pflake8

algo/coral_algo.py

@@ -4,7 +4,7 @@
 from torch import nn
 
 from ..utils import utils
-from .algo_utils import get_psuedo_label_weights, get_terminal_weights
+from .algo_utils import get_psuedo_label_weights
 
 
 def get_MSE(x, y):
@@ -28,7 +28,6 @@ def fit(data, network, **kwargs):
 
     feature_extractor = network["feature_extractor"]
     task_classifier = network["task_classifier"]
-    criterion = network["criterion"]
     task_optimizer = network["task_optimizer"]
     feature_optimizer = network["feature_optimizer"]
 

algo/dann_algo.py

@@ -76,7 +76,7 @@ def fit(data, network, **kwargs):
         config["is_class_weights"],
         config["is_psuedo_weights"],
     )
-    do_plot, do_print = config["do_plot"], config["do_print"]
+    do_plot, _ = config["do_plot"], config["do_print"]
     device = config["device"]
     is_changing_lr, epoch_thr_for_changing_lr, changed_lrs = (
         config["is_changing_lr"],

networks/codats.py

@@ -5,7 +5,6 @@
 from ..algo import coral_algo, dann_algo
 from .conv1d_three_layers import Conv1dThreeLayers
 from .conv1d_two_layers import Conv1dTwoLayers
-from .mlp_decoder_one_layer import OneLayerDecoder
 from .mlp_decoder_three_layers import ThreeLayersDecoder
 
 DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")

networks/codats_fc.py

@@ -4,7 +4,6 @@
 from ..utils import utils
 from .conv1d_three_layers import Conv1dThreeLayers
 from .conv1d_two_layers import Conv1dTwoLayers
-from .mlp_decoder_one_layer import OneLayerDecoder
 from .mlp_decoder_three_layers import ThreeLayersDecoder
 
 DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")

networks/isih_DA.py

@@ -6,7 +6,6 @@
 from .conv1d_three_layers import Conv1dThreeLayers
 from .conv1d_two_layers import Conv1dTwoLayers
 from .conv2d import Conv2d
-from .mlp_decoder_one_layer import OneLayerDecoder
 from .mlp_decoder_three_layers import ThreeLayersDecoder
 
 DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")