Error handling and minor bug fixes in CSKD (#100)

* pairwise sampler added and csdk updated

* links added in init

* Finalised and logs added

* CSKD added with tests

* Docs added

* Testing internal kdloss

* Adding docstrings and paper summary in tutorial

* Minor correction in docs

* Error handling for non-none teacher added

* cskd reformatted

KD_Lib/KD/vision/CSKD/cskd.py

@@ -11,14 +11,14 @@
 
 class CSKD(BaseClass):
     """
-    Implementation of assisted Knowledge distillation from the paper "Improved Knowledge
-    Distillation via Teacher Assistant" https://arxiv.org/pdf/1902.03393.pdf
+    Implementation of "Regularizing Class-wise Predictions via Self-knowledge Distillation"
+     https://arxiv.org/pdf/2003.13964.pdf
 
-    :param teacher_model (torch.nn.Module): Teacher model
+    :param teacher_model (torch.nn.Module): Teacher model -> Should be None
     :param student_model (torch.nn.Module): Student model
     :param train_loader (torch.utils.data.DataLoader): Dataloader for training
     :param val_loader (torch.utils.data.DataLoader): Dataloader for validation/testing
-    :param optimizer_teacher (torch.optim.*): Optimizer used for training teacher
+    :param optimizer_teacher (torch.optim.*): Optimizer used for training teacher -> Should be None
     :param optimizer_student (torch.optim.*): Optimizer used for training student
     :param loss_fn (torch.nn.Module):  Calculates loss during distillation
     :param temp (float): Temperature parameter for distillation
@@ -60,6 +60,11 @@ def __init__(
             logdir,
         )
         self.lamda = lamda
+        if teacher_model is not None or optimizer_teacher is not None:
+            print(
+                "Error!!! Teacher model and Teacher optimizer should be None for self-distillation, please refer to the documentation."
+            )
+        assert teacher_model == None
 
     def calculate_kd_loss(self, y_pred_pair_1, y_pred_pair_2):
         """