fix: Removed duplicate type hint

Author: frgfm

torchvision/models/densenet.py

@@ -44,35 +44,30 @@ def __init__(
         self.memory_efficient = memory_efficient
 
     def bn_function(self, inputs: List[Tensor]) -> Tensor:
-        # type: (List[Tensor]) -> Tensor
         concated_features = torch.cat(inputs, 1)
         bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
         return bottleneck_output
 
     # todo: rewrite when torchscript supports any
     def any_requires_grad(self, input: List[Tensor]) -> Tensor:
-        # type: (List[Tensor]) -> bool
         for tensor in input:
             if tensor.requires_grad:
                 return True
         return False
 
     @torch.jit.unused  # noqa: T484
     def call_checkpoint_bottleneck(self, input: List[Tensor]) -> Tensor:
-        # type: (List[Tensor]) -> Tensor
         def closure(*inputs):
             return self.bn_function(inputs)
 
         return cp.checkpoint(closure, *input)
 
     @torch.jit._overload_method  # noqa: F811
     def forward(self, input: List[Tensor]) -> Tensor:
-        # type: (List[Tensor]) -> (Tensor)
         pass
 
     @torch.jit._overload_method  # noqa: F811
     def forward(self, input: Tensor) -> Tensor:
-        # type: (Tensor) -> (Tensor)
         pass
 
     # torchscript does not yet support *args, so we overload method