to a custom dataset by importing "mk_task_dset"
+        function from
+        "domainlab.tasks.task_dset". For more explanation on the input params
+        refer to the
+        documentation found in "domainlab.tasks.task_dset.py".
+        - model: create a model [NameOfModel] by importing "mk_[NameOfModel]"
+        function from
+        "domainlab.models.model_[NameOfModel]". For a concrete example and
+        explanation of the input
+        params refer to the documentation found in
+        "domainlab.models.model_[NameOfModel].py"
+        - trainer: string,
+        - test_domain: string,
+        - batch size: int
+
+    Returns: experiment
+    """
+
+    str_arg = f"--model=apimodel --trainer={trainer} \
+        --te_d={test_domain} --bs={batchsize}"
+    if msel_loss_tr:
+        str_arg = f"--model=apimodel --trainer={trainer} \
+            --te_d={test_domain} --bs={batchsize} --msel=loss_tr"
+
+    parser = mk_parser_main()
+    conf = parser.parse_args(str_arg.split())
+    if alone:
+        model_sel = MSelOracleVisitor()
+    else:
+        model_sel = MSelOracleVisitor(MSelValPerf(max_es=0))
+        if force_best_val:
+            model_sel.msel._best_val_acc = 1.0
+    observer = ObVisitor(model_sel)
+    exp = Exp(conf, task, model=model, observer=observer)
+    model_sel.update(epoch=1, clear_counter=True)
+    return exp
+
+
+def mk_task():
+    task = mk_task_dset(isize=ImSize(3, 28, 28), dim_y=10, taskna="custom_task")
+    task.add_domain(
+        name="domain1",
+        dset_tr=DsetMNISTColorSoloDefault(0),
+        dset_val=DsetMNISTColorSoloDefault(1),
+    )
+    task.add_domain(
+        name="domain2",
+        dset_tr=DsetMNISTColorSoloDefault(2),
+        dset_val=DsetMNISTColorSoloDefault(3),
+    )
+    task.add_domain(
+        name="domain3",
+        dset_tr=DsetMNISTColorSoloDefault(4),
+        dset_val=DsetMNISTColorSoloDefault(5),
+    )
+    return task

From 1feff92f8bbc327314ce70d67f696402b2f3f716 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Fri, 26 Jul 2024 17:06:50 +0200
Subject: [PATCH 189/273] Update test_msel_oracle.py

---
 tests/test_msel_oracle.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/tests/test_msel_oracle.py b/tests/test_msel_oracle.py
index b8941f496..3f2143c70 100644
--- a/tests/test_msel_oracle.py
+++ b/tests/test_msel_oracle.py
@@ -42,6 +42,7 @@ def test_msel_oracle2():
     # make trainer for model
     exp = mk_exp(task, model, trainer="mldg", test_domain="domain1", batchsize=2)
     exp.execute(num_epochs=2)
+    del exp
 
 
 def test_msel_oracle3():

From d012b94fde3eb347c638e0af6055aca95e5c3413 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Fri, 26 Jul 2024 17:12:32 +0200
Subject: [PATCH 190/273] Update test_msel_oracle.py

---
 tests/test_msel_oracle.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/tests/test_msel_oracle.py b/tests/test_msel_oracle.py
index 3f2143c70..03012bb18 100644
--- a/tests/test_msel_oracle.py
+++ b/tests/test_msel_oracle.py
@@ -13,7 +13,7 @@ def test_msel_oracle():
     # make trainer for model
     exp = mk_exp(task, model, trainer="mldg", test_domain="domain1", batchsize=2)
     exp.execute(num_epochs=2)
-
+    exp.clean_up()
     del exp
 
 
@@ -29,6 +29,7 @@ def test_msel_oracle1():
 
     exp.execute(num_epochs=2)
     exp.trainer.observer.model_sel.msel.update(epoch=1, clear_counter=True)
+    exp.clean_up()
     del exp
 
 
@@ -42,6 +43,7 @@ def test_msel_oracle2():
     # make trainer for model
     exp = mk_exp(task, model, trainer="mldg", test_domain="domain1", batchsize=2)
     exp.execute(num_epochs=2)
+    exp.clean_up()
     del exp
 
 
@@ -62,4 +64,5 @@ def test_msel_oracle3():
         force_best_val=True,
     )
     exp.execute(num_epochs=2)
+    exp.clean_up()
     del exp

From 34975daeba869f9f88032fa99bfc1f250b48f51c Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Fri, 26 Jul 2024 17:12:56 +0200
Subject: [PATCH 191/273] Update test_msel_oracle2.py

---
 tests/test_msel_oracle2.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/tests/test_msel_oracle2.py b/tests/test_msel_oracle2.py
index 0f3245305..651a38f2b 100644
--- a/tests/test_msel_oracle2.py
+++ b/tests/test_msel_oracle2.py
@@ -23,4 +23,5 @@ def test_msel_oracle4():
     exp.execute(num_epochs=2)
     exp.trainer.observer.model_sel.msel.best_loss = 0
     exp.trainer.observer.model_sel.msel.update(epoch=1, clear_counter=True)
+    exp.clean_up()
     del exp

From 2c1cdc939c732a629dec601f1f7a233dbc6ed47e Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 1 Aug 2024 16:14:30 +0200
Subject: [PATCH 192/273] coverage

---
 domainlab/algos/trainers/train_causIRL.py | 44 +++++++++--------------
 domainlab/algos/trainers/zoo_trainer.py   |  7 ++--
 tests/test_causal_irl.py                  |  2 +-
 3 files changed, 22 insertions(+), 31 deletions(-)

diff --git a/domainlab/algos/trainers/train_causIRL.py b/domainlab/algos/trainers/train_causIRL.py
index bb8fa8399..085abcbfa 100644
--- a/domainlab/algos/trainers/train_causIRL.py
+++ b/domainlab/algos/trainers/train_causIRL.py
@@ -6,7 +6,7 @@
 from domainlab.algos.trainers.train_basic import TrainerBasic
 
 
-class TrainerCausIRL(TrainerBasic):
+class TrainerCausalIRL(TrainerBasic):
     """
     causal matching
     """
@@ -14,54 +14,44 @@ def my_cdist(self, x1, x2):
         """
         distance for Gaussian
         """
+        # along the last dimension
         x1_norm = x1.pow(2).sum(dim=-1, keepdim=True)
         x2_norm = x2.pow(2).sum(dim=-1, keepdim=True)
+        # x_2_norm is [batchsize, 1]
+        # matrix multiplication (2nd, 3rd) and addition to first argument
+        # X1[batchsize, dimfeat] * X2[dimfeat, batchsize)
+        # alpha: Scaling factor for the matrix product (default: 1)
+        # x2_norm.transpose(-2, -1) is row vector
+        # x_1_norm is column vector
         res = torch.addmm(x2_norm.transpose(-2, -1),
                           x1,
                           x2.transpose(-2, -1), alpha=-2).add_(x1_norm)
         return res.clamp_min_(1e-30)
 
-    def gaussian_kernel(self, x, y, gamma=[0.001, 0.01, 0.1, 1, 10, 100,
-                                           1000]):
+    def gaussian_kernel(self, x, y):
         """
         kernel for MMD
         """
+        gamma=[0.001, 0.01, 0.1, 1, 10, 100, 1000]
         dist = self.my_cdist(x, y)
-        K = torch.zeros_like(dist)
-
+        tensor = torch.zeros_like(dist)
         for g in gamma:
-            K.add_(torch.exp(dist.mul(-g)))
-
-        return K
+            tensor.add_(torch.exp(dist.mul(-g)))
+        return tensor
 
     def mmd(self, x, y):
         """
         maximum mean discrepancy
         """
-        if self.kernel_type == "gaussian":
-            Kxx = self.gaussian_kernel(x, x).mean()
-            Kyy = self.gaussian_kernel(y, y).mean()
-            Kxy = self.gaussian_kernel(x, y).mean()
-            return Kxx + Kyy - 2 * Kxy
-        else:
-            mean_x = x.mean(0, keepdim=True)
-            mean_y = y.mean(0, keepdim=True)
-            cent_x = x - mean_x
-            cent_y = y - mean_y
-            cova_x = (cent_x.t() @ cent_x) / (len(x) - 1)
-            cova_y = (cent_y.t() @ cent_y) / (len(y) - 1)
-
-            mean_diff = (mean_x - mean_y).pow(2).mean()
-            cova_diff = (cova_x - cova_y).pow(2).mean()
-
-            return mean_diff + cova_diff
-
+        kxx = self.gaussian_kernel(x, x).mean()
+        kyy = self.gaussian_kernel(y, y).mean()
+        kxy = self.gaussian_kernel(x, y).mean()
+        return kxx + kyy - 2 * kxy
 
     def tr_batch(self, tensor_x, tensor_y, tensor_d, others, ind_batch, epoch):
         """
         optimize neural network one step upon a mini-batch of data
         """
-        self.kernel_type = "gaussian"
         self.before_batch(epoch, ind_batch)
         tensor_x, tensor_y, tensor_d = (
             tensor_x.to(self.device),
diff --git a/domainlab/algos/trainers/zoo_trainer.py b/domainlab/algos/trainers/zoo_trainer.py
index 22445c76d..d1eccb59b 100644
--- a/domainlab/algos/trainers/zoo_trainer.py
+++ b/domainlab/algos/trainers/zoo_trainer.py
@@ -4,12 +4,13 @@
 from domainlab.algos.trainers.train_basic import TrainerBasic
 from domainlab.algos.trainers.train_ema import TrainerMA
 from domainlab.algos.trainers.train_dial import TrainerDIAL
-from domainlab.algos.trainers.train_hyper_scheduler import TrainerHyperScheduler
+from domainlab.algos.trainers.train_hyper_scheduler \
+    import TrainerHyperScheduler
 from domainlab.algos.trainers.train_matchdg import TrainerMatchDG
 from domainlab.algos.trainers.train_mldg import TrainerMLDG
 from domainlab.algos.trainers.train_fishr import TrainerFishr
 from domainlab.algos.trainers.train_irm import TrainerIRM
-from domainlab.algos.trainers.train_causIRL import TrainerCausIRL
+from domainlab.algos.trainers.train_causIRL import TrainerCausalIRL
 
 
 class TrainerChainNodeGetter(object):
@@ -55,7 +56,7 @@ def __call__(self, lst_candidates=None, default=None, lst_excludes=None):
         chain = TrainerFishr(chain)
         chain = TrainerIRM(chain)
         chain = TrainerHyperScheduler(chain)
-        chain = TrainerCausIRL(chain)
+        chain = TrainerCausalIRL(chain)
         node = chain.handle(self.request)
         head = node
         while self._list_str_trainer:
diff --git a/tests/test_causal_irl.py b/tests/test_causal_irl.py
index 0c1ea513d..5292ef18c 100644
--- a/tests/test_causal_irl.py
+++ b/tests/test_causal_irl.py
@@ -9,5 +9,5 @@ def test_causal_irl():
     causal irl
     """
     args = "--te_d 0 --tr_d 3 7 --bs=32 --debug --task=mnistcolor10 \
-        --model=erm --nname=conv_bn_pool_2 --trainer=causirl"
+        --model=erm --nname=conv_bn_pool_2 --trainer=causalirl"
     utils_test_algo(args)

From 6f6169ec9aa4be6fa680bcf8f4d383426bbad6c9 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 6 Aug 2024 14:30:16 +0200
Subject: [PATCH 193/273] split examples into algo doc

---
 scripts/ci_run_examples.sh | 14 ++++++++++++++
 1 file changed, 14 insertions(+)

diff --git a/scripts/ci_run_examples.sh b/scripts/ci_run_examples.sh
index 9f6b4e041..837d47433 100644
--- a/scripts/ci_run_examples.sh
+++ b/scripts/ci_run_examples.sh
@@ -3,6 +3,20 @@ set -e  # exit upon first error
 # >> append content
 # > erase original content
 
+
+files=("docs/docDIAL.md" "docs/docFishr.md")
+
+for file in "${files[@]}"
+do
+echo "Processing $file"
+echo "#!/bin/bash -x -v" > sh_temp_algo.sh  
+sed -n '/```shell/,/```/ p' $file | sed '/^```/ d' >> ./sh_temp_algo.sh
+bash -x -v -e sh_temp_also.sh
+# Add your commands to process each file here
+done
+
+
+
 # echo "#!/bin/bash -x -v" > sh_temp_example.sh
 sed -n '/```shell/,/```/ p' docs/doc_examples.md | sed '/^```/ d' >> ./sh_temp_example.sh
 split -l 5 sh_temp_example.sh sh_example_split

From 1e2ff25da0c87779719c7a04e5a5fb4d2608e00b Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 22 Aug 2024 15:58:55 +0200
Subject: [PATCH 194/273] .

---
 docs/docDIAL.md            |  6 ++++++
 docs/docFishr.md           |  5 +++++
 docs/docIRM.md             |  4 ++++
 scripts/ci_run_examples.sh | 17 ++++++-----------
 4 files changed, 21 insertions(+), 11 deletions(-)

diff --git a/docs/docDIAL.md b/docs/docDIAL.md
index 8b8111de8..600f8b2cb 100644
--- a/docs/docDIAL.md
+++ b/docs/docDIAL.md
@@ -72,3 +72,9 @@ This procedure yields to the following availability of hyperparameter:
 - `--dial_epsilon`: pixel wise threshold to perturb images
 - `--gamma_reg`: ? ($\epsilon$ in the paper)
 - `--lr`: learning rate ($\alpha$ in the paper)
+
+# Examples
+
+```
+python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=dial --nname=conv_bn_pool_2
+```
diff --git a/docs/docFishr.md b/docs/docFishr.md
index 08580d9fe..e2ba4c1b9 100644
--- a/docs/docFishr.md
+++ b/docs/docFishr.md
@@ -72,6 +72,10 @@ For more details, see the reference below or the domainlab code.
 
 
 
+# Examples
+```
+python main_out.py --te_d=0 --task=mini_vlcs --model=erm --trainer=fishr --nname=alexnet --bs=2 --nocu
+```
 
 
 
@@ -79,3 +83,4 @@ _Reference:_
 Rame, Alexandre, Corentin Dancette, and Matthieu Cord. "Fishr:
 Invariant gradient variances for out-of-distribution generalization."
 International Conference on Machine Learning. PMLR, 2022.
+
diff --git a/docs/docIRM.md b/docs/docIRM.md
index 955ff14a3..c8a78a346 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -26,4 +26,8 @@ where $\lambda$ is a hyperparameter that controls the trade-off between the empi
 In practice, one could simply divide one mini-batch into two subsets, let $i$ and $j$ to index these two subsets, multiply  subset $i$ and subset $j$ forms an unbiased estimation of the L2 norm of gradient.
 In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \ell(w \circ \Phi(X^{(d, i)}), Y^{(d, i)})$ of dimension dim(Grad) with $\nabla_{w|w=1} \ell(w \circ \Phi(X^{(d, j)}), Y^{(d, j)})$ of dimension dim(Grad) For more details, see section 3.2 and Appendix D of : Arjovsky et al., “Invariant Risk Minimization.”
 
+# Examples
+```
+python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2
 
+```
diff --git a/scripts/ci_run_examples.sh b/scripts/ci_run_examples.sh
index 837d47433..0433bd79c 100644
--- a/scripts/ci_run_examples.sh
+++ b/scripts/ci_run_examples.sh
@@ -4,28 +4,23 @@ set -e  # exit upon first error
 # > erase original content
 
 
-files=("docs/docDIAL.md" "docs/docFishr.md")
+files=("docs/docDIAL.md" "docs/docIRM.md")
 
 for file in "${files[@]}"
 do
 echo "Processing $file"
+# no need to remove sh_temp_algo.sh since the following line overwrite it each time
 echo "#!/bin/bash -x -v" > sh_temp_algo.sh  
+# remove code marker ```
+# we use >> here to append to keep the header #!/bin/bash -x -v
 sed -n '/```shell/,/```/ p' $file | sed '/^```/ d' >> ./sh_temp_algo.sh
-bash -x -v -e sh_temp_also.sh
+bash -x -v -e sh_temp_algo.sh
 # Add your commands to process each file here
+echo "finished with $file"
 done
 
 
 
-# echo "#!/bin/bash -x -v" > sh_temp_example.sh
-sed -n '/```shell/,/```/ p' docs/doc_examples.md | sed '/^```/ d' >> ./sh_temp_example.sh
-split -l 5 sh_temp_example.sh sh_example_split
-for file in sh_example_split*;
-do (echo "#!/bin/bash -x -v" > "$file"_exe && cat "$file" >> "$file"_exe && bash -x -v "$file"_exe && rm -r zoutput);
-done
-# bash -x -v -e sh_temp_example.sh
-echo "general examples done"
-
 echo "#!/bin/bash -x -v" > sh_temp_mnist.sh
 sed -n '/```shell/,/```/ p' docs/doc_MNIST_classification.md | sed '/^```/ d' >> ./sh_temp_mnist.sh
 bash -x -v -e sh_temp_mnist.sh

From ea97541633eafa032396d8afc3ec5ec95894895b Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Mon, 2 Sep 2024 16:56:44 +0200
Subject: [PATCH 195/273] Update ci_run_examples.sh

---
 scripts/ci_run_examples.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/scripts/ci_run_examples.sh b/scripts/ci_run_examples.sh
index 0433bd79c..850fad0f4 100644
--- a/scripts/ci_run_examples.sh
+++ b/scripts/ci_run_examples.sh
@@ -4,7 +4,7 @@ set -e  # exit upon first error
 # > erase original content
 
 
-files=("docs/docDIAL.md" "docs/docIRM.md")
+files=("docs/docDIAL.md" "docs/docIRM.md" "docs/doc_examples.md")
 
 for file in "${files[@]}"
 do

From 77330913ff70a5bdcbb3dd60844e4cdf6d853482 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 5 Sep 2024 15:23:44 +0200
Subject: [PATCH 196/273] Update docIRM.md to check if CI fails

---
 docs/docIRM.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/docIRM.md b/docs/docIRM.md
index c8a78a346..5dbab424a 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -28,6 +28,6 @@ In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \
 
 # Examples
 ```
-python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2
+python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2 --agas
 
 ```

From bb1500b68d3c6240b970a7fe12bc3a353e0e53ee Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 5 Sep 2024 15:42:00 +0200
Subject: [PATCH 197/273] split hduva

---
 docs/docHDUVA.md           | 12 ++++++++++++
 docs/docIRM.md             |  2 +-
 docs/doc_examples.md       | 10 ----------
 scripts/ci_run_examples.sh |  2 +-
 4 files changed, 14 insertions(+), 12 deletions(-)

diff --git a/docs/docHDUVA.md b/docs/docHDUVA.md
index 4abcb71e9..47af4d344 100644
--- a/docs/docHDUVA.md
+++ b/docs/docHDUVA.md
@@ -52,6 +52,18 @@ Alternatively, one could use an existing neural network in DomainLab using `nnam
 
 ## Hyperparameter for warmup
 Finally, the number of epochs for hyper-parameter warm-up can be specified via the argument `warmup`.
+## Examples
+### use hduva on color mnist, train on 2 domains
+```shell
+python main_out.py --tr_d 0 1 2 --te_d 3 --bs=2 --task=mnistcolor10 --model=hduva  --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
+```
+
+### hduva is domain-unsupervised, so it works also with a single domain
+```shell
+python main_out.py --tr_d 0  --te_d 3 4 --bs=2 --task=mnistcolor10 --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
+```
+
+
 
 Please cite our paper if you find it useful!
 ```text
diff --git a/docs/docIRM.md b/docs/docIRM.md
index 5dbab424a..c8a78a346 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -28,6 +28,6 @@ In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \
 
 # Examples
 ```
-python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2 --agas
+python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2
 
 ```
diff --git a/docs/doc_examples.md b/docs/doc_examples.md
index 21d0b2eb2..0dddc5f5b 100755
--- a/docs/doc_examples.md
+++ b/docs/doc_examples.md
@@ -26,16 +26,6 @@ python main_out.py --te_d 0 1 --tr_d 3 5 --task=mnistcolor10 --debug --bs=2 --mo
 python main_out.py --te_d=0 --task=mnistcolor10 --keep_model --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=10e5 --gamma_d=1e5 --gen
 ```
 
-### use hduva on color mnist, train on 2 domains
-```shell
-python main_out.py --tr_d 0 1 2 --te_d 3 --bs=2 --task=mnistcolor10 --model=hduva  --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
-```
-
-### hduva is domain-unsupervised, so it works also with a single domain
-```shell
-python main_out.py --tr_d 0  --te_d 3 4 --bs=2 --task=mnistcolor10 --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
-```
-
 
 ## Larger images:
 
diff --git a/scripts/ci_run_examples.sh b/scripts/ci_run_examples.sh
index 850fad0f4..6cf1db18f 100644
--- a/scripts/ci_run_examples.sh
+++ b/scripts/ci_run_examples.sh
@@ -4,7 +4,7 @@ set -e  # exit upon first error
 # > erase original content
 
 
-files=("docs/docDIAL.md" "docs/docIRM.md" "docs/doc_examples.md")
+files=("docs/docDIAL.md" "docs/docIRM.md" "docs/doc_examples.md" "docs/docHDUVA.md")
 
 for file in "${files[@]}"
 do

From f9bdbb11b0240550a4695b10351574c52d82af25 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 5 Sep 2024 15:57:50 +0200
Subject: [PATCH 198/273] coral is just cross domain MMD distance

---
 domainlab/algos/trainers/train_coral.py | 74 +++++++++++++++++++++++++
 1 file changed, 74 insertions(+)
 create mode 100644 domainlab/algos/trainers/train_coral.py

diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
new file mode 100644
index 000000000..c684b3092
--- /dev/null
+++ b/domainlab/algos/trainers/train_coral.py
@@ -0,0 +1,74 @@
+"""
+Alex, Xudong
+"""
+import numpy as np
+import torch
+from domainlab.algos.trainers.train_basic import TrainerBasic
+
+
+class TrainerCausalIRL(TrainerBasic):
+    """
+    causal matching
+    """
+    def my_cdist(self, x1, x2):
+        """
+        distance for Gaussian
+        """
+        # along the last dimension
+        x1_norm = x1.pow(2).sum(dim=-1, keepdim=True)
+        x2_norm = x2.pow(2).sum(dim=-1, keepdim=True)
+        # x_2_norm is [batchsize, 1]
+        # matrix multiplication (2nd, 3rd) and addition to first argument
+        # X1[batchsize, dimfeat] * X2[dimfeat, batchsize)
+        # alpha: Scaling factor for the matrix product (default: 1)
+        # x2_norm.transpose(-2, -1) is row vector
+        # x_1_norm is column vector
+        res = torch.addmm(x2_norm.transpose(-2, -1),
+                          x1,
+                          x2.transpose(-2, -1), alpha=-2).add_(x1_norm)
+        return res.clamp_min_(1e-30)
+
+    def gaussian_kernel(self, x, y):
+        """
+        kernel for MMD
+        """
+        gamma=[0.001, 0.01, 0.1, 1, 10, 100, 1000]
+        dist = self.my_cdist(x, y)
+        tensor = torch.zeros_like(dist)
+        for g in gamma:
+            tensor.add_(torch.exp(dist.mul(-g)))
+        return tensor
+
+    def mmd(self, x, y):
+        """
+        maximum mean discrepancy
+        """
+        kxx = self.gaussian_kernel(x, x).mean()
+        kyy = self.gaussian_kernel(y, y).mean()
+        kxy = self.gaussian_kernel(x, y).mean()
+        return kxx + kyy - 2 * kxy
+
+    def tr_epoch(self, epoch):
+        list_loaders = list(self.dict_loader_tr.values())
+        loaders_zip = zip(*list_loaders)
+        self.model.train()
+        self.model.convert4backpack()
+        self.epo_loss_tr = 0
+
+        for ind_batch, tuple_data_domains_batch in enumerate(loaders_zip):
+            self.optimizer.zero_grad()
+            list_dict_var_grads, list_loss_erm = self.var_grads_and_loss(tuple_data_domains_batch)
+            dict_layerwise_var_var_grads = self.variance_between_dict(list_dict_var_grads)
+            dict_layerwise_var_var_grads_sum = \
+                {key: val.sum() for key, val in dict_layerwise_var_var_grads.items()}
+            loss_fishr = sum(dict_layerwise_var_var_grads_sum.values())
+            loss = sum(list_loss_erm) + get_gamma_reg(self.aconf, self.name) * loss_fishr
+            loss.backward()
+            self.optimizer.step()
+            self.epo_loss_tr += loss.detach().item()
+            self.after_batch(epoch, ind_batch)
+
+        flag_stop = self.observer.update(epoch)  # notify observer
+        return flag_stop
+
+

From b0983bf7ce480a2edce7f4887c46cce931a9d208 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 10 Sep 2024 17:49:02 +0200
Subject: [PATCH 199/273] Update ci_run_examples.sh, cat command from each
 markdown file

---
 scripts/ci_run_examples.sh | 1 +
 1 file changed, 1 insertion(+)

diff --git a/scripts/ci_run_examples.sh b/scripts/ci_run_examples.sh
index 6cf1db18f..98e0046a6 100644
--- a/scripts/ci_run_examples.sh
+++ b/scripts/ci_run_examples.sh
@@ -14,6 +14,7 @@ echo "#!/bin/bash -x -v" > sh_temp_algo.sh
 # remove code marker ```
 # we use >> here to append to keep the header #!/bin/bash -x -v
 sed -n '/```shell/,/```/ p' $file | sed '/^```/ d' >> ./sh_temp_algo.sh
+cat sh_temp_algo.sh
 bash -x -v -e sh_temp_algo.sh
 # Add your commands to process each file here
 echo "finished with $file"

From 05e41fb91876e87045ba7a0917dc37dc6777c821 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 10 Sep 2024 17:50:48 +0200
Subject: [PATCH 200/273] Update docIRM.md

---
 docs/docIRM.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/docIRM.md b/docs/docIRM.md
index c8a78a346..5dbab424a 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -28,6 +28,6 @@ In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \
 
 # Examples
 ```
-python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2
+python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2 --agas
 
 ```

From 0ff6ae7d90254856fd18b2ba13b6b67e14618732 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Wed, 11 Sep 2024 16:26:11 +0200
Subject: [PATCH 201/273] Update docIRM.md

---
 docs/docIRM.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/docIRM.md b/docs/docIRM.md
index 5dbab424a..621ef6ab8 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -27,7 +27,7 @@ In practice, one could simply divide one mini-batch into two subsets, let $i$ an
 In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \ell(w \circ \Phi(X^{(d, i)}), Y^{(d, i)})$ of dimension dim(Grad) with $\nabla_{w|w=1} \ell(w \circ \Phi(X^{(d, j)}), Y^{(d, j)})$ of dimension dim(Grad) For more details, see section 3.2 and Appendix D of : Arjovsky et al., “Invariant Risk Minimization.”
 
 # Examples
-```
+```shell
 python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2 --agas
 
 ```

From 6b01a3aadb0a2d6b69852911366ebbdbdc30461a Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Wed, 11 Sep 2024 16:39:19 +0200
Subject: [PATCH 202/273] Update docIRM.md, remove agas to see if it works

---
 docs/docIRM.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/docIRM.md b/docs/docIRM.md
index 621ef6ab8..0b8114de8 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -28,6 +28,6 @@ In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \
 
 # Examples
 ```shell
-python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2 --agas
+python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2
 
 ```

From 3ede5843043028cfce18d06aa0223f0c94344391 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Mon, 16 Sep 2024 14:54:15 +0200
Subject: [PATCH 203/273] add test

---
 domainlab/algos/trainers/mmd_base.py    | 48 +++++++++++++++++++++++++
 domainlab/algos/trainers/train_coral.py |  7 ++--
 domainlab/algos/trainers/zoo_trainer.py |  2 ++
 tests/test_coral.py                     | 13 +++++++
 4 files changed, 66 insertions(+), 4 deletions(-)
 create mode 100644 domainlab/algos/trainers/mmd_base.py
 create mode 100644 tests/test_coral.py

diff --git a/domainlab/algos/trainers/mmd_base.py b/domainlab/algos/trainers/mmd_base.py
new file mode 100644
index 000000000..6931a3048
--- /dev/null
+++ b/domainlab/algos/trainers/mmd_base.py
@@ -0,0 +1,48 @@
+"""
+Alexej, Xudong
+"""
+import torch
+from domainlab.algos.trainers.train_basic import TrainerBasic
+
+
+class TrainerMMDBase(TrainerBasic):
+    """
+    causal matching
+    """
+    def my_cdist(self, x1, x2):
+        """
+        distance for Gaussian
+        """
+        # along the last dimension
+        x1_norm = x1.pow(2).sum(dim=-1, keepdim=True)
+        x2_norm = x2.pow(2).sum(dim=-1, keepdim=True)
+        # x_2_norm is [batchsize, 1]
+        # matrix multiplication (2nd, 3rd) and addition to first argument
+        # X1[batchsize, dimfeat] * X2[dimfeat, batchsize)
+        # alpha: Scaling factor for the matrix product (default: 1)
+        # x2_norm.transpose(-2, -1) is row vector
+        # x_1_norm is column vector
+        res = torch.addmm(x2_norm.transpose(-2, -1),
+                          x1,
+                          x2.transpose(-2, -1), alpha=-2).add_(x1_norm)
+        return res.clamp_min_(1e-30)
+
+    def gaussian_kernel(self, x, y):
+        """
+        kernel for MMD
+        """
+        gamma = [0.001, 0.01, 0.1, 1, 10, 100, 1000]
+        dist = self.my_cdist(x, y)
+        tensor = torch.zeros_like(dist)
+        for g in gamma:
+            tensor.add_(torch.exp(dist.mul(-g)))
+        return tensor
+
+    def mmd(self, x, y):
+        """
+        maximum mean discrepancy
+        """
+        kxx = self.gaussian_kernel(x, x).mean()
+        kyy = self.gaussian_kernel(y, y).mean()
+        kxy = self.gaussian_kernel(x, y).mean()
+        return kxx + kyy - 2 * kxy
diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
index c684b3092..731270361 100644
--- a/domainlab/algos/trainers/train_coral.py
+++ b/domainlab/algos/trainers/train_coral.py
@@ -1,12 +1,11 @@
 """
-Alex, Xudong
+Alexej, Xudong
 """
-import numpy as np
 import torch
-from domainlab.algos.trainers.train_basic import TrainerBasic
+from domainlab.algos.trainers.mmd_base import TrainerMMDBase
 
 
-class TrainerCausalIRL(TrainerBasic):
+class TrainerCoral(TrainerMMDBase):
     """
     causal matching
     """
diff --git a/domainlab/algos/trainers/zoo_trainer.py b/domainlab/algos/trainers/zoo_trainer.py
index d1eccb59b..2d5529738 100644
--- a/domainlab/algos/trainers/zoo_trainer.py
+++ b/domainlab/algos/trainers/zoo_trainer.py
@@ -11,6 +11,7 @@
 from domainlab.algos.trainers.train_fishr import TrainerFishr
 from domainlab.algos.trainers.train_irm import TrainerIRM
 from domainlab.algos.trainers.train_causIRL import TrainerCausalIRL
+from domainlab.algos.trainers.train_coral import TrainerCoral
 
 
 class TrainerChainNodeGetter(object):
@@ -57,6 +58,7 @@ def __call__(self, lst_candidates=None, default=None, lst_excludes=None):
         chain = TrainerIRM(chain)
         chain = TrainerHyperScheduler(chain)
         chain = TrainerCausalIRL(chain)
+        chain = TrainerCoral(chain)
         node = chain.handle(self.request)
         head = node
         while self._list_str_trainer:
diff --git a/tests/test_coral.py b/tests/test_coral.py
new file mode 100644
index 000000000..8534ee11a
--- /dev/null
+++ b/tests/test_coral.py
@@ -0,0 +1,13 @@
+"""
+ end-end test
+"""
+from tests.utils_test import utils_test_algo
+
+
+def test_coral():
+    """
+    coral
+    """
+    args = "--te_d 0 --tr_d 3 7 --bs=32 --debug --task=mnistcolor10 \
+        --model=erm --nname=conv_bn_pool_2 --trainer=coral"
+    utils_test_algo(args)

From e51b7b5bb6f64ea90268df259a259db68615b6f8 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Mon, 16 Sep 2024 15:44:03 +0200
Subject: [PATCH 204/273] cross domain mmd

---
 domainlab/algos/trainers/train_coral.py | 69 ++++++++-----------------
 1 file changed, 21 insertions(+), 48 deletions(-)

diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
index 731270361..6fc8fbf1e 100644
--- a/domainlab/algos/trainers/train_coral.py
+++ b/domainlab/algos/trainers/train_coral.py
@@ -1,51 +1,30 @@
 """
-Alexej, Xudong
+Deep CORAL: Correlation Alignment for Deep
+Domain Adaptation
+[au] Alexej, Xudong
 """
-import torch
 from domainlab.algos.trainers.mmd_base import TrainerMMDBase
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg¬
 
 
 class TrainerCoral(TrainerMMDBase):
     """
-    causal matching
+    cross domain MMD
     """
-    def my_cdist(self, x1, x2):
-        """
-        distance for Gaussian
-        """
-        # along the last dimension
-        x1_norm = x1.pow(2).sum(dim=-1, keepdim=True)
-        x2_norm = x2.pow(2).sum(dim=-1, keepdim=True)
-        # x_2_norm is [batchsize, 1]
-        # matrix multiplication (2nd, 3rd) and addition to first argument
-        # X1[batchsize, dimfeat] * X2[dimfeat, batchsize)
-        # alpha: Scaling factor for the matrix product (default: 1)
-        # x2_norm.transpose(-2, -1) is row vector
-        # x_1_norm is column vector
-        res = torch.addmm(x2_norm.transpose(-2, -1),
-                          x1,
-                          x2.transpose(-2, -1), alpha=-2).add_(x1_norm)
-        return res.clamp_min_(1e-30)
-
-    def gaussian_kernel(self, x, y):
-        """
-        kernel for MMD
-        """
-        gamma=[0.001, 0.01, 0.1, 1, 10, 100, 1000]
-        dist = self.my_cdist(x, y)
-        tensor = torch.zeros_like(dist)
-        for g in gamma:
-            tensor.add_(torch.exp(dist.mul(-g)))
-        return tensor
-
-    def mmd(self, x, y):
-        """
-        maximum mean discrepancy
-        """
-        kxx = self.gaussian_kernel(x, x).mean()
-        kyy = self.gaussian_kernel(y, y).mean()
-        kxy = self.gaussian_kernel(x, y).mean()
-        return kxx + kyy - 2 * kxy
+    def cross_domain_mmd(self, tuple_data_domains_batch):
+        penalty = 0
+        list_loss_erm = []
+        num_domains = len(tuple_data_domains_batch)
+        for ind_domain_a in range(num_domains):
+            data_a, y_a, *_ = tuple_data_domains_batch[ind_domain_a]
+            feat_a = self.model.extract_semantic_feat(data_a)
+            list_loss_erm.append(self.cal_task_loss(data_a, y_a))
+            for ind_domain_b in range(ind_domain_a, num_domains):
+                data_b, y_b, *_ = tuple_data_domains_batch[ind_domain_b]
+                feat_b = self.model.extract_semantic_feat(data_b)
+                penalty += self.mmd(feat_a, feat_b)
+            list_loss_erm.append(self.cal_task_loss(data_a))
+        return list_loss_erm, loss_mmd
 
     def tr_epoch(self, epoch):
         list_loaders = list(self.dict_loader_tr.values())
@@ -56,12 +35,8 @@ def tr_epoch(self, epoch):
 
         for ind_batch, tuple_data_domains_batch in enumerate(loaders_zip):
             self.optimizer.zero_grad()
-            list_dict_var_grads, list_loss_erm = self.var_grads_and_loss(tuple_data_domains_batch)
-            dict_layerwise_var_var_grads = self.variance_between_dict(list_dict_var_grads)
-            dict_layerwise_var_var_grads_sum = \
-                {key: val.sum() for key, val in dict_layerwise_var_var_grads.items()}
-            loss_fishr = sum(dict_layerwise_var_var_grads_sum.values())
-            loss = sum(list_loss_erm) + get_gamma_reg(self.aconf, self.name) * loss_fishr
+            list_loss_erm, loss_mmd = self.cross_domain_mmd(tuple_data_domains_batch)
+            loss = sum(list_loss_erm) + get_gamma_reg(self.aconf, self.name) * loss_mmd
             loss.backward()
             self.optimizer.step()
             self.epo_loss_tr += loss.detach().item()
@@ -69,5 +44,3 @@ def tr_epoch(self, epoch):
 
         flag_stop = self.observer.update(epoch)  # notify observer
         return flag_stop
-
-

From 8fcbc12d73a67cd1474df9a1cd80e576b4d2f032 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Mon, 16 Sep 2024 15:51:12 +0200
Subject: [PATCH 205/273] fix invalid charater

---
 domainlab/algos/trainers/train_coral.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
index 6fc8fbf1e..7bfdef0d4 100644
--- a/domainlab/algos/trainers/train_coral.py
+++ b/domainlab/algos/trainers/train_coral.py
@@ -4,7 +4,7 @@
 [au] Alexej, Xudong
 """
 from domainlab.algos.trainers.mmd_base import TrainerMMDBase
-from domainlab.utils.hyperparameter_retrieval import get_gamma_reg¬
+from domainlab.utils.hyperparameter_retrieval import get_gamma_reg
 
 
 class TrainerCoral(TrainerMMDBase):
@@ -12,6 +12,9 @@ class TrainerCoral(TrainerMMDBase):
     cross domain MMD
     """
     def cross_domain_mmd(self, tuple_data_domains_batch):
+        """
+        domain-pairwise mmd
+        """
         penalty = 0
         list_loss_erm = []
         num_domains = len(tuple_data_domains_batch)

From fbd47f5fafaaaa1e9655a180d85320308e715f84 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 17 Sep 2024 07:36:18 +0200
Subject: [PATCH 206/273] Update train_coral.py

---
 domainlab/algos/trainers/train_coral.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
index 7bfdef0d4..68966db53 100644
--- a/domainlab/algos/trainers/train_coral.py
+++ b/domainlab/algos/trainers/train_coral.py
@@ -21,7 +21,7 @@ def cross_domain_mmd(self, tuple_data_domains_batch):
         for ind_domain_a in range(num_domains):
             data_a, y_a, *_ = tuple_data_domains_batch[ind_domain_a]
             feat_a = self.model.extract_semantic_feat(data_a)
-            list_loss_erm.append(self.cal_task_loss(data_a, y_a))
+            list_loss_erm.append(self.get_model().cal_task_loss(data_a, y_a))
             for ind_domain_b in range(ind_domain_a, num_domains):
                 data_b, y_b, *_ = tuple_data_domains_batch[ind_domain_b]
                 feat_b = self.model.extract_semantic_feat(data_b)

From 50a446d8e6e7c8e08c10774a022a65aa60c49a9a Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 17 Sep 2024 08:06:27 +0200
Subject: [PATCH 207/273] .

---
 domainlab/algos/trainers/train_coral.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
index 68966db53..72f0f8cc6 100644
--- a/domainlab/algos/trainers/train_coral.py
+++ b/domainlab/algos/trainers/train_coral.py
@@ -15,7 +15,7 @@ def cross_domain_mmd(self, tuple_data_domains_batch):
         """
         domain-pairwise mmd
         """
-        penalty = 0
+        loss_mmd = 0
         list_loss_erm = []
         num_domains = len(tuple_data_domains_batch)
         for ind_domain_a in range(num_domains):
@@ -23,10 +23,9 @@ def cross_domain_mmd(self, tuple_data_domains_batch):
             feat_a = self.model.extract_semantic_feat(data_a)
             list_loss_erm.append(self.get_model().cal_task_loss(data_a, y_a))
             for ind_domain_b in range(ind_domain_a, num_domains):
-                data_b, y_b, *_ = tuple_data_domains_batch[ind_domain_b]
+                data_b, *_ = tuple_data_domains_batch[ind_domain_b]
                 feat_b = self.model.extract_semantic_feat(data_b)
-                penalty += self.mmd(feat_a, feat_b)
-            list_loss_erm.append(self.cal_task_loss(data_a))
+                loss_mmd += self.mmd(feat_a, feat_b)
         return list_loss_erm, loss_mmd
 
     def tr_epoch(self, epoch):

From cf6996f04ce1c5402ecdcf3c85ec98160d861cda Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 17 Sep 2024 09:11:16 +0200
Subject: [PATCH 208/273] sum mmd batch

---
 domainlab/algos/trainers/train_coral.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
index 72f0f8cc6..703c720bf 100644
--- a/domainlab/algos/trainers/train_coral.py
+++ b/domainlab/algos/trainers/train_coral.py
@@ -25,7 +25,7 @@ def cross_domain_mmd(self, tuple_data_domains_batch):
             for ind_domain_b in range(ind_domain_a, num_domains):
                 data_b, *_ = tuple_data_domains_batch[ind_domain_b]
                 feat_b = self.model.extract_semantic_feat(data_b)
-                loss_mmd += self.mmd(feat_a, feat_b)
+                loss_mmd += sum(self.mmd(feat_a, feat_b))
         return list_loss_erm, loss_mmd
 
     def tr_epoch(self, epoch):

From 2b2c29c633cc7e08bf24dfdc98cf6465451226a2 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 17 Sep 2024 11:33:54 +0200
Subject: [PATCH 209/273] .

---
 domainlab/algos/trainers/train_coral.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
index 703c720bf..911bb220c 100644
--- a/domainlab/algos/trainers/train_coral.py
+++ b/domainlab/algos/trainers/train_coral.py
@@ -15,18 +15,18 @@ def cross_domain_mmd(self, tuple_data_domains_batch):
         """
         domain-pairwise mmd
         """
-        loss_mmd = 0
-        list_loss_erm = []
+        list_cross_domain_mmd = []
+        list_domain_erm_loss = []
         num_domains = len(tuple_data_domains_batch)
         for ind_domain_a in range(num_domains):
             data_a, y_a, *_ = tuple_data_domains_batch[ind_domain_a]
             feat_a = self.model.extract_semantic_feat(data_a)
-            list_loss_erm.append(self.get_model().cal_task_loss(data_a, y_a))
+            list_domain_erm_loss.append(self.get_model().cal_task_loss(data_a, y_a))
             for ind_domain_b in range(ind_domain_a, num_domains):
                 data_b, *_ = tuple_data_domains_batch[ind_domain_b]
                 feat_b = self.model.extract_semantic_feat(data_b)
-                loss_mmd += sum(self.mmd(feat_a, feat_b))
-        return list_loss_erm, loss_mmd
+                list_cross_domain_mmd.append(sum(self.mmd(feat_a, feat_b)))
+        return list_domain_erm_loss, list_cross_domain_mmd
 
     def tr_epoch(self, epoch):
         list_loaders = list(self.dict_loader_tr.values())
@@ -37,8 +37,8 @@ def tr_epoch(self, epoch):
 
         for ind_batch, tuple_data_domains_batch in enumerate(loaders_zip):
             self.optimizer.zero_grad()
-            list_loss_erm, loss_mmd = self.cross_domain_mmd(tuple_data_domains_batch)
-            loss = sum(list_loss_erm) + get_gamma_reg(self.aconf, self.name) * loss_mmd
+            list_domain_erm_loss, list_cross_domain_mmd = self.cross_domain_mmd(tuple_data_domains_batch)
+            loss = sum(list_domain_erm_loss) + get_gamma_reg(self.aconf, self.name) * sum(list_cross_domain_mmd)
             loss.backward()
             self.optimizer.step()
             self.epo_loss_tr += loss.detach().item()

From c078bc42acb6ee2ba59cc589bdf81a2f1e18e574 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 17 Sep 2024 11:35:07 +0200
Subject: [PATCH 210/273] .

---
 domainlab/algos/trainers/train_coral.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
index 911bb220c..6d9ad33bb 100644
--- a/domainlab/algos/trainers/train_coral.py
+++ b/domainlab/algos/trainers/train_coral.py
@@ -21,7 +21,7 @@ def cross_domain_mmd(self, tuple_data_domains_batch):
         for ind_domain_a in range(num_domains):
             data_a, y_a, *_ = tuple_data_domains_batch[ind_domain_a]
             feat_a = self.model.extract_semantic_feat(data_a)
-            list_domain_erm_loss.append(self.get_model().cal_task_loss(data_a, y_a))
+            list_domain_erm_loss.append(sum(self.get_model().cal_task_loss(data_a, y_a)))
             for ind_domain_b in range(ind_domain_a, num_domains):
                 data_b, *_ = tuple_data_domains_batch[ind_domain_b]
                 feat_b = self.model.extract_semantic_feat(data_b)

From 88ec169c07287fe771b36aa9e94375890e8dbf5c Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 17 Sep 2024 14:47:41 +0200
Subject: [PATCH 211/273] .

---
 domainlab/algos/trainers/train_coral.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
index 6d9ad33bb..bd60e40bd 100644
--- a/domainlab/algos/trainers/train_coral.py
+++ b/domainlab/algos/trainers/train_coral.py
@@ -25,7 +25,8 @@ def cross_domain_mmd(self, tuple_data_domains_batch):
             for ind_domain_b in range(ind_domain_a, num_domains):
                 data_b, *_ = tuple_data_domains_batch[ind_domain_b]
                 feat_b = self.model.extract_semantic_feat(data_b)
-                list_cross_domain_mmd.append(sum(self.mmd(feat_a, feat_b)))
+                mmd = self.mmd(feat_a, feat_b)
+                list_cross_domain_mmd.append(sum(mmd))
         return list_domain_erm_loss, list_cross_domain_mmd
 
     def tr_epoch(self, epoch):

From 50ce5a9b64c0e657edf64023002489483fa6d035 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 17 Sep 2024 15:06:27 +0200
Subject: [PATCH 212/273] put all examples in doc_example.md into separate docs

---
 docs/conf.py          |   5 --
 docs/docDIAL.md       |  16 ++++
 docs/docHDUVA.md      |  51 ++++++++++---
 docs/docJiGen.md      |  14 ++++
 docs/docMatchDG.md    |  26 +++++++
 docs/doc_custom_nn.md |  20 +++++
 docs/doc_diva.md      |  30 ++++++++
 docs/doc_examples.md  | 169 ------------------------------------------
 docs/doc_mldg.md      |   7 ++
 docs/doc_tasks.md     |  47 ++++++++++++
 10 files changed, 202 insertions(+), 183 deletions(-)
 delete mode 100755 docs/doc_examples.md

diff --git a/docs/conf.py b/docs/conf.py
index ea547e0d7..0a0c8b1d3 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -168,11 +168,6 @@
             "internal": True,
             "title": "Examples with MNIST",
         },
-        {
-            "href": "doc_examples",
-            "internal": True,
-            "title": "More commandline examples",
-        },
         {"href": "doc_benchmark", "internal": True, "title": "Benchmarks tutorial"},
         {"href": "doc_output", "internal": True, "title": "Output Structure"},
         {
diff --git a/docs/docDIAL.md b/docs/docDIAL.md
index 600f8b2cb..9f0a38e47 100644
--- a/docs/docDIAL.md
+++ b/docs/docDIAL.md
@@ -78,3 +78,19 @@ This procedure yields to the following availability of hyperparameter:
 ```
 python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=dial --nname=conv_bn_pool_2
 ```
+
+
+
+## Adversarial images training
+```shell
+python main_out.py --te_d=0 --task=mnistcolor10 --keep_model --model=erm --trainer=dial --nname=conv_bn_pool_2
+```
+### Train DIVA model with DIAL trainer
+
+```shell
+python main_out.py --te_d 0 1 2 --tr_d 3 7 --task=mnistcolor10 --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=7e5 --gamma_d=1e5 --trainer=dial
+```
+### Set hyper-parameters for trainer as well
+```shell
+python main_out.py --te_d 0 1 2 --tr_d 3 7 --task=mnistcolor10 --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=7e5 --gamma_d=1e5 --trainer=dial --dial_steps_perturb=1
+```
diff --git a/docs/docHDUVA.md b/docs/docHDUVA.md
index 47af4d344..dbf3c429c 100644
--- a/docs/docHDUVA.md
+++ b/docs/docHDUVA.md
@@ -52,7 +52,38 @@ Alternatively, one could use an existing neural network in DomainLab using `nnam
 
 ## Hyperparameter for warmup
 Finally, the number of epochs for hyper-parameter warm-up can be specified via the argument `warmup`.
+
+
+
+Please cite our paper if you find it useful!
+```text
+@inproceedings{sun2021hierarchical,
+  title={Hierarchical Variational Auto-Encoding for Unsupervised Domain Generalization},
+  author={Sun, Xudong and Buettner, Florian},
+  booktitle={ICLR 2021 RobustML workshop, https://arxiv.org/pdf/2101.09436.pdf},
+  year={2021}
+}
+```
+
+
+
 ## Examples
+
+### hduva use custom net for sandwich encoder
+```shell
+python main_out.py --te_d=caltech --bs=2 --task=mini_vlcs --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --npath_encoder_sandwich_x2h4zd=examples/nets/resnet.py
+```
+
+### hduva use custom net for topic encoder
+```shell
+python main_out.py --te_d=caltech --bs=2 --task=mini_vlcs --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --npath_encoder_x2topic_h=examples/nets/resnet.py --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
+```
+
+### hduva use custom net for classification encoder
+```shell
+python main_out.py --te_d=caltech --bs=2 --task=mini_vlcs --model=hduva --npath=examples/nets/resnet.py --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
+```
+
 ### use hduva on color mnist, train on 2 domains
 ```shell
 python main_out.py --tr_d 0 1 2 --te_d 3 --bs=2 --task=mnistcolor10 --model=hduva  --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
@@ -63,14 +94,16 @@ python main_out.py --tr_d 0 1 2 --te_d 3 --bs=2 --task=mnistcolor10 --model=hduv
 python main_out.py --tr_d 0  --te_d 3 4 --bs=2 --task=mnistcolor10 --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
 ```
 
+### hduva with implemented neural network
+```shell
+python main_out.py --te_d=caltech --bs=2 --task=mini_vlcs --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
+```
 
-
-Please cite our paper if you find it useful!
-```text
-@inproceedings{sun2021hierarchical,
-  title={Hierarchical Variational Auto-Encoding for Unsupervised Domain Generalization},
-  author={Sun, Xudong and Buettner, Florian},
-  booktitle={ICLR 2021 RobustML workshop, https://arxiv.org/pdf/2101.09436.pdf},
-  year={2021}
-}
+### hduva use alex net
+```shell
+python main_out.py --te_d=caltech --bs=2 --task=mini_vlcs --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=alexnet
 ```
+
+
+
+
diff --git a/docs/docJiGen.md b/docs/docJiGen.md
index dc67c3c02..8da6e8270 100644
--- a/docs/docJiGen.md
+++ b/docs/docJiGen.md
@@ -36,3 +36,17 @@ Furthermore, the user can specify a custom grid length via `grid_len`.
 
 _Reference_: Carlucci, Fabio M., et al. "Domain generalization by solving jigsaw puzzles."
 Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019.
+
+
+## Examples
+
+### model jigen with implemented neural network
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=jigen --nname=alexnet --pperm=1 --nperm=100 --grid_len=3
+```
+
+
+### sannity check with jigen tile shuffling
+```shell
+python main_out.py --te_d=sketch --tpath=examples/tasks/demo_task_path_list_small.py --debug --bs=8 --model=jigen --nname=alexnet --pperm=1 --nperm=100 --grid_len=3 --san_check
+```
diff --git a/docs/docMatchDG.md b/docs/docMatchDG.md
index 96eea99f1..816196a82 100644
--- a/docs/docMatchDG.md
+++ b/docs/docMatchDG.md
@@ -69,3 +69,29 @@ This procedure yields to the following availability of hyperparameter:
 - `--epochs_ctr`: number of epochs for minimizing the contrastive loss in phase 1.
 - `--epos_per_match_update`: Number of epochs before updating the match tensor. ($t$ from phase 1)
 - `--gamma_reg`: weight for the regularization term in phase 2. ($\gamma_\text{reg}$ from phase 2)
+- 
+## Examples
+
+### trainer matchdg with custom neural network
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --bs=2 --model=erm --trainer=matchdg --epochs_ctr=3 --epos=6 --npath=examples/nets/resnet.py
+```
+
+
+### training hduva with matchdg
+
+```shell
+python main_out.py --te_d 0 1 2 --tr_d 3 7 --task=mnistcolor10 --bs=2 --model=hduva --trainer=matchdg --epochs_ctr=3 --epos=6 --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
+```
+
+### training implemented neural network with matchdg
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm --trainer=matchdg --epochs_ctr=3 --epos=6 --nname=alexnet
+```
+
+### trainer matchdg with mnist
+```shell
+ python main_out.py --te_d 0 1 2 --tr_d 3 7 --task=mnistcolor10 --model=erm --trainer=matchdg --nname=conv_bn_pool_2 --epochs_ctr=2 --epos=6
+```
+
+
diff --git a/docs/doc_custom_nn.md b/docs/doc_custom_nn.md
index 4a91b8b64..fab279c6d 100644
--- a/docs/doc_custom_nn.md
+++ b/docs/doc_custom_nn.md
@@ -23,3 +23,23 @@ python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm --
 ```shell
 python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm --trainer=matchdg --epochs_ctr=3 --epos=6 --npath=examples/nets/resnet.py
 ```
+
+
+### model erm with custom neural network
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=erm --npath=examples/nets/resnet.py
+```
+
+## Larger images:
+
+### model erm with implemented neural network
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=erm --nname=alexnet
+```
+
+### model dann with implemented neural network
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=dann --nname=alexnet
+```
+
+
diff --git a/docs/doc_diva.md b/docs/doc_diva.md
index b083e7fca..741e2fef1 100644
--- a/docs/doc_diva.md
+++ b/docs/doc_diva.md
@@ -40,5 +40,35 @@ Furthermore, the user can specify the neural networks for the class and domain c
 - `nname`/`npath`
 - `nname_dom`/`npath_dom`
 
+
+## Examples
+### model diva with implemented neural network
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=2 --model=diva --nname=alexnet --npath_dom=examples/nets/resnet.py --gamma_y=7e5 --gamma_d=1e5
+```
+
+### model diva with custom neural network
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=2 --model=diva --npath=examples/nets/resnet.py --npath_dom=examples/nets/resnet.py --gamma_y=7e5 --gamma_d=1e5
+```
+### generation of images
+```shell
+python main_out.py --te_d=0 --task=mnistcolor10 --keep_model --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=10e5 --gamma_d=1e5 --gen
+```
+## Colored version of MNIST
+
+### leave one domain out
+```shell
+python main_out.py --te_d=0 --task=mnistcolor10 --keep_model --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=10e5 --gamma_d=1e5
+```
+
+### choose train and test
+```shell
+python main_out.py --te_d 0 1 2 --tr_d 3 7 --task=mnistcolor10 --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=7e5 --gamma_d=1e5
+```
+
+
+
+
 _Reference:_
 DIVA: Domain Invariant Variational Autoencoders, https://arxiv.org/pdf/1905.10427.pdf, Medical Imaging with Deep Learning. PMLR, 2020.
diff --git a/docs/doc_examples.md b/docs/doc_examples.md
deleted file mode 100755
index 0dddc5f5b..000000000
--- a/docs/doc_examples.md
+++ /dev/null
@@ -1,169 +0,0 @@
-# Command line examples
-
-## Colored version of MNIST
-
-### leave one domain out
-```shell
-python main_out.py --te_d=0 --task=mnistcolor10 --keep_model --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=10e5 --gamma_d=1e5
-```
-
-### choose train and test
-```shell
-python main_out.py --te_d 0 1 2 --tr_d 3 7 --task=mnistcolor10 --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=7e5 --gamma_d=1e5
-```
-
-### make a sanity check for the dataset using 8 instances from each domain and from each class
-```shell
-python main_out.py --te_d=0 --task=mini_vlcs --debug --bs=2 --model=diva --nname=alexnet --npath_dom=examples/nets/resnet.py --gamma_y=7e5 --gamma_d=1e5 --san_check --san_num=4
-```
-### sanity check on only 2 train domains and 2 test domain2
-```shell
-python main_out.py --te_d 0 1 --tr_d 3 5 --task=mnistcolor10 --debug --bs=2 --model=erm --nname=conv_bn_pool_2 --san_check --san_num=4
-```
-
-### generation of images
-```shell
-python main_out.py --te_d=0 --task=mnistcolor10 --keep_model --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=10e5 --gamma_d=1e5 --gen
-```
-
-
-## Larger images:
-
-### model diva with implemented neural network
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=2 --model=diva --nname=alexnet --npath_dom=examples/nets/resnet.py --gamma_y=7e5 --gamma_d=1e5
-```
-
-### model diva with custom neural network
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=2 --model=diva --npath=examples/nets/resnet.py --npath_dom=examples/nets/resnet.py --gamma_y=7e5 --gamma_d=1e5
-```
-
-### model erm with implemented neural network
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=erm --nname=alexnet
-```
-
-### model dann with implemented neural network
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=dann --nname=alexnet
-```
-
-### model jigen with implemented neural network
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=jigen --nname=alexnet --pperm=1 --nperm=100 --grid_len=3
-```
-
-
-### sannity check with jigen tile shuffling
-```shell
-python main_out.py --te_d=sketch --tpath=examples/tasks/demo_task_path_list_small.py --debug --bs=8 --model=jigen --nname=alexnet --pperm=1 --nperm=100 --grid_len=3 --san_check
-```
-
-### training implemented neural network with matchdg
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm --trainer=matchdg --epochs_ctr=3 --epos=6 --nname=alexnet
-```
-
-### trainer matchdg with mnist
-```shell
- python main_out.py --te_d 0 1 2 --tr_d 3 7 --task=mnistcolor10 --model=erm --trainer=matchdg --nname=conv_bn_pool_2 --epochs_ctr=2 --epos=6
-```
-
-### hduva with implemented neural network
-```shell
-python main_out.py --te_d=caltech --bs=2 --task=mini_vlcs --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
-```
-
-### hduva use alex net
-```shell
-python main_out.py --te_d=caltech --bs=2 --task=mini_vlcs --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=alexnet
-```
-
-
-## Custom Neural Network
-
-### model erm with custom neural network
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=erm --npath=examples/nets/resnet.py
-```
-
-### trainer matchdg with custom neural network
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --bs=2 --model=erm --trainer=matchdg --epochs_ctr=3 --epos=6 --npath=examples/nets/resnet.py
-```
-
-
-### training hduva with matchdg
-
-```shell
-python main_out.py --te_d 0 1 2 --tr_d 3 7 --task=mnistcolor10 --bs=2 --model=hduva --trainer=matchdg --epochs_ctr=3 --epos=6 --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
-```
-
-### hduva use custom net for sandwich encoder
-```shell
-python main_out.py --te_d=caltech --bs=2 --task=mini_vlcs --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --npath_encoder_sandwich_x2h4zd=examples/nets/resnet.py
-```
-
-### hduva use custom net for topic encoder
-```shell
-python main_out.py --te_d=caltech --bs=2 --task=mini_vlcs --model=hduva --nname=conv_bn_pool_2 --gamma_y=7e5 --npath_encoder_x2topic_h=examples/nets/resnet.py --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
-```
-
-### hduva use custom net for classification encoder
-```shell
-python main_out.py --te_d=caltech --bs=2 --task=mini_vlcs --model=hduva --npath=examples/nets/resnet.py --gamma_y=7e5 --nname_encoder_x2topic_h=conv_bn_pool_2 --nname_encoder_sandwich_x2h4zd=conv_bn_pool_2
-```
-
-
-## User defined tasks
-
-### Folder Task
-#### Folder Task with implemented neural network
-```shell
-python main_out.py --te_d=caltech --tpath=examples/tasks/task_vlcs.py --debug --bs=2 --nname=alexnet --model=diva --nname_dom=alexnet --gamma_y=7e5 --gamma_d=1e5
-```
-
-#### Folder Task with externally user defined neural network
-```shell
-python main_out.py --te_d=caltech --tpath=examples/tasks/task_vlcs.py --debug --bs=2 --npath=examples/nets/resnet.py --model=diva --npath_dom=examples/nets/resnet.py --gamma_y=7e5 --gamma_d=1e5
-```
-
-### ImagePath Task
-#### ImagePath Task with implemented algorithm
-```shell
-python main_out.py --te_d=sketch --tpath=examples/tasks/demo_task_path_list_small.py --debug --bs=2 --nname=alexnet --model=diva --nname_dom=alexnet --gamma_y=7e5 --gamma_d=1e5
-```
-
-#### ImagePath Task with externally user defined neural network
-```shell
-python main_out.py --te_d=sketch --tpath=examples/tasks/demo_task_path_list_small.py --debug --bs=2 --npath=examples/nets/resnet.py --model=diva --npath_dom=examples/nets/resnet.py --gamma_y=7e5 --gamma_d=1e5
-```
-
-## Custom algorithm defined in external python file
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=3 --apath=examples/models/demo_custom_model.py --model=custom --nname_argna2val my_custom_arg_name --nname_argna2val alexnet
-```
-
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=3 --apath=examples/models/demo_custom_model.py --model=custom --npath_argna2val my_custom_arg_name --npath_argna2val examples/nets/resnet.py
-```
-
-## Adversarial images training
-```shell
-python main_out.py --te_d=0 --task=mnistcolor10 --keep_model --model=erm --trainer=dial --nname=conv_bn_pool_2
-```
-### Train DIVA model with DIAL trainer
-
-```shell
-python main_out.py --te_d 0 1 2 --tr_d 3 7 --task=mnistcolor10 --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=7e5 --gamma_d=1e5 --trainer=dial
-```
-### Set hyper-parameters for trainer as well
-```shell
-python main_out.py --te_d 0 1 2 --tr_d 3 7 --task=mnistcolor10 --model=diva --nname=conv_bn_pool_2 --nname_dom=conv_bn_pool_2 --gamma_y=7e5 --gamma_d=1e5 --trainer=dial --dial_steps_perturb=1
-```
-
-## Meta Learning Domain Generalization
-```shell
-python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=erm --trainer=mldg --nname=alexnet
-```
diff --git a/docs/doc_mldg.md b/docs/doc_mldg.md
index 694f4b3d8..47b061620 100644
--- a/docs/doc_mldg.md
+++ b/docs/doc_mldg.md
@@ -2,3 +2,10 @@
 ##  Meta Learning Domain Generalization
 
 Li, Da, et al. "Learning to generalize: Meta-learning for domain generalization." Proceedings of the AAAI conference on artificial intelligence. Vol. 32. No. 1. 2018.
+
+
+# Examples
+## Meta Learning Domain Generalization
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=erm --trainer=mldg --nname=alexnet
+```
diff --git a/docs/doc_tasks.md b/docs/doc_tasks.md
index 21a774c59..d469ab491 100644
--- a/docs/doc_tasks.md
+++ b/docs/doc_tasks.md
@@ -156,3 +156,50 @@ of domain information so only a unique transform (composition) is allowed.
 as the absolute path to each domain's data.
 
 `taskna`: user defined task name
+
+
+
+## Examples
+
+## User defined tasks
+
+### Folder Task
+#### Folder Task with implemented neural network
+```shell
+python main_out.py --te_d=caltech --tpath=examples/tasks/task_vlcs.py --debug --bs=2 --nname=alexnet --model=diva --nname_dom=alexnet --gamma_y=7e5 --gamma_d=1e5
+```
+
+#### Folder Task with externally user defined neural network
+```shell
+python main_out.py --te_d=caltech --tpath=examples/tasks/task_vlcs.py --debug --bs=2 --npath=examples/nets/resnet.py --model=diva --npath_dom=examples/nets/resnet.py --gamma_y=7e5 --gamma_d=1e5
+```
+
+### ImagePath Task
+#### ImagePath Task with implemented algorithm
+```shell
+python main_out.py --te_d=sketch --tpath=examples/tasks/demo_task_path_list_small.py --debug --bs=2 --nname=alexnet --model=diva --nname_dom=alexnet --gamma_y=7e5 --gamma_d=1e5
+```
+
+#### ImagePath Task with externally user defined neural network
+```shell
+python main_out.py --te_d=sketch --tpath=examples/tasks/demo_task_path_list_small.py --debug --bs=2 --npath=examples/nets/resnet.py --model=diva --npath_dom=examples/nets/resnet.py --gamma_y=7e5 --gamma_d=1e5
+```
+
+## Custom algorithm defined in external python file
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=3 --apath=examples/models/demo_custom_model.py --model=custom --nname_argna2val my_custom_arg_name --nname_argna2val alexnet
+```
+
+```shell
+python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=3 --apath=examples/models/demo_custom_model.py --model=custom --npath_argna2val my_custom_arg_name --npath_argna2val examples/nets/resnet.py
+```
+
+
+### make a sanity check for the dataset using 8 instances from each domain and from each class
+```shell
+python main_out.py --te_d=0 --task=mini_vlcs --debug --bs=2 --model=diva --nname=alexnet --npath_dom=examples/nets/resnet.py --gamma_y=7e5 --gamma_d=1e5 --san_check --san_num=4
+```
+### sanity check on only 2 train domains and 2 test domain2
+```shell
+python main_out.py --te_d 0 1 --tr_d 3 5 --task=mnistcolor10 --debug --bs=2 --model=erm --nname=conv_bn_pool_2 --san_check --san_num=4
+```

From 5a164a96dd80092d2c0c88f413683cb83046934c Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 17 Sep 2024 15:38:08 +0200
Subject: [PATCH 213/273] .

---
 domainlab/algos/trainers/train_coral.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/domainlab/algos/trainers/train_coral.py b/domainlab/algos/trainers/train_coral.py
index bd60e40bd..a8f7c3f05 100644
--- a/domainlab/algos/trainers/train_coral.py
+++ b/domainlab/algos/trainers/train_coral.py
@@ -20,13 +20,13 @@ def cross_domain_mmd(self, tuple_data_domains_batch):
         num_domains = len(tuple_data_domains_batch)
         for ind_domain_a in range(num_domains):
             data_a, y_a, *_ = tuple_data_domains_batch[ind_domain_a]
-            feat_a = self.model.extract_semantic_feat(data_a)
+            feat_a = self.get_model().extract_semantic_feat(data_a)
             list_domain_erm_loss.append(sum(self.get_model().cal_task_loss(data_a, y_a)))
             for ind_domain_b in range(ind_domain_a, num_domains):
                 data_b, *_ = tuple_data_domains_batch[ind_domain_b]
-                feat_b = self.model.extract_semantic_feat(data_b)
+                feat_b = self.get_model().extract_semantic_feat(data_b)
                 mmd = self.mmd(feat_a, feat_b)
-                list_cross_domain_mmd.append(sum(mmd))
+                list_cross_domain_mmd.append(mmd)
         return list_domain_erm_loss, list_cross_domain_mmd
 
     def tr_epoch(self, epoch):

From c46205b08c1226fe7a1291801b14525e9b397a58 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 17 Sep 2024 16:01:29 +0200
Subject: [PATCH 214/273] .

---
 docs/docDIAL.md  | 3 +--
 docs/docFishr.md | 2 +-
 docs/docIRM.md   | 2 +-
 docs/doc_mldg.md | 3 +--
 4 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/docs/docDIAL.md b/docs/docDIAL.md
index 9f0a38e47..3aa28a49f 100644
--- a/docs/docDIAL.md
+++ b/docs/docDIAL.md
@@ -73,7 +73,7 @@ This procedure yields to the following availability of hyperparameter:
 - `--gamma_reg`: ? ($\epsilon$ in the paper)
 - `--lr`: learning rate ($\alpha$ in the paper)
 
-# Examples
+## Examples
 
 ```
 python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=dial --nname=conv_bn_pool_2
@@ -81,7 +81,6 @@ python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=dial --nna
 
 
 
-## Adversarial images training
 ```shell
 python main_out.py --te_d=0 --task=mnistcolor10 --keep_model --model=erm --trainer=dial --nname=conv_bn_pool_2
 ```
diff --git a/docs/docFishr.md b/docs/docFishr.md
index e2ba4c1b9..90c2da6b4 100644
--- a/docs/docFishr.md
+++ b/docs/docFishr.md
@@ -72,7 +72,7 @@ For more details, see the reference below or the domainlab code.
 
 
 
-# Examples
+## Examples
 ```
 python main_out.py --te_d=0 --task=mini_vlcs --model=erm --trainer=fishr --nname=alexnet --bs=2 --nocu
 ```
diff --git a/docs/docIRM.md b/docs/docIRM.md
index 0b8114de8..57d033db7 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -26,7 +26,7 @@ where $\lambda$ is a hyperparameter that controls the trade-off between the empi
 In practice, one could simply divide one mini-batch into two subsets, let $i$ and $j$ to index these two subsets, multiply  subset $i$ and subset $j$ forms an unbiased estimation of the L2 norm of gradient.
 In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \ell(w \circ \Phi(X^{(d, i)}), Y^{(d, i)})$ of dimension dim(Grad) with $\nabla_{w|w=1} \ell(w \circ \Phi(X^{(d, j)}), Y^{(d, j)})$ of dimension dim(Grad) For more details, see section 3.2 and Appendix D of : Arjovsky et al., “Invariant Risk Minimization.”
 
-# Examples
+## Examples
 ```shell
 python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=irm --nname=conv_bn_pool_2
 
diff --git a/docs/doc_mldg.md b/docs/doc_mldg.md
index 47b061620..92e412180 100644
--- a/docs/doc_mldg.md
+++ b/docs/doc_mldg.md
@@ -4,8 +4,7 @@
 Li, Da, et al. "Learning to generalize: Meta-learning for domain generalization." Proceedings of the AAAI conference on artificial intelligence. Vol. 32. No. 1. 2018.
 
 
-# Examples
-## Meta Learning Domain Generalization
+## Examples
 ```shell
 python main_out.py --te_d=caltech --task=mini_vlcs --debug --bs=8 --model=erm --trainer=mldg --nname=alexnet
 ```

From 206953bceb3d839625807fe6f20c9942d8fd56b6 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 17 Sep 2024 19:10:48 +0200
Subject: [PATCH 215/273] .

---
 docs/doc_coral.md | 12 ++++++++++++
 docs/doc_irl.md   | 10 ++++++++++
 docs/index.rst    |  2 ++
 3 files changed, 24 insertions(+)
 create mode 100644 docs/doc_coral.md
 create mode 100644 docs/doc_irl.md

diff --git a/docs/doc_coral.md b/docs/doc_coral.md
new file mode 100644
index 000000000..a79be02b7
--- /dev/null
+++ b/docs/doc_coral.md
@@ -0,0 +1,12 @@
+# Deep CORAL
+## Deep CORAL: Correlation Alignment for Deep Domain Adaptation
+
+nonlinear transformation that aligns correlations of
+layer activations in deep neural network
+https://arxiv.org/pdf/1607.01719
+
+## Examples
+
+```
+python main_out.py --te_d 0 --tr_d 3 7 --bs=32 --epos=1 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=coral
+```
diff --git a/docs/doc_irl.md b/docs/doc_irl.md
new file mode 100644
index 000000000..74dce30c0
--- /dev/null
+++ b/docs/doc_irl.md
@@ -0,0 +1,10 @@
+# Causal IRL
+# Invariant Causal Mechanisms through Distribution Matching
+
+Source: https://arxiv.org/pdf/2206.11646 
+
+## Example
+
+```
+python main_out.py --te_d 0 --tr_d 3 7 --bs=32 --debug --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=causalirl"
+``` 
diff --git a/docs/index.rst b/docs/index.rst
index 548cd5f84..d6226f5c9 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -22,6 +22,8 @@ Welcome to domainlab's documentation!
    doc_mldg
    docIRM
    docMA
+   doc_coral
+   doc_irl
 
 
 Indices and tables

From d466b75f6205f26b3630ce8e89078fdc25d7cda6 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 18 Sep 2024 11:29:07 +0200
Subject: [PATCH 216/273] .

---
 docs/docIRM.md | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/docs/docIRM.md b/docs/docIRM.md
index 57d033db7..e703b3ef6 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -7,9 +7,10 @@ where we use $\ell$ to denote the cross entropy for a classification task, and $
 
 The idea of IRM is to choose classifier $w$ to be in the intersection of optimal classifiers for each domain $$d$$.
 
-$$w \in {\argmin}_{\bar{w}} \ell^{(d)}(\bar{w} \circ \Phi) \quad \forall d$$
+$$w \in {\arg\min}_{\bar{w}} \ell^{(d)}(\bar{w} \circ \Phi) \quad \forall d$$
 
-regardless of feature extractor $$\Phi(\cdot)$$, this serves as a constraint on the choice of classifiers $w$.
+regardless of feature extractor $\Phi(\cdot)$, 
+this serves as a constraint on the choice of classifiers $w$.
 
 The feature extractor $\Phi(\cdot)$ then get optimized under this constraint.
 

From 12c107378065379eff103f0da2ac6ddfe60bc2f1 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 18 Sep 2024 13:16:30 +0200
Subject: [PATCH 217/273] 0.7.0

---
 pyproject.toml | 2 +-
 setup.py       | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index fa64c0b81..02fb0e856 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "domainlab"
-version = "0.6.5"
+version = "0.7.0"
 readme = "README.md"
 repository = "https://github.com/marrlab/DomainLab"
 homepage = "https://marrlab.github.io/DomainLab/"
diff --git a/setup.py b/setup.py
index 3738e48e7..5ea48277c 100644
--- a/setup.py
+++ b/setup.py
@@ -38,7 +38,7 @@ def copy_dir(dir_path="zdata"):
     package_data={
         "zdata": [f for f in copy_dir()],
     },
-    version="0.6.5",
+    version="0.7.0",
     description="Library of modular domain generalization for deep learning",
     url="https://github.com/marrlab/DomainLab",
     author="Xudong Sun, et.al.",

From 93d59c8ed858d73f668d414d51b2a5bd2d432eda Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 19 Sep 2024 12:28:51 +0200
Subject: [PATCH 218/273] fix typo in irm doc

---
 docs/docIRM.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/docIRM.md b/docs/docIRM.md
index e703b3ef6..fd097e2aa 100644
--- a/docs/docIRM.md
+++ b/docs/docIRM.md
@@ -22,7 +22,7 @@ In DomainLab, we write the loss function as $$\ell(\cdot) + \lambda R(\cdot)$$,
 
 $$\min_{\Phi, w} \sum_{d} \ell^{(d)}(w \circ \Phi) + \lambda \sum_{d} \|\nabla_{w|w=1.0} \ell^{(d)}(w \circ \Phi)\|^2$$
 
-where $\lambda$ is a hyperparameter that controls the trade-off between the empirical risk and the penalty. One interpretation can be the penalty encourages the representation $\Phi$ to be small evaluated at $w = 1.0$ across all domains.
+where $\lambda$ is a hyperparameter that controls the trade-off between the empirical risk and the penalty. One interpretation can be the penalty encourages the representation $\Phi$ to be orthogonal to the gradient of the loss (e.g. cross entropy) at $w = 1.0$ across all domains.
 
 In practice, one could simply divide one mini-batch into two subsets, let $i$ and $j$ to index these two subsets, multiply  subset $i$ and subset $j$ forms an unbiased estimation of the L2 norm of gradient.
 In detail: the squared gradient norm via inner product between $\nabla_{w|w=1} \ell(w \circ \Phi(X^{(d, i)}), Y^{(d, i)})$ of dimension dim(Grad) with $\nabla_{w|w=1} \ell(w \circ \Phi(X^{(d, j)}), Y^{(d, j)})$ of dimension dim(Grad) For more details, see section 3.2 and Appendix D of : Arjovsky et al., “Invariant Risk Minimization.”

From c7cf554f4ee53f1fa704c0fca0d8c9e1a367ede8 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 27 Sep 2024 16:11:40 +0200
Subject: [PATCH 219/273] fix doc IRL

---
 docs/doc_irl.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/doc_irl.md b/docs/doc_irl.md
index 74dce30c0..46a907314 100644
--- a/docs/doc_irl.md
+++ b/docs/doc_irl.md
@@ -1,5 +1,5 @@
 # Causal IRL
-# Invariant Causal Mechanisms through Distribution Matching
+## Invariant Causal Mechanisms through Distribution Matching
 
 Source: https://arxiv.org/pdf/2206.11646 
 

From b2b204d831efa48226d13a62f7f6fe7d552bdeed Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 4 Oct 2024 16:48:45 +0200
Subject: [PATCH 220/273] copy branch fbopt_vector_ki_gain to mhof_dev

---
 domainlab/algos/trainers/fbopt_mu_controller.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/domainlab/algos/trainers/fbopt_mu_controller.py b/domainlab/algos/trainers/fbopt_mu_controller.py
index 824638461..f61b4bc63 100644
--- a/domainlab/algos/trainers/fbopt_mu_controller.py
+++ b/domainlab/algos/trainers/fbopt_mu_controller.py
@@ -50,7 +50,8 @@ def __init__(self, trainer, **kwargs):
         self.mmu = {key: self.init_mu for key, val in self.mmu.items()}
         self.set_point_controller = FbOptSetpointController(args=self.trainer.aconf)
 
-        self.k_i_control = trainer.aconf.k_i_gain
+        self.k_i_control = [trainer.aconf.k_i_gain for i in
+                            range(len(self.mmu))]
         self.k_i_gain_ratio = None
         self.overshoot_rewind = trainer.aconf.overshoot_rewind == "yes"
         self.delta_epsilon_r = None
@@ -84,7 +85,7 @@ def set_k_i_gain(self, epo_reg_loss):
         k_i_gain_saturate_min = min(k_i_gain_saturate)
         # NOTE: here we override the commandline arguments specification
         # for k_i_control, so k_i_control is not a hyperparameter anymore
-        self.k_i_control = self.k_i_gain_ratio * k_i_gain_saturate_min
+        self.k_i_control = [self.k_i_gain_ratio * ele for ele in k_i_gain_saturate]
         warnings.warn(
             f"hyperparameter k_i_gain disabled! \
                       replace with {self.k_i_control}"
@@ -162,7 +163,7 @@ def cal_activation(self):
         """
         setpoint = self.get_setpoint4r()
         activation = [
-            self.k_i_control * val if setpoint[i] > 0 else self.k_i_control * (-val)
+            self.k_i_control[i] * val if setpoint[i] > 0 else self.k_i_control[i] * (-val)
             for i, val in enumerate(self.delta_epsilon_r)
         ]
         if self.activation_clip is not None:

From 0678950198792e66bef4ee1d9d84022e903dbc0e Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sat, 5 Oct 2024 15:55:43 +0200
Subject: [PATCH 221/273] rename yaml

---
 .../{pacs_fbopt_irm_erm.yaml => aistat_irm_erm_mhof.yaml}         | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 rename examples/benchmark/{pacs_fbopt_irm_erm.yaml => aistat_irm_erm_mhof.yaml} (100%)

diff --git a/examples/benchmark/pacs_fbopt_irm_erm.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
similarity index 100%
rename from examples/benchmark/pacs_fbopt_irm_erm.yaml
rename to examples/benchmark/aistat_irm_erm_mhof.yaml

From 9a018115b99949bbd2d31cc836e2098347d7f083 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sat, 5 Oct 2024 15:56:08 +0200
Subject: [PATCH 222/273] erm alone more hyper

---
 examples/benchmark/aistat_irm_erm_only.yaml | 58 +++++++++++++++++++++
 1 file changed, 58 insertions(+)
 create mode 100644 examples/benchmark/aistat_irm_erm_only.yaml

diff --git a/examples/benchmark/aistat_irm_erm_only.yaml b/examples/benchmark/aistat_irm_erm_only.yaml
new file mode 100644
index 000000000..299ec528c
--- /dev/null
+++ b/examples/benchmark/aistat_irm_erm_only.yaml
@@ -0,0 +1,58 @@
+mode: grid
+
+output_dir: zoutput/benchmarks/benchmark_irm_erm
+
+sampling_seed: 0
+startseed: 0
+endseed: 2
+
+test_domains:
+  - sketch
+
+domainlab_args:
+  tpath: examples/tasks/task_pacs_aug.py
+  dmem: False
+  lr: 5e-5
+  epos: 500
+  epos_min: 200
+  es: 5
+  bs: 32
+  san_check: False
+  npath: examples/nets/resnet50domainbed.py
+  npath_dom: examples/nets/resnet50domainbed.py
+  zx_dim: 0
+  zy_dim: 64
+  zd_dim: 64
+
+
+
+
+Shared params:
+  ini_setpoint_ratio:
+    min: 0.5
+    max: 0.99
+    num: 2
+    step: 0.05
+    distribution: uniform
+
+  k_i_gain:
+    min: 0.0001
+    max: 0.01
+    num: 2
+    step: 0.0001
+    distribution: uniform
+
+  gamma_reg:
+    min: 0.01
+    max: 1e4
+    num: 10
+    distribution: loguniform
+
+
+# Test fbopt with different hyperparameter configurations
+
+irm_erm:
+  model: erm
+  trainer: irm
+  shared:
+    - gamma_reg

From cbdc5055f53dfa275a7fa9260b4222efb7c24944 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sun, 6 Oct 2024 18:19:58 +0200
Subject: [PATCH 223/273] Update aistat_irm_erm_mhof.yaml

---
 examples/benchmark/aistat_irm_erm_mhof.yaml | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/examples/benchmark/aistat_irm_erm_mhof.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
index 2c435f2da..092c04682 100644
--- a/examples/benchmark/aistat_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof.yaml
@@ -35,17 +35,16 @@ Shared params:
     step: 0.05
     distribution: uniform
 
-  k_i_gain:
-    min: 0.0001
-    max: 0.01
-    num: 2
-    step: 0.0001
+ k_i_gain_ratio:
+    min: 0.1
+    max: 1
+    num: 3
     distribution: uniform
 
   gamma_reg:
     min: 0.01
     max: 1e4
-    num: 3
+    num: 4
     distribution: loguniform
 
 
@@ -56,6 +55,7 @@ fbopt_irm_erm:
   trainer: fbopt_irm
   shared:
     - ini_setpoint_ratio
+    - k_i_gain_ratio
 
 irm_erm:
   model: erm

From 144efba65bbbf052a028c386cd930e9a717d2076 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sun, 6 Oct 2024 18:21:41 +0200
Subject: [PATCH 224/273] Update aistat_irm_erm_mhof.yaml, fix grammar error

---
 examples/benchmark/aistat_irm_erm_mhof.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/benchmark/aistat_irm_erm_mhof.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
index 092c04682..be8a3c480 100644
--- a/examples/benchmark/aistat_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof.yaml
@@ -35,7 +35,7 @@ Shared params:
     step: 0.05
     distribution: uniform
 
- k_i_gain_ratio:
+  k_i_gain_ratio:
     min: 0.1
     max: 1
     num: 3

From 68c1e3612c5d5671680a7b0a2722cb1a11234df8 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sun, 6 Oct 2024 18:31:11 +0200
Subject: [PATCH 225/273] Update sh_link_pacs_dataset.sh

---
 scripts/sh_link_pacs_dataset.sh | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/scripts/sh_link_pacs_dataset.sh b/scripts/sh_link_pacs_dataset.sh
index f973db02b..60823522b 100644
--- a/scripts/sh_link_pacs_dataset.sh
+++ b/scripts/sh_link_pacs_dataset.sh
@@ -1,2 +1,5 @@
 mkdir -p domainlab/zdata/pacs
 ln -s ~/Documents/datasets/pacs/raw domainlab/zdata/pacs/PACS
+
+mkdir -p data/pacs
+ln -s ~/Documents/datasets/pacs/raw data/pacs/PACS

From 3a051fe177c845e7ac58a84211456d8bca7c40d4 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Sun, 6 Oct 2024 18:35:21 +0200
Subject: [PATCH 226/273] Update .gitignore,  display slurm_errors,

---
 .gitignore | 2 --
 1 file changed, 2 deletions(-)

diff --git a/.gitignore b/.gitignore
index a351b31fe..b001bad9e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -6,8 +6,6 @@ tests/__pycache__/
 .vscode/
 domainlab/zdata/pacs
 /data/
-/.snakemake/
 /dist 
 /domainlab.egg-info
 /runs
-/slurm_errors.txt
\ No newline at end of file

From fe84b5b05f5b47a64f20bbbfd52e4f7a91c355c3 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Tue, 8 Oct 2024 11:52:02 +0200
Subject: [PATCH 227/273] Update and rename sh_list_job_via_slurm_id.sh to
 sh_list_job_via_run_experiment_folder1_slurm_id2.sh

---
 sh_list_job_via_run_experiment_folder1_slurm_id2.sh | 2 ++
 sh_list_job_via_slurm_id.sh                         | 1 -
 2 files changed, 2 insertions(+), 1 deletion(-)
 create mode 100644 sh_list_job_via_run_experiment_folder1_slurm_id2.sh
 delete mode 100644 sh_list_job_via_slurm_id.sh

diff --git a/sh_list_job_via_run_experiment_folder1_slurm_id2.sh b/sh_list_job_via_run_experiment_folder1_slurm_id2.sh
new file mode 100644
index 000000000..5eeb6493b
--- /dev/null
+++ b/sh_list_job_via_run_experiment_folder1_slurm_id2.sh
@@ -0,0 +1,2 @@
+# find zoutput/benchmarks/xxx/slurm_logs/run_experiment/ | grep -i "$1"
+find $1 | grep -i "$2"
diff --git a/sh_list_job_via_slurm_id.sh b/sh_list_job_via_slurm_id.sh
deleted file mode 100644
index d8e2272ce..000000000
--- a/sh_list_job_via_slurm_id.sh
+++ /dev/null
@@ -1 +0,0 @@
-find zoutput/slurm_logs/run_experiment/ | grep -i "$1"

From 1be163493d45bb41dacc2b335ca317033ee788b8 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 8 Oct 2024 12:52:59 +0200
Subject: [PATCH 228/273] causalirl yaml

---
 examples/benchmark/aistat_irl_erm_mhof.yaml | 64 +++++++++++++++++++++
 1 file changed, 64 insertions(+)
 create mode 100644 examples/benchmark/aistat_irl_erm_mhof.yaml

diff --git a/examples/benchmark/aistat_irl_erm_mhof.yaml b/examples/benchmark/aistat_irl_erm_mhof.yaml
new file mode 100644
index 000000000..12b678e2a
--- /dev/null
+++ b/examples/benchmark/aistat_irl_erm_mhof.yaml
@@ -0,0 +1,64 @@
+mode: grid
+
+output_dir: zoutput/benchmarks/benchmark_fbopt_fishr_erm_pacs
+
+sampling_seed: 0
+startseed: 0
+endseed: 2
+
+test_domains:
+  - sketch
+
+domainlab_args:
+  tpath: examples/tasks/task_pacs_aug.py
+  dmem: False
+  lr: 5e-5
+  epos: 500
+  epos_min: 200
+  es: 5
+  bs: 32
+  san_check: False
+  npath: examples/nets/resnet50domainbed.py
+  npath_dom: examples/nets/resnet50domainbed.py
+  zx_dim: 0
+  zy_dim: 64
+  zd_dim: 64
+
+
+
+
+Shared params:
+  ini_setpoint_ratio:
+    min: 0.5
+    max: 0.99
+    num: 2
+    step: 0.05
+    distribution: uniform
+
+  k_i_gain_ratio:
+    min: 0.1
+    max: 1
+    num: 3
+    distribution: uniform
+
+  gamma_reg:
+    min: 0.01
+    max: 1e4
+    num: 4
+    distribution: loguniform
+
+
+# Test fbopt with different hyperparameter configurations
+
+fbopt_irm_erm:
+  model: erm
+  trainer: fbopt_causalirl
+  shared:
+    - ini_setpoint_ratio
+    - k_i_gain_ratio
+
+irm_erm:
+  model: erm
+  trainer: causalirl
+  shared:
+    - gamma_reg

From 121ca555db03d5cff238765fd0d6ba331debcd29 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 8 Oct 2024 12:53:25 +0200
Subject: [PATCH 229/273] .

---
 examples/benchmark/aistat_irl_erm_mhof.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/benchmark/aistat_irl_erm_mhof.yaml b/examples/benchmark/aistat_irl_erm_mhof.yaml
index 12b678e2a..9d13e0cf3 100644
--- a/examples/benchmark/aistat_irl_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irl_erm_mhof.yaml
@@ -1,6 +1,6 @@
 mode: grid
 
-output_dir: zoutput/benchmarks/benchmark_fbopt_fishr_erm_pacs
+output_dir: zoutput/benchmarks/benchmark_mhof_causal_irl_erm_pacs
 
 sampling_seed: 0
 startseed: 0

From 6626475c39bad4b2851e13674a0aa24bbae2bc5a Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 8 Oct 2024 16:50:56 +0200
Subject: [PATCH 230/273] use self.decoratee instead of self.model

---
 domainlab/algos/trainers/a_trainer.py           |  1 +
 domainlab/algos/trainers/fbopt_mu_controller.py | 12 +++++++++---
 domainlab/algos/trainers/train_fbopt_b.py       |  3 ++-
 tests/test_fbopt_irm.py                         | 14 ++++++++++++++
 4 files changed, 26 insertions(+), 4 deletions(-)
 create mode 100644 tests/test_fbopt_irm.py

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 871abd8f0..890d5aea0 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -53,6 +53,7 @@ def __init__(self, successor_node=None, extend=None):
         """
         super().__init__(successor_node)
         self._model = None
+        # decoratee can be both model or trainer
         self._decoratee = extend
         self.task = None
         self.observer = None
diff --git a/domainlab/algos/trainers/fbopt_mu_controller.py b/domainlab/algos/trainers/fbopt_mu_controller.py
index f61b4bc63..5c635e147 100644
--- a/domainlab/algos/trainers/fbopt_mu_controller.py
+++ b/domainlab/algos/trainers/fbopt_mu_controller.py
@@ -52,7 +52,7 @@ def __init__(self, trainer, **kwargs):
 
         self.k_i_control = [trainer.aconf.k_i_gain for i in
                             range(len(self.mmu))]
-        self.k_i_gain_ratio = None
+        self.k_i_gain_ratio = trainer.aconf.k_i_gain_ratio
         self.overshoot_rewind = trainer.aconf.overshoot_rewind == "yes"
         self.delta_epsilon_r = None
 
@@ -71,7 +71,10 @@ def __init__(self, trainer, **kwargs):
 
     def set_k_i_gain(self, epo_reg_loss):
         if self.k_i_gain_ratio is None:
-            return
+            if self.k_i_control:
+                return
+            raise RuntimeError("set either direct k_i_control value or \
+                               set k_i_gain_ratio, can not be both empty!")
         # NOTE: do not use self.cal_delta4control!!!! which will change
         # class member variables self.delta_epsilon_r!
         list_setpoint = self.get_setpoint4r()
@@ -79,9 +82,12 @@ def set_k_i_gain(self, epo_reg_loss):
         delta_epsilon_r = [a - b for a, b in zip(epo_reg_loss, list_setpoint)]
 
         # to calculate self.delta_epsilon_r
+        list_active = [self.activation_clip for i in range(len(delta_epsilon_r))]
+
         k_i_gain_saturate = [
-            a / b for a, b in zip(self.activation_clip, delta_epsilon_r)
+            a / b for a, b in zip(list_active, delta_epsilon_r)
         ]
+
         k_i_gain_saturate_min = min(k_i_gain_saturate)
         # NOTE: here we override the commandline arguments specification
         # for k_i_control, so k_i_control is not a hyperparameter anymore
diff --git a/domainlab/algos/trainers/train_fbopt_b.py b/domainlab/algos/trainers/train_fbopt_b.py
index 1efe3ce58..e922a7521 100644
--- a/domainlab/algos/trainers/train_fbopt_b.py
+++ b/domainlab/algos/trainers/train_fbopt_b.py
@@ -66,7 +66,7 @@ def eval_r_loss(self):
                     vec_y.to(self.device),
                     vec_d.to(self.device),
                 )
-                tuple_reg_loss = self.model.cal_reg_loss(tensor_x, vec_y, vec_d, others)
+                tuple_reg_loss = self.decoratee.cal_reg_loss(tensor_x, vec_y, vec_d, others)
                 p_loss, *_ = self.model.cal_loss(tensor_x, vec_y, vec_d, others)
                 # NOTE: first [0] extract the loss, second [0] get the list
                 list_b_reg_loss = tuple_reg_loss[0]
@@ -127,6 +127,7 @@ def before_tr(self):
             ],
             self.epo_task_loss_tr,
         )  # setpoing w.r.t. random initialization of neural network
+        # FIXME: check if self.epo_reg_loss_tr is zero!!
         self.hyper_scheduler.set_k_i_gain(self.epo_reg_loss_tr)
 
     @property
diff --git a/tests/test_fbopt_irm.py b/tests/test_fbopt_irm.py
new file mode 100644
index 000000000..fb1f109f6
--- /dev/null
+++ b/tests/test_fbopt_irm.py
@@ -0,0 +1,14 @@
+"""
+ end-end test
+"""
+from tests.utils_test import utils_test_algo
+
+
+def test_mhof_irm():
+    """
+    mhof-irm
+    """
+    args = "--te_d=0 --task=mnistcolor10 --model=erm \
+        --trainer=fbopt_irm --nname=conv_bn_pool_2 \
+        --k_i_gain_ratio=0.5"
+    utils_test_algo(args)

From d5d3a0b982d9d32b6a22a58c425af1e7a7f06e8f Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 8 Oct 2024 16:52:39 +0200
Subject: [PATCH 231/273] cmd script to test mhof irm

---
 a_test_mhof_irm.sh | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 a_test_mhof_irm.sh

diff --git a/a_test_mhof_irm.sh b/a_test_mhof_irm.sh
new file mode 100644
index 000000000..610d3a606
--- /dev/null
+++ b/a_test_mhof_irm.sh
@@ -0,0 +1 @@
+python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=fbopt_irm --nname=conv_bn_pool_2 --k_i_gain_ratio=0.5

From e6c368bf13cee9c31fa542ba286e74905e163a5d Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 8 Oct 2024 16:55:07 +0200
Subject: [PATCH 232/273] script to test mhof_irm

---
 a_test_mhof_irm.sh | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 a_test_mhof_irm.sh

diff --git a/a_test_mhof_irm.sh b/a_test_mhof_irm.sh
new file mode 100644
index 000000000..610d3a606
--- /dev/null
+++ b/a_test_mhof_irm.sh
@@ -0,0 +1 @@
+python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=fbopt_irm --nname=conv_bn_pool_2 --k_i_gain_ratio=0.5

From 6701cbf3a8108a309bc655de9bb31a85b55dec79 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 9 Oct 2024 11:36:17 +0200
Subject: [PATCH 233/273] enable grad for irm inside torch.no_grad for mhof

---
 domainlab/algos/trainers/train_irm.py | 19 ++++++++++---------
 1 file changed, 10 insertions(+), 9 deletions(-)

diff --git a/domainlab/algos/trainers/train_irm.py b/domainlab/algos/trainers/train_irm.py
index 45797bf00..a2753989e 100644
--- a/domainlab/algos/trainers/train_irm.py
+++ b/domainlab/algos/trainers/train_irm.py
@@ -60,12 +60,13 @@ def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         _ = tensor_d
         _ = others
         y = tensor_y
-        phi = self._cal_phi(tensor_x)
-        dummy_w_scale = torch.tensor(1.).to(tensor_x.device).requires_grad_()
-        loss_1 = F.cross_entropy(phi[::2] * dummy_w_scale, y[::2])
-        loss_2 = F.cross_entropy(phi[1::2] * dummy_w_scale, y[1::2])
-        grad_1 = autograd.grad(loss_1, [dummy_w_scale], create_graph=True)[0]
-        grad_2 = autograd.grad(loss_2, [dummy_w_scale], create_graph=True)[0]
-        loss_irm_scalar = torch.sum(grad_1 * grad_2)  # scalar
-        loss_irm_tensor = loss_irm_scalar.expand(tensor_x.shape[0])
-        return [loss_irm_tensor], [self.aconf.gamma_reg]
+        with torch.enable_grad():
+            phi = self._cal_phi(tensor_x)
+            dummy_w_scale = torch.tensor(1.).to(tensor_x.device).requires_grad_()
+            loss_1 = F.cross_entropy(phi[::2] * dummy_w_scale, y[::2])
+            loss_2 = F.cross_entropy(phi[1::2] * dummy_w_scale, y[1::2])
+            grad_1 = autograd.grad(loss_1, [dummy_w_scale], create_graph=True)[0]
+            grad_2 = autograd.grad(loss_2, [dummy_w_scale], create_graph=True)[0]
+            loss_irm_scalar = torch.sum(grad_1 * grad_2)  # scalar
+            loss_irm_tensor = loss_irm_scalar.expand(tensor_x.shape[0])
+            return [loss_irm_tensor], [self.aconf.gamma_reg]

From 888d7143e92dc190ca123be1f79d54fba98cdfcd Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 9 Oct 2024 12:24:25 +0200
Subject: [PATCH 234/273] filter out zero reg loss in abstract trainer

---
 domainlab/algos/trainers/a_trainer.py | 4 ++++
 domainlab/algos/trainers/train_irm.py | 2 +-
 domainlab/models/a_model_classif.py   | 1 +
 3 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 890d5aea0..35a5b0fe2 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -298,6 +298,10 @@ def cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         list_loss_tensor = list_reg_loss_model_tensor + \
             list_reg_loss_trainer_tensor
         list_mu = list_mu_model + list_mu_trainer
+        # ERM return a tensor of all zeros, delete here
+        list_boolean_zero = [torch.all(torch.eq(list_loss_tensor[i], 0)).item() for i in range(len(list_mu))]
+        list_loss_tensor = [list_loss_tensor[i] for (i, flag) in enumerate(list_boolean_zero) if not flag]
+        list_mu = [list_mu[i] for (i, flag) in enumerate(list_boolean_zero) if not flag]
         return list_loss_tensor, list_mu
 
     def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
diff --git a/domainlab/algos/trainers/train_irm.py b/domainlab/algos/trainers/train_irm.py
index a2753989e..377759a2f 100644
--- a/domainlab/algos/trainers/train_irm.py
+++ b/domainlab/algos/trainers/train_irm.py
@@ -37,7 +37,7 @@ def tr_epoch(self, epoch, flag_info=False):
                 list_domain_loss_erm.append(
                     self.model.cal_task_loss(tensor_x, tensor_y))
                 list_1ele_loss_irm, _ = \
-                    self._cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
+                    self.cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
                 list_domain_reg += list_1ele_loss_irm
             loss = torch.sum(torch.stack(list_domain_loss_erm)) + \
                 self.aconf.gamma_reg * torch.sum(torch.stack(list_domain_reg))
diff --git a/domainlab/models/a_model_classif.py b/domainlab/models/a_model_classif.py
index 1f72eec0a..ea9ef5f47 100644
--- a/domainlab/models/a_model_classif.py
+++ b/domainlab/models/a_model_classif.py
@@ -243,3 +243,4 @@ def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         device = tensor_x.device
         bsize = tensor_x.shape[0]
         return [torch.zeros(bsize).to(device)], [0.0]
+        # return [], []

From 64bcc9cdd2021eea749e8685af69d2fac384b96b Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 9 Oct 2024 14:45:26 +0200
Subject: [PATCH 235/273] trainer behaves like model, now decoratte's cal_loss
 has to be changed

---
 domainlab/algos/trainers/a_trainer.py     | 34 +++++++++++++++++++++--
 domainlab/algos/trainers/train_basic.py   |  5 ++--
 domainlab/algos/trainers/train_dial.py    |  8 ------
 domainlab/algos/trainers/train_fbopt_b.py | 21 ++++++++------
 4 files changed, 47 insertions(+), 21 deletions(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 35a5b0fe2..35e3f5f21 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -97,6 +97,8 @@ def __init__(self, successor_node=None, extend=None):
         self._ma_iter = 0
         #
         self.list_reg_over_task_ratio = None
+        # mhof
+        self.dict_multiplier = {}
 
 
     @property
@@ -200,11 +202,18 @@ def before_tr(self):
         """
         before training, probe model performance
         """
-        self.cal_reg_loss_over_task_loss_ratio()
+        list_mu = self.cal_reg_loss_over_task_loss_ratio()
+        self.dict_multiplier = {'mu4regloss'+str(i): value for i, value in enumerate(list_mu)}
+
+    @property
+    def list_str_multiplier_na(self):
+        list_str = list(self.dict_multiplier.keys())
+        return list_str
 
     def cal_reg_loss_over_task_loss_ratio(self):
         list_accum_reg_loss = []
         loss_task_agg = 0
+        list_mu = None
         for ind_batch, (tensor_x, tensor_y, tensor_d, *others) in enumerate(
             self.loader_tr
         ):
@@ -215,7 +224,7 @@ def cal_reg_loss_over_task_loss_ratio(self):
                 tensor_y.to(self.device),
                 tensor_d.to(self.device),
             )
-            list_reg_loss_tensor, _ = \
+            list_reg_loss_tensor, list_mu = \
                 self.cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
             list_reg_loss_tensor = [torch.sum(tensor).detach().item()
                                     for tensor in list_reg_loss_tensor]
@@ -232,6 +241,7 @@ def cal_reg_loss_over_task_loss_ratio(self):
             loss_task_agg += tensor_loss_task
         self.list_reg_over_task_ratio = [reg_loss / loss_task_agg
                                          for reg_loss in list_accum_reg_loss]
+        return list_mu
 
     def post_tr(self):
         """
@@ -327,3 +337,23 @@ def print_parameters(self):
         """
         params = vars(self)
         print(f"Parameters of {type(self).__name__}: {params}")
+
+    def hyper_init(self, functor_scheduler, trainer):
+        """
+        initialize both trainer's multiplier and model's multiplier
+        """
+        if not self.dict_multiplier:
+            raise RuntimeError("self.dict_multiplier empty!")
+        return functor_scheduler(
+            trainer=trainer, **self.dict_multiplier
+        )
+
+    def hyper_update(self, epoch, fun_scheduler):
+        """hyper_update.
+
+        :param epoch:
+        :param fun_scheduler:
+        """
+        dict_rst = fun_scheduler(epoch)
+        for key in self.dict_multiplier:
+            self.dict_multiplier[key] = dict_rst[key]
diff --git a/domainlab/algos/trainers/train_basic.py b/domainlab/algos/trainers/train_basic.py
index 100c274b4..d06952005 100644
--- a/domainlab/algos/trainers/train_basic.py
+++ b/domainlab/algos/trainers/train_basic.py
@@ -23,6 +23,7 @@ def before_tr(self):
         """
         self.model.evaluate(self.loader_te, self.device)
         super().before_tr()
+        self.before_epoch()
 
     def before_epoch(self):
         """
@@ -94,7 +95,6 @@ def cal_loss(self, tensor_x, tensor_y, tensor_d, others):
         list_reg_tr_batch, list_mu_tr = self.cal_reg_loss(
             tensor_x, tensor_y, tensor_d, others
         )
-
         list_mu_tr_normalized = list_mu_tr
         if self.list_reg_over_task_ratio:
             assert len(list_mu_tr) == len(self.list_reg_over_task_ratio)
@@ -105,6 +105,7 @@ def cal_loss(self, tensor_x, tensor_y, tensor_d, others):
         tensor_batch_reg_loss_penalized = self.model.list_inner_product(
             list_reg_tr_batch, list_mu_tr_normalized
         )
+
         assert len(tensor_batch_reg_loss_penalized.shape) == 1
         loss_erm_agg = g_tensor_batch_agg(loss_task)
         loss_reg_penalized_agg = g_tensor_batch_agg(tensor_batch_reg_loss_penalized)
@@ -112,4 +113,4 @@ def cal_loss(self, tensor_x, tensor_y, tensor_d, others):
             self.model.multiplier4task_loss * loss_erm_agg + loss_reg_penalized_agg
         )
         self.log_loss(list_reg_tr_batch, loss_task, loss_penalized)
-        return loss_penalized
+        return loss_penalized, list_reg_tr_batch, loss_erm_agg
diff --git a/domainlab/algos/trainers/train_dial.py b/domainlab/algos/trainers/train_dial.py
index dbcb50eae..4fe700f45 100644
--- a/domainlab/algos/trainers/train_dial.py
+++ b/domainlab/algos/trainers/train_dial.py
@@ -51,11 +51,3 @@ def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         tensor_x_batch_adv_no_grad = Variable(tensor_x_adv, requires_grad=False)
         loss_dial = self.model.cal_task_loss(tensor_x_batch_adv_no_grad, tensor_y)
         return [loss_dial], [get_gamma_reg(self.aconf, self.name)]
-
-    def hyper_init(self, functor_scheduler, trainer):
-        """
-        initialize both trainer's multiplier and model's multiplier
-        """
-        fun_scheduler = super().hyper_init(functor_scheduler, trainer)
-        return fun_scheduler
-        # FIXME: register also the trainer hyperpars: return functor_scheduler(trainer=trainer, gamma_reg=self.gamma_reg)
diff --git a/domainlab/algos/trainers/train_fbopt_b.py b/domainlab/algos/trainers/train_fbopt_b.py
index e922a7521..43a5bf619 100644
--- a/domainlab/algos/trainers/train_fbopt_b.py
+++ b/domainlab/algos/trainers/train_fbopt_b.py
@@ -43,7 +43,7 @@ def set_scheduler(self, scheduler):
             this class name will be created inside model
         """
         # model.hyper_init will register the hyper-parameters of the model to scheduler
-        self.hyper_scheduler = self.model.hyper_init(scheduler, trainer=self)
+        self.hyper_scheduler = self.decoratee.hyper_init(scheduler, trainer=self)
 
     def eval_r_loss(self):
         """
@@ -67,7 +67,9 @@ def eval_r_loss(self):
                     vec_d.to(self.device),
                 )
                 tuple_reg_loss = self.decoratee.cal_reg_loss(tensor_x, vec_y, vec_d, others)
-                p_loss, *_ = self.model.cal_loss(tensor_x, vec_y, vec_d, others)
+                p_loss, *_ = self.decoratee.cal_loss(tensor_x, vec_y, vec_d, others)
+                if p_loss.dim() > 0:
+                    p_loss = p_loss.sum()
                 # NOTE: first [0] extract the loss, second [0] get the list
                 list_b_reg_loss = tuple_reg_loss[0]
                 list_b_reg_loss_sumed = [
@@ -82,7 +84,7 @@ def eval_r_loss(self):
                 )
                 # sum will kill the dimension of the mini batch
                 epo_task_loss += b_task_loss
-                epo_p_loss += p_loss.sum().detach().item()
+                epo_p_loss += p_loss.detach().item()
                 counter += 1.0
         return (
             list_divide(epo_reg_loss, counter),
@@ -103,6 +105,8 @@ def before_batch(self, epoch, ind_batch):
         return super().after_batch(epoch, ind_batch)
 
     def before_tr(self):
+        if hasattr(self.decoratee, "before_tr"):
+            self.decoratee.before_tr()
         self.flag_setpoint_updated = False
         if self.aconf.force_feedforward:
             self.set_scheduler(scheduler=HyperSchedulerWarmupLinear)
@@ -126,8 +130,7 @@ def before_tr(self):
                 for ele in self.epo_reg_loss_tr
             ],
             self.epo_task_loss_tr,
-        )  # setpoing w.r.t. random initialization of neural network
-        # FIXME: check if self.epo_reg_loss_tr is zero!!
+        )  # setpoint w.r.t. random initialization of neural network
         self.hyper_scheduler.set_k_i_gain(self.epo_reg_loss_tr)
 
     @property
@@ -135,7 +138,7 @@ def list_str_multiplier_na(self):
         """
         return the name of multipliers
         """
-        return self.model.list_str_multiplier_na
+        return self.decoratee.list_str_multiplier_na
 
     def tr_with_init_mu(self):
         """
@@ -147,7 +150,7 @@ def set_model_with_mu(self):
         """
         set model multipliers
         """
-        self.model.hyper_update(
+        self.decoratee.hyper_update(
             epoch=None, fun_scheduler=HyperSetter(self.hyper_scheduler.mmu)
         )
 
@@ -163,9 +166,9 @@ def tr_epoch(self, epoch, flag_info=False):
             miter=epoch,
         )
         self.set_model_with_mu()
-        if hasattr(self.model, "dict_multiplier"):
+        if hasattr(self.decoratee, "dict_multiplier"):
             logger = Logger.get_logger()
-            logger.info(f"current multiplier: {self.model.dict_multiplier}")
+            logger.info(f"current multiplier: {self.decoratee.dict_multiplier}")
 
         if self._decoratee is not None:
             flag = self._decoratee.tr_epoch(epoch, self.flag_setpoint_updated)

From 22f343cac977767ac1ef9165eb22fe284f71ae24 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 9 Oct 2024 15:29:46 +0200
Subject: [PATCH 236/273] overwrite multiplier from scheduler(default static
 scheduler then no change) in cal_reg_loss

---
 domainlab/algos/trainers/a_trainer.py   |  2 ++
 domainlab/algos/trainers/train_basic.py |  2 +-
 domainlab/algos/trainers/train_irm.py   | 30 -------------------------
 domainlab/algos/trainers/zoo_trainer.py |  2 ++
 4 files changed, 5 insertions(+), 31 deletions(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 35e3f5f21..d53bac29f 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -312,6 +312,8 @@ def cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         list_boolean_zero = [torch.all(torch.eq(list_loss_tensor[i], 0)).item() for i in range(len(list_mu))]
         list_loss_tensor = [list_loss_tensor[i] for (i, flag) in enumerate(list_boolean_zero) if not flag]
         list_mu = [list_mu[i] for (i, flag) in enumerate(list_boolean_zero) if not flag]
+        if self.dict_multiplier:
+            list_mu = list(self.dict_multiplier.values())
         return list_loss_tensor, list_mu
 
     def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
diff --git a/domainlab/algos/trainers/train_basic.py b/domainlab/algos/trainers/train_basic.py
index d06952005..0e7faf8e4 100644
--- a/domainlab/algos/trainers/train_basic.py
+++ b/domainlab/algos/trainers/train_basic.py
@@ -80,7 +80,7 @@ def tr_batch(self, tensor_x, tensor_y, tensor_d, others, ind_batch, epoch):
             tensor_d.to(self.device),
         )
         self.optimizer.zero_grad()
-        loss = self.cal_loss(tensor_x, tensor_y, tensor_d, others)
+        loss, *_ = self.cal_loss(tensor_x, tensor_y, tensor_d, others)
         loss.backward()
         self.optimizer.step()
         self.after_batch(epoch, ind_batch)
diff --git a/domainlab/algos/trainers/train_irm.py b/domainlab/algos/trainers/train_irm.py
index 377759a2f..aaa9f2dd0 100644
--- a/domainlab/algos/trainers/train_irm.py
+++ b/domainlab/algos/trainers/train_irm.py
@@ -19,36 +19,6 @@ class TrainerIRM(TrainerBasic):
     For more details, see section 3.2 and Appendix D of :
     Arjovsky et al., “Invariant Risk Minimization.”
     """
-    def tr_epoch(self, epoch, flag_info=False):
-        list_loaders = list(self.dict_loader_tr.values())
-        loaders_zip = zip(*list_loaders)
-        self.model.train()
-        self.epo_loss_tr = 0
-
-        for ind_batch, tuple_data_domains_batch in enumerate(loaders_zip):
-            self.optimizer.zero_grad()
-            list_domain_loss_erm = []
-            list_domain_reg = []
-            for batch_domain_e in tuple_data_domains_batch:
-                tensor_x, tensor_y, tensor_d, *others = batch_domain_e
-                tensor_x, tensor_y, tensor_d = \
-                    tensor_x.to(self.device), tensor_y.to(self.device), \
-                    tensor_d.to(self.device)
-                list_domain_loss_erm.append(
-                    self.model.cal_task_loss(tensor_x, tensor_y))
-                list_1ele_loss_irm, _ = \
-                    self.cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
-                list_domain_reg += list_1ele_loss_irm
-            loss = torch.sum(torch.stack(list_domain_loss_erm)) + \
-                self.aconf.gamma_reg * torch.sum(torch.stack(list_domain_reg))
-            loss.backward()
-            self.optimizer.step()
-            self.epo_loss_tr += loss.detach().item()
-            self.after_batch(epoch, ind_batch)
-
-        flag_stop = self.observer.update(epoch, flag_info)  # notify observer
-        return flag_stop
-
     def _cal_phi(self, tensor_x):
         logits = self.model.cal_logit_y(tensor_x)
         return logits
diff --git a/domainlab/algos/trainers/zoo_trainer.py b/domainlab/algos/trainers/zoo_trainer.py
index 93b40acfe..dcf1785dc 100644
--- a/domainlab/algos/trainers/zoo_trainer.py
+++ b/domainlab/algos/trainers/zoo_trainer.py
@@ -11,6 +11,7 @@
 from domainlab.algos.trainers.train_mldg import TrainerMLDG
 from domainlab.algos.trainers.train_fishr import TrainerFishr
 from domainlab.algos.trainers.train_irm import TrainerIRM
+from domainlab.algos.trainers.train_irm_sep_dom import TrainerIRMSepDom
 from domainlab.algos.trainers.train_causIRL import TrainerCausalIRL
 from domainlab.algos.trainers.train_coral import TrainerCoral
 
@@ -57,6 +58,7 @@ def __call__(self, lst_candidates=None, default=None, lst_excludes=None):
         chain = TrainerMLDG(chain)
         chain = TrainerFishr(chain)
         chain = TrainerIRM(chain)
+        chain = TrainerIRMSepDom(chain)
         chain = TrainerHyperScheduler(chain)
         chain = TrainerFbOpt(chain)
         chain = TrainerCausalIRL(chain)

From 23607fb430e166fdada5e8b931e66be2117ab63a Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 9 Oct 2024 15:30:13 +0200
Subject: [PATCH 237/273] per domain irm to separate file

---
 domainlab/algos/trainers/train_irm_sep_dom.py | 39 +++++++++++++++++++
 1 file changed, 39 insertions(+)
 create mode 100644 domainlab/algos/trainers/train_irm_sep_dom.py

diff --git a/domainlab/algos/trainers/train_irm_sep_dom.py b/domainlab/algos/trainers/train_irm_sep_dom.py
new file mode 100644
index 000000000..94d3bca79
--- /dev/null
+++ b/domainlab/algos/trainers/train_irm_sep_dom.py
@@ -0,0 +1,39 @@
+"""
+use random start to generate adversarial images
+"""
+import torch
+from torch import autograd
+from torch.nn import functional as F
+from domainlab.algos.trainers.train_irm import TrainerIRM
+
+
+class TrainerIRMSepDom(TrainerIRM):
+    def tr_epoch(self, epoch, flag_info=False):
+        list_loaders = list(self.dict_loader_tr.values())
+        loaders_zip = zip(*list_loaders)
+        self.model.train()
+        self.epo_loss_tr = 0
+
+        for ind_batch, tuple_data_domains_batch in enumerate(loaders_zip):
+            self.optimizer.zero_grad()
+            list_domain_loss_erm = []
+            list_domain_reg = []
+            for batch_domain_e in tuple_data_domains_batch:
+                tensor_x, tensor_y, tensor_d, *others = batch_domain_e
+                tensor_x, tensor_y, tensor_d = \
+                    tensor_x.to(self.device), tensor_y.to(self.device), \
+                    tensor_d.to(self.device)
+                list_domain_loss_erm.append(
+                    self.model.cal_task_loss(tensor_x, tensor_y))
+                list_1ele_loss_irm, _ = \
+                    self.cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
+                list_domain_reg += list_1ele_loss_irm
+            loss = torch.sum(torch.stack(list_domain_loss_erm)) + \
+                self.aconf.gamma_reg * torch.sum(torch.stack(list_domain_reg))
+            loss.backward()
+            self.optimizer.step()
+            self.epo_loss_tr += loss.detach().item()
+            self.after_batch(epoch, ind_batch)
+
+        flag_stop = self.observer.update(epoch, flag_info)  # notify observer
+        return flag_stop

From 63ad47b89bd771ffc8f98ecb7001fdff3964ecc3 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 9 Oct 2024 18:13:38 +0200
Subject: [PATCH 238/273] dial mhof yaml

---
 examples/benchmark/aistat_dial_erm_mhof.yaml | 64 ++++++++++++++++++++
 1 file changed, 64 insertions(+)
 create mode 100644 examples/benchmark/aistat_dial_erm_mhof.yaml

diff --git a/examples/benchmark/aistat_dial_erm_mhof.yaml b/examples/benchmark/aistat_dial_erm_mhof.yaml
new file mode 100644
index 000000000..50e801766
--- /dev/null
+++ b/examples/benchmark/aistat_dial_erm_mhof.yaml
@@ -0,0 +1,64 @@
+mode: grid
+
+output_dir: zoutput/benchmarks/benchmark_mhof_dial
+
+sampling_seed: 0
+startseed: 0
+endseed: 2
+
+test_domains:
+  - sketch
+
+domainlab_args:
+  tpath: examples/tasks/task_pacs_aug.py
+  dmem: False
+  lr: 5e-5
+  epos: 500
+  epos_min: 200
+  es: 5
+  bs: 32
+  san_check: False
+  npath: examples/nets/resnet50domainbed.py
+  npath_dom: examples/nets/resnet50domainbed.py
+  zx_dim: 0
+  zy_dim: 64
+  zd_dim: 64
+
+
+
+
+Shared params:
+  ini_setpoint_ratio:
+    min: 0.5
+    max: 0.99
+    num: 2
+    step: 0.05
+    distribution: uniform
+
+  k_i_gain_ratio:
+    min: 0.1
+    max: 1
+    num: 3
+    distribution: uniform
+
+  gamma_reg:
+    min: 0.01
+    max: 1e4
+    num: 4
+    distribution: loguniform
+
+
+# Test fbopt with different hyperparameter configurations
+
+fbopt_dial_erm:
+  model: erm
+  trainer: fbopt_dial
+  shared:
+    - ini_setpoint_ratio
+    - k_i_gain_ratio
+
+dial_erm:
+  model: erm
+  trainer: dial
+  shared:
+    - gamma_reg

From 8ba7e110430938e35e572d8a79106d0196c91e59 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Wed, 9 Oct 2024 18:34:39 +0200
Subject: [PATCH 239/273] number of bathces to estimate ratio

---
 examples/benchmark/aistat_irm_erm_mhof.yaml | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/examples/benchmark/aistat_irm_erm_mhof.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
index be8a3c480..eceef6919 100644
--- a/examples/benchmark/aistat_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof.yaml
@@ -28,6 +28,14 @@ domainlab_args:
 
 
 Shared params:
+  nb4reg_over_task_ratio:
+    distribution: categorical   # name of the distribution
+    datatype: int
+    values:                     # concrete values to choose from
+      - 0
+      - 1
+      - 100
+      
   ini_setpoint_ratio:
     min: 0.5
     max: 0.99

From 60734030a2e6af044cf2f88de908c5d9d9480267 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Wed, 9 Oct 2024 18:54:46 +0200
Subject: [PATCH 240/273] Update aistat_irm_erm_only.yaml

---
 examples/benchmark/aistat_irm_erm_only.yaml | 11 ++++++++++-
 1 file changed, 10 insertions(+), 1 deletion(-)

diff --git a/examples/benchmark/aistat_irm_erm_only.yaml b/examples/benchmark/aistat_irm_erm_only.yaml
index 299ec528c..a194c4c63 100644
--- a/examples/benchmark/aistat_irm_erm_only.yaml
+++ b/examples/benchmark/aistat_irm_erm_only.yaml
@@ -14,7 +14,7 @@ domainlab_args:
   dmem: False
   lr: 5e-5
   epos: 500
-  epos_min: 200
+  epos_min: 10
   es: 5
   bs: 32
   san_check: False
@@ -28,6 +28,14 @@ domainlab_args:
 
 
 Shared params:
+  nb4reg_over_task_ratio:
+    distribution: categorical   # name of the distribution
+    datatype: int
+    values:                     # concrete values to choose from
+      - 0
+      - 1
+      - 100
+      
   ini_setpoint_ratio:
     min: 0.5
     max: 0.99
@@ -56,3 +64,4 @@ irm_erm:
   trainer: irm
   shared:
     - gamma_reg
+    - nb4reg_over_task_ratio

From 8bd1163e8e0b246d40d495109c6e9b6cf64b08c8 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Wed, 9 Oct 2024 18:56:49 +0200
Subject: [PATCH 241/273] Update aistat_irm_erm_mhof.yaml

---
 examples/benchmark/aistat_irm_erm_mhof.yaml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/examples/benchmark/aistat_irm_erm_mhof.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
index eceef6919..dae4334b7 100644
--- a/examples/benchmark/aistat_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof.yaml
@@ -14,7 +14,7 @@ domainlab_args:
   dmem: False
   lr: 5e-5
   epos: 500
-  epos_min: 200
+  epos_min: 20
   es: 5
   bs: 32
   san_check: False
@@ -64,9 +64,11 @@ fbopt_irm_erm:
   shared:
     - ini_setpoint_ratio
     - k_i_gain_ratio
+    - nb4reg_over_task_ratio
 
 irm_erm:
   model: erm
   trainer: irm
   shared:
     - gamma_reg
+    - nb4reg_over_task_ratio

From 7667cbc902d0ef8a0c9797cae96181b32e95d7a8 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Wed, 9 Oct 2024 19:02:20 +0200
Subject: [PATCH 242/273] .

---
 examples/benchmark/aistat_irm_erm_mhof.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/benchmark/aistat_irm_erm_mhof.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
index dae4334b7..003b7a616 100644
--- a/examples/benchmark/aistat_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof.yaml
@@ -1,6 +1,6 @@
 mode: grid
 
-output_dir: zoutput/benchmarks/benchmark_fbopt_fishr_erm_pacs
+output_dir: zoutput/benchmarks/benchmark_mhof_irm_erm_pacs
 
 sampling_seed: 0
 startseed: 0

From 5eefec0189e11fad771bb6568064c1e5c3796403 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 10 Oct 2024 08:36:12 +0200
Subject: [PATCH 243/273] fix #issue 881, nb4reg_over_task_ratio is 0 cause
 error

---
 domainlab/algos/trainers/a_trainer.py | 6 +++++-
 sh_list_error.sh                      | 5 -----
 2 files changed, 5 insertions(+), 6 deletions(-)
 delete mode 100644 sh_list_error.sh

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 67120a1b6..db5c70c6a 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -194,13 +194,17 @@ def before_tr(self):
         self.cal_reg_loss_over_task_loss_ratio()
 
     def cal_reg_loss_over_task_loss_ratio(self):
+        """
+        estimate the scale of each loss term, match each loss term to the major
+        loss via a ratio, this ratio will be multiplied with multiplier
+        """
         list_accum_reg_loss = []
         loss_task_agg = 0
         for ind_batch, (tensor_x, tensor_y, tensor_d, *others) in enumerate(
             self.loader_tr
         ):
             if ind_batch >= self.aconf.nb4reg_over_task_ratio:
-                break
+                return
             tensor_x, tensor_y, tensor_d = (
                 tensor_x.to(self.device),
                 tensor_y.to(self.device),
diff --git a/sh_list_error.sh b/sh_list_error.sh
deleted file mode 100644
index 5f725e15b..000000000
--- a/sh_list_error.sh
+++ /dev/null
@@ -1,5 +0,0 @@
-# find $1 -type f -print0 | xargs -0 grep -li error
-# B means before, A means after, some erros have long stack exception message so we need at least
-# 100 lines before the error, the last line usually indicate the root cause of error
-grep -B 100 -wnr "error" --group-separator="=========begin_slurm_error===============" $1 > slurm_errors.txt
-cat slurm_errors.txt

From b64e5d0f3abcab3f0400c3cbd09eb36f8dcd5e49 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 10 Oct 2024 08:37:33 +0200
Subject: [PATCH 244/273] Update aistat_irm_erm_only.yaml

---
 examples/benchmark/aistat_irm_erm_only.yaml | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/examples/benchmark/aistat_irm_erm_only.yaml b/examples/benchmark/aistat_irm_erm_only.yaml
index a194c4c63..2a9c011e8 100644
--- a/examples/benchmark/aistat_irm_erm_only.yaml
+++ b/examples/benchmark/aistat_irm_erm_only.yaml
@@ -65,3 +65,10 @@ irm_erm:
   shared:
     - gamma_reg
     - nb4reg_over_task_ratio
+
+irm_erm_dep_dom:
+  model: erm
+  trainer: irmsepdom
+  shared:
+    - gamma_reg
+    - nb4reg_over_task_ratio

From 0033cd298e6bc2b4f07bf541479bd13fb94c09e0 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 10 Oct 2024 08:45:32 +0200
Subject: [PATCH 245/273] mv scripts from root folder to scripts folder

---
 poetry_pytest.sh => scripts/poetry_pytest.sh                      | 0
 .../sbatch4submit_slurm_cpu_10days.sh                             | 0
 .../sbatch4submit_slurm_cpu_3days.sh                              | 0
 sh_benchmark_agg.sh => scripts/sh_benchmark_agg.sh                | 0
 sh_download_pacs.sh => scripts/sh_download_pacs.sh                | 0
 .../sh_list_job_via_run_experiment_folder1_slurm_id2.sh           | 0
 slurm_status.sh => scripts/slurm_status.sh                        | 0
 .../submit_slurm_via_cpu_10days.sh                                | 0
 .../submit_slurm_via_cpu_3days.sh                                 | 0
 9 files changed, 0 insertions(+), 0 deletions(-)
 rename poetry_pytest.sh => scripts/poetry_pytest.sh (100%)
 rename sbatch4submit_slurm_cpu_10days.sh => scripts/sbatch4submit_slurm_cpu_10days.sh (100%)
 rename sbatch4submit_slurm_cpu_3days.sh => scripts/sbatch4submit_slurm_cpu_3days.sh (100%)
 rename sh_benchmark_agg.sh => scripts/sh_benchmark_agg.sh (100%)
 rename sh_download_pacs.sh => scripts/sh_download_pacs.sh (100%)
 rename sh_list_job_via_run_experiment_folder1_slurm_id2.sh => scripts/sh_list_job_via_run_experiment_folder1_slurm_id2.sh (100%)
 rename slurm_status.sh => scripts/slurm_status.sh (100%)
 rename submit_slurm_via_cpu_10days.sh => scripts/submit_slurm_via_cpu_10days.sh (100%)
 rename submit_slurm_via_cpu_3days.sh => scripts/submit_slurm_via_cpu_3days.sh (100%)

diff --git a/poetry_pytest.sh b/scripts/poetry_pytest.sh
similarity index 100%
rename from poetry_pytest.sh
rename to scripts/poetry_pytest.sh
diff --git a/sbatch4submit_slurm_cpu_10days.sh b/scripts/sbatch4submit_slurm_cpu_10days.sh
similarity index 100%
rename from sbatch4submit_slurm_cpu_10days.sh
rename to scripts/sbatch4submit_slurm_cpu_10days.sh
diff --git a/sbatch4submit_slurm_cpu_3days.sh b/scripts/sbatch4submit_slurm_cpu_3days.sh
similarity index 100%
rename from sbatch4submit_slurm_cpu_3days.sh
rename to scripts/sbatch4submit_slurm_cpu_3days.sh
diff --git a/sh_benchmark_agg.sh b/scripts/sh_benchmark_agg.sh
similarity index 100%
rename from sh_benchmark_agg.sh
rename to scripts/sh_benchmark_agg.sh
diff --git a/sh_download_pacs.sh b/scripts/sh_download_pacs.sh
similarity index 100%
rename from sh_download_pacs.sh
rename to scripts/sh_download_pacs.sh
diff --git a/sh_list_job_via_run_experiment_folder1_slurm_id2.sh b/scripts/sh_list_job_via_run_experiment_folder1_slurm_id2.sh
similarity index 100%
rename from sh_list_job_via_run_experiment_folder1_slurm_id2.sh
rename to scripts/sh_list_job_via_run_experiment_folder1_slurm_id2.sh
diff --git a/slurm_status.sh b/scripts/slurm_status.sh
similarity index 100%
rename from slurm_status.sh
rename to scripts/slurm_status.sh
diff --git a/submit_slurm_via_cpu_10days.sh b/scripts/submit_slurm_via_cpu_10days.sh
similarity index 100%
rename from submit_slurm_via_cpu_10days.sh
rename to scripts/submit_slurm_via_cpu_10days.sh
diff --git a/submit_slurm_via_cpu_3days.sh b/scripts/submit_slurm_via_cpu_3days.sh
similarity index 100%
rename from submit_slurm_via_cpu_3days.sh
rename to scripts/submit_slurm_via_cpu_3days.sh

From 80dcfe4120e4585fe0e86c0c61bb7b3b5c44a291 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 10 Oct 2024 09:06:53 +0200
Subject: [PATCH 246/273] unit test number batches for estimate loss raiot

---
 scripts/sh_list_error.sh                         |  5 +++++
 tests/test_number_batches_loss_ratio_estimate.py | 14 ++++++++++++++
 2 files changed, 19 insertions(+)
 create mode 100644 scripts/sh_list_error.sh
 create mode 100644 tests/test_number_batches_loss_ratio_estimate.py

diff --git a/scripts/sh_list_error.sh b/scripts/sh_list_error.sh
new file mode 100644
index 000000000..cd0c01bef
--- /dev/null
+++ b/scripts/sh_list_error.sh
@@ -0,0 +1,5 @@
+# find $1 -type f -print0 | xargs -0 grep -li error
+# # B means before, A means after, some erros have long stack exception message so we need at least
+# # 100 lines before the error, the last line usually indicate the root cause of error
+grep -B 100 -wnr "error" --group-separator="=========begin_slurm_error===============" $1 > slurm_errors.txt
+cat slurm_errors.txt
diff --git a/tests/test_number_batches_loss_ratio_estimate.py b/tests/test_number_batches_loss_ratio_estimate.py
new file mode 100644
index 000000000..218f51090
--- /dev/null
+++ b/tests/test_number_batches_loss_ratio_estimate.py
@@ -0,0 +1,14 @@
+"""
+loss ratio estimate
+"""
+from tests.utils_test import utils_test_algo
+
+
+def test_loss_ratio_estimate():
+    """
+    test different number of batches
+    """
+    #args = "--te_d=0 --tr_d 2 4 --task=mnistcolor10 --debug --bs=8 \
+    #    --model=erm --trainer=mldg --nname=conv_bn_pool_2"
+
+    utils_test_algo(args)

From d9eb780377eb45fe7661f8ed4f75bda765eb026d Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 10 Oct 2024 09:11:07 +0200
Subject: [PATCH 247/273] .

---
 tests/test_number_batches_loss_ratio_estimate.py | 16 +++++++++++++---
 1 file changed, 13 insertions(+), 3 deletions(-)

diff --git a/tests/test_number_batches_loss_ratio_estimate.py b/tests/test_number_batches_loss_ratio_estimate.py
index 218f51090..70d662c52 100644
--- a/tests/test_number_batches_loss_ratio_estimate.py
+++ b/tests/test_number_batches_loss_ratio_estimate.py
@@ -4,11 +4,21 @@
 from tests.utils_test import utils_test_algo
 
 
-def test_loss_ratio_estimate():
+def test_loss_ratio_estimate0():
     """
     test different number of batches
     """
-    #args = "--te_d=0 --tr_d 2 4 --task=mnistcolor10 --debug --bs=8 \
-    #    --model=erm --trainer=mldg --nname=conv_bn_pool_2"
+    args = "--te_d=0 --tr_d 2 4 --task=mnistcolor10 --debug --bs=8 \
+        --model=erm --trainer=mldg --nname=conv_bn_pool_2 \
+        --nb4reg_over_task_ratio=0"
+    utils_test_algo(args)
+
 
+def test_loss_ratio_estimate100():
+    """
+    test different number of batches
+    """
+    args = "--te_d=0 --tr_d 2 4 --task=mnistcolor10 --debug --bs=8 \
+        --model=erm --trainer=mldg --nname=conv_bn_pool_2 \
+        --nb4reg_over_task_ratio=100"
     utils_test_algo(args)

From ba68e274345e9981438d1611495aba224fd8f31b Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 10 Oct 2024 09:52:45 +0200
Subject: [PATCH 248/273] fix num_batches for loss ratio estimate

---
 domainlab/algos/trainers/a_trainer.py | 15 ++++++++++-----
 1 file changed, 10 insertions(+), 5 deletions(-)

diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index d9c4a13f5..99460afc9 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -221,8 +221,6 @@ def cal_reg_loss_over_task_loss_ratio(self):
         for ind_batch, (tensor_x, tensor_y, tensor_d, *others) in enumerate(
             self.loader_tr
         ):
-            if ind_batch >= self.aconf.nb4reg_over_task_ratio:
-                return
             tensor_x, tensor_y, tensor_d = (
                 tensor_x.to(self.device),
                 tensor_y.to(self.device),
@@ -230,6 +228,10 @@ def cal_reg_loss_over_task_loss_ratio(self):
             )
             list_reg_loss_tensor, list_mu = \
                 self.cal_reg_loss(tensor_x, tensor_y, tensor_d, others)
+
+            if ind_batch >= self.aconf.nb4reg_over_task_ratio:
+                return list_mu
+
             list_reg_loss_tensor = [torch.sum(tensor).detach().item()
                                     for tensor in list_reg_loss_tensor]
             if ind_batch == 0:
@@ -313,9 +315,12 @@ def cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
             list_reg_loss_trainer_tensor
         list_mu = list_mu_model + list_mu_trainer
         # ERM return a tensor of all zeros, delete here
-        list_boolean_zero = [torch.all(torch.eq(list_loss_tensor[i], 0)).item() for i in range(len(list_mu))]
-        list_loss_tensor = [list_loss_tensor[i] for (i, flag) in enumerate(list_boolean_zero) if not flag]
-        list_mu = [list_mu[i] for (i, flag) in enumerate(list_boolean_zero) if not flag]
+        if len(list_mu) > 1:
+            list_boolean_zero = [torch.all(torch.eq(list_loss_tensor[i], 0)).item()
+                                 for i in range(len(list_mu))]
+            list_loss_tensor = [list_loss_tensor[i] for (i, flag) in
+                                enumerate(list_boolean_zero) if not flag]
+            list_mu = [list_mu[i] for (i, flag) in enumerate(list_boolean_zero) if not flag]
         if self.dict_multiplier:
             list_mu = list(self.dict_multiplier.values())
         return list_loss_tensor, list_mu

From c09879d5970f541cca435ef3693309832b5e5ca1 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 10 Oct 2024 09:53:58 +0200
Subject: [PATCH 249/273] .

---
 examples/benchmark/aistat_irm_erm_mhof.yaml | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/examples/benchmark/aistat_irm_erm_mhof.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
index 003b7a616..326a82fc2 100644
--- a/examples/benchmark/aistat_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof.yaml
@@ -72,3 +72,11 @@ irm_erm:
   shared:
     - gamma_reg
     - nb4reg_over_task_ratio
+
+
+irm_erm_dep_dom:
+  model: erm
+  trainer: irmsepdom
+  shared:
+    - gamma_reg
+    - nb4reg_over_task_ratio

From 394cdd65f32a029c736a5f1f3036537e1392cfcf Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 10 Oct 2024 10:12:42 +0200
Subject: [PATCH 250/273] add back missing @property due to text insert

---
 domainlab/algos/msels/a_model_sel.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/domainlab/algos/msels/a_model_sel.py b/domainlab/algos/msels/a_model_sel.py
index 4f62b9982..09b703377 100644
--- a/domainlab/algos/msels/a_model_sel.py
+++ b/domainlab/algos/msels/a_model_sel.py
@@ -130,6 +130,7 @@ def oracle_last_setpoint_sel_te_acc(self):
             return self.msel.oracle_last_setpoint_sel_te_acc
         return -1
 
+    @property
     def model_selection_epoch(self):
         """
         the epoch when the model was selected

From 5585b4a2a6c02f2debc0eaf4c11ad43b962f13d6 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 10 Oct 2024 12:06:32 +0200
Subject: [PATCH 251/273] use correct hyper range

---
 examples/benchmark/aistat_irm_erm_mhof.yaml | 36 ++++++++++++---------
 1 file changed, 20 insertions(+), 16 deletions(-)

diff --git a/examples/benchmark/aistat_irm_erm_mhof.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
index 326a82fc2..0e36394b8 100644
--- a/examples/benchmark/aistat_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof.yaml
@@ -35,13 +35,22 @@ Shared params:
       - 0
       - 1
       - 100
-      
-  ini_setpoint_ratio:
-    min: 0.5
-    max: 0.99
-    num: 2
-    step: 0.05
-    distribution: uniform
+
+  mu_init:
+    distribution: categorical
+    datatype: float
+    values:
+      - 1
+      - 0.001
+
+  mu_clip:
+    distribution: categorical
+    datatype: float
+    values:
+      - 1
+      - 10
+      - 100
+      - 1000
 
   k_i_gain_ratio:
     min: 0.1
@@ -61,10 +70,13 @@ Shared params:
 fbopt_irm_erm:
   model: erm
   trainer: fbopt_irm
+  ini_setpoint_ratio: 0.99
+
   shared:
-    - ini_setpoint_ratio
     - k_i_gain_ratio
     - nb4reg_over_task_ratio
+    - mu_clip
+    - mu_init
 
 irm_erm:
   model: erm
@@ -72,11 +84,3 @@ irm_erm:
   shared:
     - gamma_reg
     - nb4reg_over_task_ratio
-
-
-irm_erm_dep_dom:
-  model: erm
-  trainer: irmsepdom
-  shared:
-    - gamma_reg
-    - nb4reg_over_task_ratio

From d176e1a110284b774e745201f00876b48c3ab8e4 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 10 Oct 2024 13:34:36 +0200
Subject: [PATCH 252/273] Update aistat_irm_erm_mhof.yaml

---
 examples/benchmark/aistat_irm_erm_mhof.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/benchmark/aistat_irm_erm_mhof.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
index 0e36394b8..d33769bbe 100644
--- a/examples/benchmark/aistat_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof.yaml
@@ -14,7 +14,7 @@ domainlab_args:
   dmem: False
   lr: 5e-5
   epos: 500
-  epos_min: 20
+  epos_min: 10
   es: 5
   bs: 32
   san_check: False

From 3a4226e68cc3a818069691bcc1dae896613257dd Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 10 Oct 2024 13:37:22 +0200
Subject: [PATCH 253/273] add unit test

---
 tests/test_irm.py | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/tests/test_irm.py b/tests/test_irm.py
index 235b9e4ce..42b12811f 100644
--- a/tests/test_irm.py
+++ b/tests/test_irm.py
@@ -12,6 +12,16 @@ def test_irm():
         --trainer=irm --nname=alexnet"
     utils_test_algo(args)
 
+def test_irm_sepdom():
+    """
+    train with Invariant Risk Minimization
+    """
+    args = "--te_d=caltech --task=mini_vlcs --debug --bs=2 --model=erm \
+        --trainer=irmsepdom --nname=alexnet"
+    utils_test_algo(args)
+
+
+
 
 def test_irm_scheduler():
     """

From 011cccbbf2ba3f76f6ea23236102c15ae958f356 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 10 Oct 2024 14:45:58 +0200
Subject: [PATCH 254/273] Update aistat_irm_erm_mhof.yaml

---
 examples/benchmark/aistat_irm_erm_mhof.yaml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/examples/benchmark/aistat_irm_erm_mhof.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
index d33769bbe..9859e4281 100644
--- a/examples/benchmark/aistat_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof.yaml
@@ -40,7 +40,7 @@ Shared params:
     distribution: categorical
     datatype: float
     values:
-      - 1
+      - 0.000001
       - 0.001
 
   mu_clip:
@@ -63,6 +63,7 @@ Shared params:
     max: 1e4
     num: 4
     distribution: loguniform
+    # 1778 is the largest gamma_reg using this sampling
 
 
 # Test fbopt with different hyperparameter configurations

From ae03219338d68e68ca5c5ab92b03b30e4ee36462 Mon Sep 17 00:00:00 2001
From: Xudong Sun <smilesun@users.noreply.github.com>
Date: Thu, 10 Oct 2024 15:35:50 +0200
Subject: [PATCH 255/273] Update and rename pacs_fbopt_dial_diva.yaml to
 aistat_pacs_mhof_dial_diva.yaml

---
 ...a.yaml => aistat_pacs_mhof_dial_diva.yaml} | 26 +++++++------------
 1 file changed, 9 insertions(+), 17 deletions(-)
 rename examples/benchmark/{pacs_fbopt_dial_diva.yaml => aistat_pacs_mhof_dial_diva.yaml} (81%)

diff --git a/examples/benchmark/pacs_fbopt_dial_diva.yaml b/examples/benchmark/aistat_pacs_mhof_dial_diva.yaml
similarity index 81%
rename from examples/benchmark/pacs_fbopt_dial_diva.yaml
rename to examples/benchmark/aistat_pacs_mhof_dial_diva.yaml
index ca2cf3921..ba0753e53 100644
--- a/examples/benchmark/pacs_fbopt_dial_diva.yaml
+++ b/examples/benchmark/aistat_pacs_mhof_dial_diva.yaml
@@ -14,7 +14,7 @@ domainlab_args:
   dmem: False
   lr: 5e-5
   epos: 500
-  epos_min: 200
+  epos_min: 20
   es: 5
   bs: 16
   san_check: False
@@ -28,13 +28,6 @@ domainlab_args:
 
 
 Shared params:
-  ini_setpoint_ratio:
-    min: 0.9
-    max: 0.99
-    num: 2
-    step: 0.05
-    distribution: uniform
-
   k_i_gain_ratio:
     min: 0.01
     max: 0.90
@@ -78,16 +71,15 @@ dial_fbopt:
   trainer: fbopt_dial
   gamma_y: 1.0
   shared:
-    - ini_setpoint_ratio
     - k_i_gain_ratio
     - dial_lr 
     - dial_epsilon
 
-# dial:
-# model: diva
-# trainer: dial
-# shared:
-# - dial_lr 
-# - dial_epsilon
-# - gamma_y
-# - gamma_d
+dial_diva:
+  model: diva
+  trainer: dial
+  shared:
+    - dial_lr 
+    - dial_epsilon
+    - gamma_y
+    - gamma_d

From 3166eb24c4b14fe9bf1d7575408eb3a8899914bc Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 10 Oct 2024 16:21:20 +0200
Subject: [PATCH 256/273] dial

---
 examples/benchmark/aistat_dial_erm_mhof.yaml | 33 +++++++++++++++-----
 1 file changed, 26 insertions(+), 7 deletions(-)

diff --git a/examples/benchmark/aistat_dial_erm_mhof.yaml b/examples/benchmark/aistat_dial_erm_mhof.yaml
index 50e801766..ad9304402 100644
--- a/examples/benchmark/aistat_dial_erm_mhof.yaml
+++ b/examples/benchmark/aistat_dial_erm_mhof.yaml
@@ -28,12 +28,28 @@ domainlab_args:
 
 
 Shared params:
-  ini_setpoint_ratio:
-    min: 0.5
-    max: 0.99
-    num: 2
-    step: 0.05
-    distribution: uniform
+  nb4reg_over_task_ratio:
+    distribution: categorical   # name of the distribution
+    datatype: int
+    values:                     # concrete values to choose from
+      - 0
+      - 100
+ 
+  mu_init:
+    distribution: categorical
+    datatype: float
+    values:
+      - 0.000001
+      - 0.001
+
+  mu_clip:
+    distribution: categorical
+    datatype: float
+    values:
+      - 1
+      - 10
+      - 100
+      - 1000
 
   k_i_gain_ratio:
     min: 0.1
@@ -53,12 +69,15 @@ Shared params:
 fbopt_dial_erm:
   model: erm
   trainer: fbopt_dial
+  nb4reg_over_task_ratio: 0
   shared:
-    - ini_setpoint_ratio
     - k_i_gain_ratio
+    - mu_init
+    - mu_clip
 
 dial_erm:
   model: erm
+  nb4reg_over_task_ratio: 0
   trainer: dial
   shared:
     - gamma_reg

From d8cee2d67a40fcc186a84358e8b131b39567f8aa Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 11 Oct 2024 08:53:32 +0200
Subject: [PATCH 257/273] fix partially issue #777

---
 domainlab/algos/trainers/args_fbopt.py | 31 +++++++++++++++++---------
 1 file changed, 20 insertions(+), 11 deletions(-)

diff --git a/domainlab/algos/trainers/args_fbopt.py b/domainlab/algos/trainers/args_fbopt.py
index 53719e05f..38ff70b55 100644
--- a/domainlab/algos/trainers/args_fbopt.py
+++ b/domainlab/algos/trainers/args_fbopt.py
@@ -9,7 +9,9 @@ def add_args2parser_fbopt(parser):
     """
 
     parser.add_argument(
-        "--k_i_gain", type=float, default=0.001, help="PID control gain for integrator"
+        "--k_i_gain", type=float, default=0.001,
+        help="PID control gain for integrator, if k_i_gain_ratio is not None, \
+        then this value will be overwriten"
     )
 
     parser.add_argument(
@@ -29,33 +31,39 @@ def add_args2parser_fbopt(parser):
     )
 
     parser.add_argument(
-        "--mu_init", type=float, default=0.001, help="initial beta for multiplication"
+        "--mu_init", type=float, default=0.001,
+        help="initial value for each component of the multiplier vector"
     )
 
     parser.add_argument(
-        "--coeff_ma", type=float, default=0.5, help="exponential moving average"
+        "--coeff_ma", type=float, default=0.5,
+        help="exponential moving average"
     )
 
     parser.add_argument(
         "--coeff_ma_output_state",
         type=float,
         default=0.1,
-        help="state exponential moving average of \
-                        reguarlization loss",
+        help="output (reguarization loss) exponential moving average",
     )
 
     parser.add_argument(
         "--coeff_ma_setpoint",
         type=float,
         default=0.9,
-        help="setpoint average coeff for previous setpoint",
+        help="setpoint average (coeff for previous setpoint)",
     )
 
     parser.add_argument(
         "--exp_shoulder_clip",
         type=float,
         default=5,
-        help="clip before exponential operation",
+        help="clip delta(control error): \
+        R(reg-loss)-b(setpoint) before exponential operation: \
+        exp[clip(R-b, exp_shoulder_clip)].\
+        exponential magnifies control error, so this argument \
+        defines the maximum rate of change of multipliers \
+        exp(5)=148",
     )
 
     parser.add_argument(
@@ -77,8 +85,8 @@ def add_args2parser_fbopt(parser):
         "--force_setpoint_change_once",
         action="store_true",
         default=False,
-        help="train until the setpoint changed at least once \
-                        up to maximum epos specified",
+        help="continue trainiing until the setpoint changed at least once: \
+              up to maximum epos specified",
     )
 
     parser.add_argument(
@@ -102,6 +110,7 @@ def add_args2parser_fbopt(parser):
         help="disable setpoint update",
     )
 
+    # FIXME: change arguments from str to boolean
     parser.add_argument(
         "--overshoot_rewind",
         type=str,
@@ -113,14 +122,14 @@ def add_args2parser_fbopt(parser):
         "--setpoint_rewind",
         type=str,
         default="no",
-        help="setpoing_rewind, for benchmark, use yes or no",
+        help="rewind setpoint, for benchmark, use yes or no",
     )
 
     parser.add_argument(
         "--str_diva_multiplier_type",
         type=str,
         default="gammad_recon",
-        help="which penalty to tune",
+        help="which penalty to tune, only useful to DIVA model",
     )
 
     return parser

From 98846403c582c9d3443e339a303d434b8d23e998 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 11 Oct 2024 11:13:39 +0200
Subject: [PATCH 258/273] detailed doc for mhof args, change str args to
 boolean, fix issue #777

---
 domainlab/algos/trainers/args_fbopt.py        | 49 ++++++++++++-------
 .../algos/trainers/fbopt_mu_controller.py     |  7 +--
 .../algos/trainers/fbopt_setpoint_ada.py      |  6 +--
 examples/benchmark/aistat_dial_erm_mhof.yaml  |  1 +
 examples/benchmark/aistat_irm_erm_mhof.yaml   | 10 +++-
 5 files changed, 48 insertions(+), 25 deletions(-)

diff --git a/domainlab/algos/trainers/args_fbopt.py b/domainlab/algos/trainers/args_fbopt.py
index 38ff70b55..c738d76ff 100644
--- a/domainlab/algos/trainers/args_fbopt.py
+++ b/domainlab/algos/trainers/args_fbopt.py
@@ -11,23 +11,31 @@ def add_args2parser_fbopt(parser):
     parser.add_argument(
         "--k_i_gain", type=float, default=0.001,
         help="PID control gain for integrator, if k_i_gain_ratio is not None, \
-        then this value will be overwriten"
+        then this value will be overwriten, see doc for k_i_gain_ratio"
     )
 
     parser.add_argument(
         "--k_i_gain_ratio",
         type=float,
         default=None,
-        help="set k_i_gain to be ratio of \
-                        initial saturation k_i_gain",
+        help="set k_i_gain to be ratio of initial saturation k_i_gain \
+        which K_I * delta = exp_shoulder_clip(saturation value), solve \
+        for K_I, where delta = reg loss - setpoint. \
+        Now independent of the scale of delta, the K_I gain will be set so \
+        that the multiplier will be increased at a rate defined by \
+        exp_shoulder_clip",
     )
 
     parser.add_argument(
-        "--mu_clip", type=float, default=1e4, help="maximum value of mu"
+        "--mu_clip", type=float, default=1e4,
+        help="maximum value of mu: mu_clip should be large enough so that the \
+        regularization loss as penalty can be weighed superior enough to \
+        decrease."
     )
 
     parser.add_argument(
-        "--mu_min", type=float, default=1e-6, help="minimum value of mu"
+        "--mu_min", type=float, default=1e-6, help="minimum value of mu, mu \
+        can not be negative"
     )
 
     parser.add_argument(
@@ -37,14 +45,17 @@ def add_args2parser_fbopt(parser):
 
     parser.add_argument(
         "--coeff_ma", type=float, default=0.5,
-        help="exponential moving average"
+        help="exponential moving average of delta \
+        (reg minus setpoint as control error): \
+        move_ave=move_ave + coeff*delta(current value)"
     )
 
     parser.add_argument(
         "--coeff_ma_output_state",
         type=float,
         default=0.1,
-        help="output (reguarization loss) exponential moving average",
+        help="output (reguarization loss) exponential moving average \
+        move_ave=move_ave*coeef + reg(current value)",
     )
 
     parser.add_argument(
@@ -63,7 +74,8 @@ def add_args2parser_fbopt(parser):
         exp[clip(R-b, exp_shoulder_clip)].\
         exponential magnifies control error, so this argument \
         defines the maximum rate of change of multipliers \
-        exp(5)=148",
+        exp(5)=148, exp_shoulder_clip should not be too big, \
+        if exp_shoulder_clip is small, then more like exterior point method",
     )
 
     parser.add_argument(
@@ -71,7 +83,7 @@ def add_args2parser_fbopt(parser):
         type=float,
         default=0.99,
         help="before training start, evaluate reg loss, \
-                        setpoint will be 0.9 of this loss",
+              setpoint will be 0.9 of this loss",
     )
 
     parser.add_argument(
@@ -85,7 +97,7 @@ def add_args2parser_fbopt(parser):
         "--force_setpoint_change_once",
         action="store_true",
         default=False,
-        help="continue trainiing until the setpoint changed at least once: \
+        help="continue training until the setpoint changed at least once: \
               up to maximum epos specified",
     )
 
@@ -110,21 +122,22 @@ def add_args2parser_fbopt(parser):
         help="disable setpoint update",
     )
 
-    # FIXME: change arguments from str to boolean
     parser.add_argument(
-        "--overshoot_rewind",
-        type=str,
-        default="yes",
-        help="overshoot_rewind, for benchmark, use yes or no",
+        "--no_overshoot_rewind",
+        action="store_true",
+        default=False,
+        help="disable overshoot rewind: when reg loss satisfies setpoint \
+        already, then set activation=K_I*delta = 0",
     )
 
     parser.add_argument(
         "--setpoint_rewind",
-        type=str,
-        default="no",
-        help="rewind setpoint, for benchmark, use yes or no",
+        action="store_true",
+        default=False,
+        help="rewind setpoint",
     )
 
+    # this arg is only used when model is set to be "diva"
     parser.add_argument(
         "--str_diva_multiplier_type",
         type=str,
diff --git a/domainlab/algos/trainers/fbopt_mu_controller.py b/domainlab/algos/trainers/fbopt_mu_controller.py
index 5c635e147..bfdccbcbd 100644
--- a/domainlab/algos/trainers/fbopt_mu_controller.py
+++ b/domainlab/algos/trainers/fbopt_mu_controller.py
@@ -53,13 +53,13 @@ def __init__(self, trainer, **kwargs):
         self.k_i_control = [trainer.aconf.k_i_gain for i in
                             range(len(self.mmu))]
         self.k_i_gain_ratio = trainer.aconf.k_i_gain_ratio
-        self.overshoot_rewind = trainer.aconf.overshoot_rewind == "yes"
+        self.overshoot_rewind = not trainer.aconf.no_overshoot_rewind
         self.delta_epsilon_r = None
 
         # NOTE: this value will be set according to initial evaluation of
         # neural network
         self.activation_clip = trainer.aconf.exp_shoulder_clip
-        self.coeff_ma = trainer.aconf.coeff_ma
+        self.coeff4newval_ma_delta = trainer.aconf.coeff_ma
         # NOTE:
         # print(copy.deepcopy(self.model))
         # TypeError: cannot pickle '_thread.lock' object
@@ -125,7 +125,8 @@ def cal_delta4control(self, list1, list_setpoint):
             # self.delta_epsilon_r is the previous time step.
             # delta_epsilon_r is the current time step
             self.delta_epsilon_r = self.cal_delta_integration(
-                self.delta_epsilon_r, delta_epsilon_r, self.coeff_ma
+                self.delta_epsilon_r, delta_epsilon_r,
+                self.coeff4newval_ma_delta
             )
 
     def cal_delta_integration(self, list_old, list_new, coeff):
diff --git a/domainlab/algos/trainers/fbopt_setpoint_ada.py b/domainlab/algos/trainers/fbopt_setpoint_ada.py
index c3c0193ce..d243fc5e8 100644
--- a/domainlab/algos/trainers/fbopt_setpoint_ada.py
+++ b/domainlab/algos/trainers/fbopt_setpoint_ada.py
@@ -81,7 +81,7 @@ def __init__(self, host):
         self.counter = None
         self.epo_ma = None
         self.ref = None
-        self.coeff_ma = 0.5
+        self.coeff_ma_setpoint_rewinder = 0.5
         self.setpoint_rewind = host.flag_setpoint_rewind
 
     def reset(self, epo_reg_loss):
@@ -98,7 +98,7 @@ def observe(self, epo_reg_loss):
         """
         if self.ref is None:
             self.reset(epo_reg_loss)
-        self.epo_ma = list_ma(self.epo_ma, epo_reg_loss, self.coeff_ma)
+        self.epo_ma = list_ma(self.epo_ma, epo_reg_loss, self.coeff_ma_setpoint_rewinder)
         list_comparison_increase = [a < b for a, b in zip(self.ref, self.epo_ma)]
         list_comparison_above_setpoint = [
             a < b for a, b in zip(self.host.setpoint4R, self.epo_ma)
@@ -146,7 +146,7 @@ def __init__(self, state=None, args=None):
             else:
                 state = DominateAllComponent()
         self.transition_to(state)
-        self.flag_setpoint_rewind = args.setpoint_rewind == "yes"
+        self.flag_setpoint_rewind = args.setpoint_rewind
         self.setpoint_rewinder = SetpointRewinder(self)
         self.state_task_loss = 0.0
         self.state_epo_reg_loss = [
diff --git a/examples/benchmark/aistat_dial_erm_mhof.yaml b/examples/benchmark/aistat_dial_erm_mhof.yaml
index ad9304402..ab530d72f 100644
--- a/examples/benchmark/aistat_dial_erm_mhof.yaml
+++ b/examples/benchmark/aistat_dial_erm_mhof.yaml
@@ -70,6 +70,7 @@ fbopt_dial_erm:
   model: erm
   trainer: fbopt_dial
   nb4reg_over_task_ratio: 0
+  force_setpoint_change_once: True
   shared:
     - k_i_gain_ratio
     - mu_init
diff --git a/examples/benchmark/aistat_irm_erm_mhof.yaml b/examples/benchmark/aistat_irm_erm_mhof.yaml
index 9859e4281..f4a508896 100644
--- a/examples/benchmark/aistat_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof.yaml
@@ -52,6 +52,14 @@ Shared params:
       - 100
       - 1000
 
+  exp_shoulder_clip:
+    distribution: categorical
+    datatype: float
+    values:
+      - 1
+      - 2
+      - 5
+
   k_i_gain_ratio:
     min: 0.1
     max: 1
@@ -72,7 +80,7 @@ fbopt_irm_erm:
   model: erm
   trainer: fbopt_irm
   ini_setpoint_ratio: 0.99
-
+  force_setpoint_change_once: True
   shared:
     - k_i_gain_ratio
     - nb4reg_over_task_ratio

From cd1591581479d408bdf6e0788b655fab33d2d829 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 11 Oct 2024 12:00:06 +0200
Subject: [PATCH 259/273] new irm yaml file

---
 ...rm_only.yaml => aistat_irm_erm_mhof2.yaml} | 69 +++++++++++++------
 1 file changed, 47 insertions(+), 22 deletions(-)
 rename examples/benchmark/{aistat_irm_erm_only.yaml => aistat_irm_erm_mhof2.yaml} (51%)

diff --git a/examples/benchmark/aistat_irm_erm_only.yaml b/examples/benchmark/aistat_irm_erm_mhof2.yaml
similarity index 51%
rename from examples/benchmark/aistat_irm_erm_only.yaml
rename to examples/benchmark/aistat_irm_erm_mhof2.yaml
index 2a9c011e8..d9f8e4037 100644
--- a/examples/benchmark/aistat_irm_erm_only.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof2.yaml
@@ -1,6 +1,6 @@
 mode: grid
 
-output_dir: zoutput/benchmarks/benchmark_irm_erm
+output_dir: zoutput/benchmarks/benchmark_mhof_irm_erm_pacs
 
 sampling_seed: 0
 startseed: 0
@@ -13,7 +13,7 @@ domainlab_args:
   tpath: examples/tasks/task_pacs_aug.py
   dmem: False
   lr: 5e-5
-  epos: 500
+  epos: 100
   epos_min: 10
   es: 5
   bs: 32
@@ -33,42 +33,67 @@ Shared params:
     datatype: int
     values:                     # concrete values to choose from
       - 0
+      - 100
+
+  mu_init:
+    distribution: categorical
+    datatype: float
+    values:
+      - 0.000001
+      - 0.001
+
+  mu_clip:
+    distribution: categorical
+    datatype: float
+    values:
       - 1
+      - 10
       - 100
-      
-  ini_setpoint_ratio:
-    min: 0.5
-    max: 0.99
-    num: 2
-    step: 0.05
-    distribution: uniform
+      - 1000
+
+  exp_shoulder_clip:
+    distribution: categorical
+    datatype: float
+    values:
+      - 1
+      - 5
 
-  k_i_gain:
-    min: 0.0001
-    max: 0.01
+  k_i_gain_ratio:
+    min: 0.1
+    max: 1
     num: 2
-    step: 0.0001
     distribution: uniform
 
   gamma_reg:
-    min: 0.01
-    max: 1e4
-    num: 10
-    distribution: loguniform
+    distribution: categorical
+    datatype: float
+    values:
+      - 0.01
+      - 0.1
+      - 1
+      - 10
+      - 100
+
+    # 1778 is the largest gamma_reg using this sampling
 
 
 # Test fbopt with different hyperparameter configurations
 
-irm_erm:
+fbopt_irm_erm:
   model: erm
-  trainer: irm
+  trainer: fbopt_irm
+  ini_setpoint_ratio: 0.99
+  force_setpoint_change_once: True
+  mu_clip: 10000
   shared:
-    - gamma_reg
+    - k_i_gain_ratio
     - nb4reg_over_task_ratio
+    - mu_init
+    - exp_shoulder_clip
 
-irm_erm_dep_dom:
+irm_erm:
   model: erm
-  trainer: irmsepdom
+  trainer: irm
   shared:
     - gamma_reg
     - nb4reg_over_task_ratio

From 273422bf1fdb8fd13422df98ddd7dbe3bfe4bed6 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 11 Oct 2024 12:17:32 +0200
Subject: [PATCH 260/273] .

---
 a_test_mhof_irm.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/a_test_mhof_irm.sh b/a_test_mhof_irm.sh
index 610d3a606..f3aaf549d 100644
--- a/a_test_mhof_irm.sh
+++ b/a_test_mhof_irm.sh
@@ -1 +1 @@
-python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=fbopt_irm --nname=conv_bn_pool_2 --k_i_gain_ratio=0.5
+python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=fbopt_irm --nname=conv_bn_pool_2 --k_i_gain_ratio=0.5 --force_setpoint_change_once

From dbbda55ea1c3708524511088814ec51855ff8829 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 11 Oct 2024 13:07:41 +0200
Subject: [PATCH 261/273] take square of irm loss, copy reg loss from decoratee
 to fbopt

---
 a_test_mhof_irm.sh                        | 2 +-
 domainlab/algos/trainers/train_fbopt_b.py | 8 ++++++++
 domainlab/algos/trainers/train_irm.py     | 2 ++
 3 files changed, 11 insertions(+), 1 deletion(-)

diff --git a/a_test_mhof_irm.sh b/a_test_mhof_irm.sh
index f3aaf549d..85b9445cc 100644
--- a/a_test_mhof_irm.sh
+++ b/a_test_mhof_irm.sh
@@ -1 +1 @@
-python main_out.py --te_d=0 --task=mnistcolor10 --model=erm --trainer=fbopt_irm --nname=conv_bn_pool_2 --k_i_gain_ratio=0.5 --force_setpoint_change_once
+python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --trainer=fbopt_irm --nname=conv_bn_pool_2 --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500
diff --git a/domainlab/algos/trainers/train_fbopt_b.py b/domainlab/algos/trainers/train_fbopt_b.py
index 43a5bf619..e786579c2 100644
--- a/domainlab/algos/trainers/train_fbopt_b.py
+++ b/domainlab/algos/trainers/train_fbopt_b.py
@@ -122,6 +122,7 @@ def before_tr(self):
             self.epo_task_loss_tr,
             self.epo_loss_tr,
         ) = self.eval_r_loss()
+
         self.hyper_scheduler.set_setpoint(
             [
                 ele * self.aconf.ini_setpoint_ratio
@@ -172,6 +173,13 @@ def tr_epoch(self, epoch, flag_info=False):
 
         if self._decoratee is not None:
             flag = self._decoratee.tr_epoch(epoch, self.flag_setpoint_updated)
+            # self._decoratee.tr_epoch here will call
+            # self._decoratee.after_epoch to log the losses, but it only sotre
+            # the value into self._decoratee,
+            # so we have to mannually copy the value here
+            self.epo_loss_tr = self._decoratee.epo_loss_tr
+            self.epo_reg_loss_tr = self._decoratee.epo_reg_loss_tr
+            self.epo_task_loss_tr = self._decoratee.epo_task_loss_tr
         else:
             flag = super().tr_epoch(epoch, self.flag_setpoint_updated)
         # is it good to update setpoint after we know the new value of each loss?
diff --git a/domainlab/algos/trainers/train_irm.py b/domainlab/algos/trainers/train_irm.py
index aaa9f2dd0..09748ee1f 100644
--- a/domainlab/algos/trainers/train_irm.py
+++ b/domainlab/algos/trainers/train_irm.py
@@ -33,10 +33,12 @@ def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         with torch.enable_grad():
             phi = self._cal_phi(tensor_x)
             dummy_w_scale = torch.tensor(1.).to(tensor_x.device).requires_grad_()
+            # interleave instances inside a minibatch
             loss_1 = F.cross_entropy(phi[::2] * dummy_w_scale, y[::2])
             loss_2 = F.cross_entropy(phi[1::2] * dummy_w_scale, y[1::2])
             grad_1 = autograd.grad(loss_1, [dummy_w_scale], create_graph=True)[0]
             grad_2 = autograd.grad(loss_2, [dummy_w_scale], create_graph=True)[0]
             loss_irm_scalar = torch.sum(grad_1 * grad_2)  # scalar
+            loss_irm_scalar = torch.square(loss_irm_scalar)
             loss_irm_tensor = loss_irm_scalar.expand(tensor_x.shape[0])
             return [loss_irm_tensor], [self.aconf.gamma_reg]

From 1cb2428219f7b02dcd3ca2321048130f132d0d10 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 11 Oct 2024 13:23:50 +0200
Subject: [PATCH 262/273] .

---
 examples/benchmark/aistat_irm_erm_mhof2.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/benchmark/aistat_irm_erm_mhof2.yaml b/examples/benchmark/aistat_irm_erm_mhof2.yaml
index d9f8e4037..ffdde0425 100644
--- a/examples/benchmark/aistat_irm_erm_mhof2.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof2.yaml
@@ -1,6 +1,6 @@
 mode: grid
 
-output_dir: zoutput/benchmarks/benchmark_mhof_irm_erm_pacs
+output_dir: zoutput/benchmarks/mhof_irm_erm_pacs
 
 sampling_seed: 0
 startseed: 0

From 155f0df5dec9884431244329d522e3b8b8c3e093 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 11 Oct 2024 13:27:42 +0200
Subject: [PATCH 263/273] .

---
 examples/benchmark/aistat_irm_erm_mhof2.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/benchmark/aistat_irm_erm_mhof2.yaml b/examples/benchmark/aistat_irm_erm_mhof2.yaml
index ffdde0425..f6bc9467e 100644
--- a/examples/benchmark/aistat_irm_erm_mhof2.yaml
+++ b/examples/benchmark/aistat_irm_erm_mhof2.yaml
@@ -46,7 +46,6 @@ Shared params:
     distribution: categorical
     datatype: float
     values:
-      - 1
       - 10
       - 100
       - 1000
@@ -73,6 +72,7 @@ Shared params:
       - 1
       - 10
       - 100
+      - 1000
 
     # 1778 is the largest gamma_reg using this sampling
 
@@ -84,11 +84,11 @@ fbopt_irm_erm:
   trainer: fbopt_irm
   ini_setpoint_ratio: 0.99
   force_setpoint_change_once: True
-  mu_clip: 10000
   shared:
     - k_i_gain_ratio
     - nb4reg_over_task_ratio
     - mu_init
+    - mu_clip
     - exp_shoulder_clip
 
 irm_erm:

From c41e92b5aae5f04756c5613c72d9932c4ac204ec Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Fri, 11 Oct 2024 14:31:52 +0200
Subject: [PATCH 264/273] .

---
 a_test_mhof_irm.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/a_test_mhof_irm.sh b/a_test_mhof_irm.sh
index 85b9445cc..4168c5e8c 100644
--- a/a_test_mhof_irm.sh
+++ b/a_test_mhof_irm.sh
@@ -1 +1 @@
-python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --trainer=fbopt_irm --nname=conv_bn_pool_2 --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500
+python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=fbopt_irm --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500 --epos_min=400 --exp_shoulder_clip=1 --mu_clip=100 --ini_setpoint_ratio=0.99999999

From b8731cb29d973276d141449ae54cb82f928c446b Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sun, 13 Oct 2024 14:16:29 +0200
Subject: [PATCH 265/273] Milestone: feedforward works now with trainers

---
 a_test_mhof_irm.sh                                |  2 +-
 domainlab/algos/trainers/train_dial.py            |  9 +++++----
 domainlab/algos/trainers/train_hyper_scheduler.py | 12 ++++++++----
 3 files changed, 14 insertions(+), 9 deletions(-)

diff --git a/a_test_mhof_irm.sh b/a_test_mhof_irm.sh
index 4168c5e8c..653dec138 100644
--- a/a_test_mhof_irm.sh
+++ b/a_test_mhof_irm.sh
@@ -1 +1 @@
-python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=fbopt_irm --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500 --epos_min=400 --exp_shoulder_clip=1 --mu_clip=100 --ini_setpoint_ratio=0.99999999
+python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=fbopt_irm_dial --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500 --epos_min=400 --exp_shoulder_clip=1 --mu_clip=100 --ini_setpoint_ratio=0.99999999
diff --git a/domainlab/algos/trainers/train_dial.py b/domainlab/algos/trainers/train_dial.py
index 4fe700f45..711a83008 100644
--- a/domainlab/algos/trainers/train_dial.py
+++ b/domainlab/algos/trainers/train_dial.py
@@ -47,7 +47,8 @@ def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         """
         _ = tensor_d
         _ = others
-        tensor_x_adv = self.gen_adversarial(self.device, tensor_x, tensor_y)
-        tensor_x_batch_adv_no_grad = Variable(tensor_x_adv, requires_grad=False)
-        loss_dial = self.model.cal_task_loss(tensor_x_batch_adv_no_grad, tensor_y)
-        return [loss_dial], [get_gamma_reg(self.aconf, self.name)]
+        with torch.enable_grad():
+            tensor_x_adv = self.gen_adversarial(self.device, tensor_x, tensor_y)
+            tensor_x_batch_adv_no_grad = Variable(tensor_x_adv, requires_grad=False)
+            loss_dial = self.model.cal_task_loss(tensor_x_batch_adv_no_grad, tensor_y)
+            return [loss_dial], [get_gamma_reg(self.aconf, self.name)]
diff --git a/domainlab/algos/trainers/train_hyper_scheduler.py b/domainlab/algos/trainers/train_hyper_scheduler.py
index e595ea0fe..00b1cb1d3 100644
--- a/domainlab/algos/trainers/train_hyper_scheduler.py
+++ b/domainlab/algos/trainers/train_hyper_scheduler.py
@@ -25,7 +25,7 @@ def set_scheduler(
             flag_update_epoch: if hyper-parameters should be changed per epoch
             flag_update_batch: if hyper-parameters should be changed per batch
         """
-        self.hyper_scheduler = self.model.hyper_init(scheduler)
+        self.hyper_scheduler = self.decoratee.hyper_init(scheduler, trainer=self)
         # let model register its hyper-parameters to the scheduler
         self.flag_update_hyper_per_epoch = flag_update_epoch
         self.flag_update_hyper_per_batch = flag_update_batch
@@ -37,12 +37,14 @@ def before_batch(self, epoch, ind_batch):
         should be set to epoch*self.num_batches + ind_batch
         """
         if self.flag_update_hyper_per_batch:
-            self.model.hyper_update(
+            self.decoratee.hyper_update(
                 epoch * self.num_batches + ind_batch, self.hyper_scheduler
             )
         return super().before_batch(epoch, ind_batch)
 
     def before_tr(self):
+        if hasattr(self.decoratee, "before_tr"):
+            self.decoratee.before_tr()
         if self.hyper_scheduler is None:
             logger = Logger.get_logger()
             logger.warning(
@@ -54,12 +56,14 @@ def before_tr(self):
                 total_steps=self.aconf.warmup,
                 flag_update_epoch=True,
             )
-        super().before_tr()
 
     def tr_epoch(self, epoch, flag_info=False):
         """
         update hyper-parameters only per epoch
         """
         if self.flag_update_hyper_per_epoch:
-            self.model.hyper_update(epoch, self.hyper_scheduler)
+            self.decoratee.hyper_update(epoch, self.hyper_scheduler)
+        if hasattr(self.decoratee, "dict_multiplier"):
+            logger = Logger.get_logger()
+            logger.info(f"---before epoch, current multiplier: {self.decoratee.dict_multiplier}")
         return super().tr_epoch(epoch)

From f4e47732fd1e675d29b6ac71ffc8d85a91614627 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Sun, 13 Oct 2024 14:16:45 +0200
Subject: [PATCH 266/273] yaml for feedforward

---
 a_test_feedforward_irm.sh                     |   1 +
 ...istat_trainer_combo_dial_irm_erm_mhof.yaml | 102 ++++++++++++++++++
 2 files changed, 103 insertions(+)
 create mode 100644 a_test_feedforward_irm.sh
 create mode 100644 examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof.yaml

diff --git a/a_test_feedforward_irm.sh b/a_test_feedforward_irm.sh
new file mode 100644
index 000000000..007f3e9ac
--- /dev/null
+++ b/a_test_feedforward_irm.sh
@@ -0,0 +1 @@
+python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=hyperscheduler_irm_dial --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=10 --epos_min=4 --exp_shoulder_clip=1 --mu_clip=100 --ini_setpoint_ratio=0.99999999
diff --git a/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof.yaml b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof.yaml
new file mode 100644
index 000000000..919100cef
--- /dev/null
+++ b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof.yaml
@@ -0,0 +1,102 @@
+mode: grid
+
+output_dir: zoutput/benchmarks/mhof_combo_irm_dial_pacs
+
+sampling_seed: 0
+startseed: 0
+endseed: 2
+
+test_domains:
+  - sketch
+
+domainlab_args:
+  tpath: examples/tasks/task_pacs_aug.py
+  dmem: False
+  lr: 5e-5
+  epos: 100
+  epos_min: 10
+  es: 5
+  bs: 32
+  san_check: False
+  npath: examples/nets/resnet50domainbed.py
+  npath_dom: examples/nets/resnet50domainbed.py
+  zx_dim: 0
+  zy_dim: 64
+  zd_dim: 64
+
+
+
+
+Shared params:
+  nb4reg_over_task_ratio:
+    distribution: categorical   # name of the distribution
+    datatype: int
+    values:                     # concrete values to choose from
+      - 0
+      - 100
+
+  mu_init:
+    distribution: categorical
+    datatype: float
+    values:
+      - 0.000001
+      - 0.001
+
+  mu_clip:
+    distribution: categorical
+    datatype: float
+    values:
+      - 10
+      - 100
+      - 1000
+
+  exp_shoulder_clip:
+    distribution: categorical
+    datatype: float
+    values:
+      - 1
+      - 5
+
+  k_i_gain_ratio:
+    min: 0.1
+    max: 1
+    num: 2
+    distribution: uniform
+
+  gamma_reg:
+    distribution: categorical
+    datatype: float
+    values:
+      - 0.01
+      - 0.1
+      - 1
+      - 10
+      - 100
+      - 1000
+
+
+fbopt_irm_dial_erm:
+  model: erm
+  trainer: fbopt_irm_dial
+  ini_setpoint_ratio: 0.99
+  force_setpoint_change_once: True
+  shared:
+    - k_i_gain_ratio
+    - nb4reg_over_task_ratio
+    - mu_init
+    - mu_clip
+    - exp_shoulder_clip
+
+irm_dial:
+  model: erm
+  trainer: irm_dial
+  shared:
+    - gamma_reg
+    - nb4reg_over_task_ratio
+
+irm_dial_feedforward_full:
+  model: erm
+  trainer: hyperscheduler_irm_dial
+  shared:
+    - gamma_reg
+    - nb4reg_over_task_ratio

From e3ed8c6f9a4ba8567a824986940fa6b7a98573d9 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 15 Oct 2024 11:36:13 +0200
Subject: [PATCH 267/273] tr_with_init_mu

---
 a_test_mhof_irm.sh                            |  2 +-
 domainlab/algos/trainers/a_trainer.py         | 11 ++-
 .../algos/trainers/fbopt_mu_controller.py     |  6 +-
 domainlab/algos/trainers/train_basic.py       |  6 --
 domainlab/algos/trainers/train_fbopt_b.py     |  1 +
 ...istat_trainer_combo_dial_irm_erm_mhof.yaml |  1 +
 ..._trainer_combo_dial_irm_erm_mhof_only.yaml | 89 +++++++++++++++++++
 7 files changed, 107 insertions(+), 9 deletions(-)
 create mode 100644 examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml

diff --git a/a_test_mhof_irm.sh b/a_test_mhof_irm.sh
index 653dec138..27d4e8658 100644
--- a/a_test_mhof_irm.sh
+++ b/a_test_mhof_irm.sh
@@ -1 +1 @@
-python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=fbopt_irm_dial --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500 --epos_min=400 --exp_shoulder_clip=1 --mu_clip=100 --ini_setpoint_ratio=0.99999999
+python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=fbopt_irm_dial --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500 --epos_min=400 --exp_shoulder_clip=1 --mu_clip=100 --ini_setpoint_ratio=0.99999999 --nb4reg_over_task_ratio=0 --tr_with_init_mu
diff --git a/domainlab/algos/trainers/a_trainer.py b/domainlab/algos/trainers/a_trainer.py
index 99460afc9..24e0ccc21 100644
--- a/domainlab/algos/trainers/a_trainer.py
+++ b/domainlab/algos/trainers/a_trainer.py
@@ -323,7 +323,16 @@ def cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
             list_mu = [list_mu[i] for (i, flag) in enumerate(list_boolean_zero) if not flag]
         if self.dict_multiplier:
             list_mu = list(self.dict_multiplier.values())
-        return list_loss_tensor, list_mu
+
+        list_loss_tensor_normalized = list_loss_tensor
+        if self.list_reg_over_task_ratio:
+            assert len(list_mu) == len(self.list_reg_over_task_ratio)
+            list_loss_tensor_normalized = \
+                [reg_loss / reg_over_task_ratio if reg_over_task_ratio != 0
+                 else reg_loss for (reg_loss, reg_over_task_ratio)
+                 in zip(list_loss_tensor, self.list_reg_over_task_ratio)]
+
+        return list_loss_tensor_normalized, list_mu
 
     def _cal_reg_loss(self, tensor_x, tensor_y, tensor_d, others=None):
         """
diff --git a/domainlab/algos/trainers/fbopt_mu_controller.py b/domainlab/algos/trainers/fbopt_mu_controller.py
index bfdccbcbd..5c8efdcac 100644
--- a/domainlab/algos/trainers/fbopt_mu_controller.py
+++ b/domainlab/algos/trainers/fbopt_mu_controller.py
@@ -91,7 +91,11 @@ def set_k_i_gain(self, epo_reg_loss):
         k_i_gain_saturate_min = min(k_i_gain_saturate)
         # NOTE: here we override the commandline arguments specification
         # for k_i_control, so k_i_control is not a hyperparameter anymore
-        self.k_i_control = [self.k_i_gain_ratio * ele for ele in k_i_gain_saturate]
+        # self.k_i_control = [self.k_i_gain_ratio * ele for ele in k_i_gain_saturate]
+        # k_I should be the same for each component, the control error already
+        # make the multiplier magnification different
+        self.k_i_control = [self.k_i_gain_ratio * k_i_gain_saturate_min for i
+                            in range(len(delta_epsilon_r))]
         warnings.warn(
             f"hyperparameter k_i_gain disabled! \
                       replace with {self.k_i_control}"
diff --git a/domainlab/algos/trainers/train_basic.py b/domainlab/algos/trainers/train_basic.py
index 0e7faf8e4..0e2cd5dec 100644
--- a/domainlab/algos/trainers/train_basic.py
+++ b/domainlab/algos/trainers/train_basic.py
@@ -96,12 +96,6 @@ def cal_loss(self, tensor_x, tensor_y, tensor_d, others):
             tensor_x, tensor_y, tensor_d, others
         )
         list_mu_tr_normalized = list_mu_tr
-        if self.list_reg_over_task_ratio:
-            assert len(list_mu_tr) == len(self.list_reg_over_task_ratio)
-            list_mu_tr_normalized = \
-                [mu / reg_over_task_ratio if reg_over_task_ratio != 0
-                 else mu for (mu, reg_over_task_ratio)
-                 in zip(list_mu_tr, self.list_reg_over_task_ratio)]
         tensor_batch_reg_loss_penalized = self.model.list_inner_product(
             list_reg_tr_batch, list_mu_tr_normalized
         )
diff --git a/domainlab/algos/trainers/train_fbopt_b.py b/domainlab/algos/trainers/train_fbopt_b.py
index e786579c2..2c1483aa9 100644
--- a/domainlab/algos/trainers/train_fbopt_b.py
+++ b/domainlab/algos/trainers/train_fbopt_b.py
@@ -117,6 +117,7 @@ def before_tr(self):
         if self.aconf.tr_with_init_mu:
             self.tr_with_init_mu()
 
+        # evaluate regularization loss list
         (
             self.epo_reg_loss_tr,
             self.epo_task_loss_tr,
diff --git a/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof.yaml b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof.yaml
index 919100cef..35ca668ba 100644
--- a/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof.yaml
+++ b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof.yaml
@@ -80,6 +80,7 @@ fbopt_irm_dial_erm:
   trainer: fbopt_irm_dial
   ini_setpoint_ratio: 0.99
   force_setpoint_change_once: True
+  tr_with_init_mu: True
   shared:
     - k_i_gain_ratio
     - nb4reg_over_task_ratio
diff --git a/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
new file mode 100644
index 000000000..81cc10609
--- /dev/null
+++ b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
@@ -0,0 +1,89 @@
+mode: grid
+
+output_dir: zoutput/benchmarks/mhof_combo_irm_dial_pacs
+
+sampling_seed: 0
+startseed: 0
+endseed: 2
+
+test_domains:
+  - sketch
+
+domainlab_args:
+  tpath: examples/tasks/task_pacs_aug.py
+  dmem: False
+  lr: 5e-5
+  epos: 100
+  epos_min: 10
+  es: 5
+  bs: 32
+  san_check: False
+  npath: examples/nets/resnet50domainbed.py
+  npath_dom: examples/nets/resnet50domainbed.py
+  zx_dim: 0
+  zy_dim: 64
+  zd_dim: 64
+
+
+
+
+Shared params:
+  nb4reg_over_task_ratio:
+    distribution: categorical   # name of the distribution
+    datatype: int
+    values:                     # concrete values to choose from
+      - 0
+      - 100
+
+  mu_init:
+    distribution: categorical
+    datatype: float
+    values:
+      - 0.000001
+      - 0.001
+
+  mu_clip:
+    distribution: categorical
+    datatype: float
+    values:
+      - 10
+      - 100
+      - 1000
+
+  exp_shoulder_clip:
+    distribution: categorical
+    datatype: float
+    values:
+      - 1
+      - 5
+
+  k_i_gain_ratio:
+    min: 0.1
+    max: 1
+    num: 2
+    distribution: uniform
+
+  gamma_reg:
+    distribution: categorical
+    datatype: float
+    values:
+      - 0.01
+      - 0.1
+      - 1
+      - 10
+      - 100
+      - 1000
+
+
+fbopt_irm_dial_erm:
+  model: erm
+  trainer: fbopt_irm_dial
+  ini_setpoint_ratio: 0.99
+  force_setpoint_change_once: True
+  tr_with_init_mu: True
+  shared:
+    - k_i_gain_ratio
+    - nb4reg_over_task_ratio
+    - mu_init
+    - mu_clip
+    - exp_shoulder_clip

From e38fa758cdbda89246281adc8578d2243ac5fdad Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 15 Oct 2024 11:43:42 +0200
Subject: [PATCH 268/273] doc

---
 domainlab/algos/trainers/train_fbopt_b.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/domainlab/algos/trainers/train_fbopt_b.py b/domainlab/algos/trainers/train_fbopt_b.py
index 2c1483aa9..ff9302274 100644
--- a/domainlab/algos/trainers/train_fbopt_b.py
+++ b/domainlab/algos/trainers/train_fbopt_b.py
@@ -106,6 +106,7 @@ def before_batch(self, epoch, ind_batch):
 
     def before_tr(self):
         if hasattr(self.decoratee, "before_tr"):
+            # initialize self.decoratee.dict_multiplier
             self.decoratee.before_tr()
         self.flag_setpoint_updated = False
         if self.aconf.force_feedforward:

From 044e3ccb514c892ebedd82a87fe1648fc95c054d Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Tue, 15 Oct 2024 11:52:24 +0200
Subject: [PATCH 269/273] .

---
 .../benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml  | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
index 81cc10609..9ecad287b 100644
--- a/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
+++ b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
@@ -1,6 +1,6 @@
 mode: grid
 
-output_dir: zoutput/benchmarks/mhof_combo_irm_dial_pacs
+output_dir: zoutput/benchmarks/only_mhof_combo_irm_dial_pacs
 
 sampling_seed: 0
 startseed: 0

From aea6e907316118e6d5b482bb92360c75ff4aedb5 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 17 Oct 2024 10:29:03 +0200
Subject: [PATCH 270/273] no ma for setpoint

---
 a_test_mhof_irm.sh                                    |  2 +-
 domainlab/algos/trainers/fbopt_mu_controller.py       |  2 ++
 domainlab/algos/trainers/train_fbopt_b.py             | 11 +++++++++--
 .../aistat_trainer_combo_dial_irm_erm_mhof_only.yaml  |  3 ++-
 4 files changed, 14 insertions(+), 4 deletions(-)

diff --git a/a_test_mhof_irm.sh b/a_test_mhof_irm.sh
index 27d4e8658..df138e487 100644
--- a/a_test_mhof_irm.sh
+++ b/a_test_mhof_irm.sh
@@ -1 +1 @@
-python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=fbopt_irm_dial --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500 --epos_min=400 --exp_shoulder_clip=1 --mu_clip=100 --ini_setpoint_ratio=0.99999999 --nb4reg_over_task_ratio=0 --tr_with_init_mu
+python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=fbopt_irm_dial --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500 --epos_min=400 --exp_shoulder_clip=1 --mu_clip=100 --ini_setpoint_ratio=0.9 --nb4reg_over_task_ratio=0 --tr_with_init_mu --coeff_ma_setpoint=0.0
diff --git a/domainlab/algos/trainers/fbopt_mu_controller.py b/domainlab/algos/trainers/fbopt_mu_controller.py
index 5c8efdcac..ce53fc0df 100644
--- a/domainlab/algos/trainers/fbopt_mu_controller.py
+++ b/domainlab/algos/trainers/fbopt_mu_controller.py
@@ -88,6 +88,8 @@ def set_k_i_gain(self, epo_reg_loss):
             a / b for a, b in zip(list_active, delta_epsilon_r)
         ]
 
+        # FIXME: add max K_I gain here if initial delta is too small
+
         k_i_gain_saturate_min = min(k_i_gain_saturate)
         # NOTE: here we override the commandline arguments specification
         # for k_i_control, so k_i_control is not a hyperparameter anymore
diff --git a/domainlab/algos/trainers/train_fbopt_b.py b/domainlab/algos/trainers/train_fbopt_b.py
index ff9302274..b47ffc69e 100644
--- a/domainlab/algos/trainers/train_fbopt_b.py
+++ b/domainlab/algos/trainers/train_fbopt_b.py
@@ -115,8 +115,6 @@ def before_tr(self):
             self.set_scheduler(scheduler=HyperSchedulerFeedback)
 
         self.set_model_with_mu()  # very small value
-        if self.aconf.tr_with_init_mu:
-            self.tr_with_init_mu()
 
         # evaluate regularization loss list
         (
@@ -125,6 +123,15 @@ def before_tr(self):
             self.epo_loss_tr,
         ) = self.eval_r_loss()
 
+        if self.aconf.tr_with_init_mu:
+            self.tr_with_init_mu()
+            # evaluate regularization loss list
+            (
+                self.epo_reg_loss_tr,
+                self.epo_task_loss_tr,
+                self.epo_loss_tr,
+            ) = self.eval_r_loss()
+
         self.hyper_scheduler.set_setpoint(
             [
                 ele * self.aconf.ini_setpoint_ratio
diff --git a/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
index 9ecad287b..4dd325e7d 100644
--- a/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
+++ b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
@@ -80,10 +80,11 @@ fbopt_irm_dial_erm:
   trainer: fbopt_irm_dial
   ini_setpoint_ratio: 0.99
   force_setpoint_change_once: True
+  coeff_ma_setpoint: 0.0
   tr_with_init_mu: True
+  nb4reg_over_task_ratio: 0
   shared:
     - k_i_gain_ratio
-    - nb4reg_over_task_ratio
     - mu_init
     - mu_clip
     - exp_shoulder_clip

From e5197f3d7efe63ca918c7b9be601ce5f5f27323f Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 17 Oct 2024 12:09:43 +0200
Subject: [PATCH 271/273] logger

---
 domainlab/algos/trainers/fbopt_setpoint_ada.py | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/domainlab/algos/trainers/fbopt_setpoint_ada.py b/domainlab/algos/trainers/fbopt_setpoint_ada.py
index d243fc5e8..f0e5f6a9a 100644
--- a/domainlab/algos/trainers/fbopt_setpoint_ada.py
+++ b/domainlab/algos/trainers/fbopt_setpoint_ada.py
@@ -311,4 +311,12 @@ def update_setpoint(self):
                 {self.host.state_task_loss}"
             )
             self.host.setpoint4ell = self.host.state_task_loss
+
+        if flag1 & flag2:
+            logger = Logger.get_logger(logger_name="main_out_logger", loglevel="INFO")
+            logger.info(
+                "!!!!!!!!!In DominantAllComponent: \
+                besides each components of reg loss shrinks \
+                task loss also decreased which forms dominance!"
+            )
         return flag1 & flag2, list_pos

From dc58a5008819c31908f244948e1195a28f1a71b5 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 17 Oct 2024 12:16:36 +0200
Subject: [PATCH 272/273] setpoint ada as argument

---
 a_test_mhof_irm.sh                             | 2 +-
 domainlab/algos/trainers/args_fbopt.py         | 8 ++++++++
 domainlab/algos/trainers/fbopt_setpoint_ada.py | 4 +++-
 3 files changed, 12 insertions(+), 2 deletions(-)

diff --git a/a_test_mhof_irm.sh b/a_test_mhof_irm.sh
index df138e487..3cf1ae7ed 100644
--- a/a_test_mhof_irm.sh
+++ b/a_test_mhof_irm.sh
@@ -1 +1 @@
-python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=fbopt_irm_dial --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500 --epos_min=400 --exp_shoulder_clip=1 --mu_clip=100 --ini_setpoint_ratio=0.9 --nb4reg_over_task_ratio=0 --tr_with_init_mu --coeff_ma_setpoint=0.0
+python main_out.py --te_d=0 --tr_d 1 2 --task=mnistcolor10 --model=erm --nname=conv_bn_pool_2 --trainer=fbopt_irm_dial --k_i_gain_ratio=0.5 --force_setpoint_change_once --epos=500 --epos_min=400 --exp_shoulder_clip=1 --mu_clip=100 --ini_setpoint_ratio=0.9 --nb4reg_over_task_ratio=0 --tr_with_init_mu --coeff_ma_setpoint=0.0 --str_setpoint_ada="SliderAnyComponent()"
diff --git a/domainlab/algos/trainers/args_fbopt.py b/domainlab/algos/trainers/args_fbopt.py
index c738d76ff..e1fa536ac 100644
--- a/domainlab/algos/trainers/args_fbopt.py
+++ b/domainlab/algos/trainers/args_fbopt.py
@@ -137,6 +137,14 @@ def add_args2parser_fbopt(parser):
         help="rewind setpoint",
     )
 
+    # this arg is only used when model is set to be "diva"
+    parser.add_argument(
+        "--str_setpoint_ada",
+        type=str,
+        default="DominateAllComponent()",
+        help="which setpoint adaptation criteria to use",
+    )
+
     # this arg is only used when model is set to be "diva"
     parser.add_argument(
         "--str_diva_multiplier_type",
diff --git a/domainlab/algos/trainers/fbopt_setpoint_ada.py b/domainlab/algos/trainers/fbopt_setpoint_ada.py
index f0e5f6a9a..e22e13a75 100644
--- a/domainlab/algos/trainers/fbopt_setpoint_ada.py
+++ b/domainlab/algos/trainers/fbopt_setpoint_ada.py
@@ -144,7 +144,9 @@ def __init__(self, state=None, args=None):
             if args is not None and args.no_setpoint_update:
                 state = FixedSetpoint()
             else:
-                state = DominateAllComponent()
+                # state = eval('DominateAllComponent()')
+                # state = DominateAllComponent()
+                state = eval(args.str_setpoint_ada)
         self.transition_to(state)
         self.flag_setpoint_rewind = args.setpoint_rewind
         self.setpoint_rewinder = SetpointRewinder(self)

From 9ddd0373832bef1e3d92d9c5e1882d560a31a5c8 Mon Sep 17 00:00:00 2001
From: smilesun <smilesun.east@gmail.com>
Date: Thu, 17 Oct 2024 12:20:26 +0200
Subject: [PATCH 273/273] yaml file search setpoint ada

---
 .../aistat_trainer_combo_dial_irm_erm_mhof_only.yaml     | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
index 4dd325e7d..f1221b2f8 100644
--- a/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
+++ b/examples/benchmark/aistat_trainer_combo_dial_irm_erm_mhof_only.yaml
@@ -74,6 +74,14 @@ Shared params:
       - 100
       - 1000
 
+  gamma_reg:
+    distribution: categorical
+    datatype: str
+    values:
+      - "SliderAnyComponent()"
+      - "SliderAllComponent()"
+      - "DominateAnyComponent()"
+
 
 fbopt_irm_dial_erm:
   model: erm
@@ -88,3 +96,4 @@ fbopt_irm_dial_erm:
     - mu_init
     - mu_clip
     - exp_shoulder_clip
+    - str_setpoint_ada