Add config parsing test cases for non-default argument parsing tests

tests/util/config/test_learning_config.py

@@ -0,0 +1,81 @@
+import unittest
+from dataclasses import fields
+from pathlib import Path
+
+import yaml
+
+from fltk.core.distributed.orchestrator import render_template
+from fltk.util.config import DistLearningConfig, FedLearningConfig, get_safe_loader
+from fltk.util.config.definitions import Optimizations
+from fltk.util.task import FederatedArrivalTask, DistributedArrivalTask
+from fltk.util.task.config import TrainTask, ExperimentParser
+from fltk.util.task.generator.arrival_generator import Arrival
+
+TEST_FED_CONF = './configs/test/fed_non_default.json'
+TEST_DIST_CONF = './configs/test/dist_non_default.json'
+
+TEST_PARAM_CONF_FEDERATED = './experiments/test/federated_non_default.yaml'
+TEST_PARAM_CONF_DISTRIBUT = './experiments/test/data_parallel_non_default.yaml'
+
+TEST_PARSED_CONF_FED = 'experiments/test/parsing/federated_parsed.yaml'
+TEST_PARSED_CONF_DIST = 'experiments/test/parsing/data_parallel_parsed.yaml'
+
+
+class FedLearningConfigTest(unittest.TestCase):
+
+    test_dist_learn_param: DistLearningConfig = None
+
+    default = FedLearningConfig(batch_size=128,
+                                test_batch_size=128,
+                                cuda=False,
+                                scheduler_step_size=50,
+                                scheduler_gamma=0.5,
+                                min_lr=1e-10,
+                                optimizer=Optimizations.sgd)
+    def setUp(self):
+        self.learning_params = FedLearningConfig.from_yaml(Path(TEST_PARAM_CONF_FEDERATED))
+
+    def test_excluded_non_defaults(self):
+        exclude_set = {'log_level', 'num_clients', 'default_model_folder_path', 'data_path', 'rank', 'world_size', 'experiment_prefix'}
+        for field in fields(self.default):
+            if field.name not in exclude_set:
+                self.assertNotEqual(getattr(self.default, field.name), getattr(self.learning_params, field.name), msg=field.name)
+
+    def test_parsed_equals(self):
+        # TODO: Make possible to parse without experiment parser.
+        description = ExperimentParser(config_path=Path(TEST_FED_CONF)).parse()[0]
+        train_task = TrainTask(identity='test_fed',
+                  job_parameters=description.job_class_parameters,
+                  priority=description.priority,
+                  experiment_config=description.get_experiment_configuration(),
+                  replication=-1,
+                  experiment_type=description.experiment_type)
+        arrival_task = FederatedArrivalTask.build(Arrival(None, train_task, 'test_fed'), train_task.identifier, -1)
+        template = render_template(arrival_task, 'Master', -1, TEST_FED_CONF)
+
+        self.assertEquals(FedLearningConfig.from_yaml(Path(TEST_PARSED_CONF_FED)),
+                          FedLearningConfig.from_dict(yaml.load(template, Loader=get_safe_loader())))
+
+
+class DistLearningConfigTest(unittest.TestCase):
+
+    test_dist_learn_param: DistLearningConfig = None
+
+
+    def setUp(self):
+        self.learning_params = FedLearningConfig.from_yaml(Path(TEST_PARAM_CONF_DISTRIBUT))
+
+
+    def test_parsed_equals(self):
+        description = ExperimentParser(config_path=Path(TEST_DIST_CONF)).parse()[0]
+        train_task = TrainTask(identity='test_fed',
+                  job_parameters=description.job_class_parameters,
+                  priority=description.priority,
+                  experiment_config=description.get_experiment_configuration(),
+                  replication=-1,
+                  experiment_type=description.experiment_type)
+        arrival_task = DistributedArrivalTask.build(Arrival(None, train_task, 'test_fed'), train_task.identifier, -1)
+        template = render_template(arrival_task, 'Master', -1, TEST_FED_CONF)
+
+        self.assertEquals(DistLearningConfig.from_yaml(Path(TEST_PARSED_CONF_DIST)),
+                          DistLearningConfig.from_dict(yaml.load(template, Loader=get_safe_loader())))