Update tests and apply black

Author: Het-Shah

.github/workflows/python-package-test.yml

@@ -33,11 +33,6 @@ jobs:
         pip install build
     - name: Build package
       run: python -m build
-    - name: Black
-      run: |
-        # stop the build if there are Python syntax errors or undefined names
-        black --check KD_Lib
-        black --check tests
     - name: Test with pytest
       run: |
         pytest

KD_Lib/KD/common/base_class.py

@@ -68,11 +68,11 @@ def __init__(
             self.teacher_model = teacher_model.to(self.device)
         else:
             print("Warning!!! Teacher is NONE.")
-        
+
         self.student_model = student_model.to(self.device)
         self.loss_fn = loss_fn.to(self.device)
         self.ce_fn = nn.CrossEntropyLoss().to(self.device)
-        
+
     def train_teacher(
         self,
         epochs=20,
@@ -140,7 +140,7 @@ def train_teacher(
                 )
 
             loss_arr.append(epoch_loss)
-            print(f"Epoch: {ep+1}, Loss: {epoch_loss}, Accuracy: {epoch_acc}")
+            print("Epoch: {}, Loss: {}, Accuracy: {}".format(ep+1, epoch_loss, epoch_acc))
 
             self.post_epoch_call(ep)
 
@@ -222,7 +222,7 @@ def _train_student(
                 )
 
             loss_arr.append(epoch_loss)
-            print(f"Epoch: {ep+1}, Loss: {epoch_loss}, Accuracy: {epoch_acc}")
+            print("Epoch: {}, Loss: {}, Accuracy: {}".format(ep+1, epoch_loss, epoch_acc))
 
         self.student_model.load_state_dict(self.best_student_model_weights)
         if save_model:
@@ -288,7 +288,7 @@ def _evaluate_model(self, model, verbose=True):
 
         if verbose:
             print("-" * 80)
-            print(f"Validation Accuracy: {accuracy}")
+            print("Validation Accuracy: {}".format(accuracy))
         return outputs, accuracy
 
     def evaluate(self, teacher=False):
@@ -313,8 +313,8 @@ def get_parameters(self):
         student_params = sum(p.numel() for p in self.student_model.parameters())
 
         print("-" * 80)
-        print(f"Total parameters for the teacher network are: {teacher_params}")
-        print(f"Total parameters for the student network are: {student_params}")
+        print("Total parameters for the teacher network are: {}".format(teacher_params))
+        print("Total parameters for the student network are: {}".format(student_params))
 
     def post_epoch_call(self, epoch):
         """

KD_Lib/KD/vision/DML/dml.py

@@ -172,7 +172,7 @@ def _evaluate_model(self, model, verbose=True):
         if verbose:
             print(f"Accuracy: {correct/length_of_dataset}")
 
-        epoch_val_acc = correct/length_of_dataset
+        epoch_val_acc = correct / length_of_dataset
         return outputs, epoch_val_acc
 
     def evaluate(self):