Remove input_shape property and set default to None. (facebookresearc…

…h#90)

Summary:
Pull Request resolved: fairinternal/ClassyVision#90

Pull Request resolved: facebookresearch#687

This does not update video models or models with custom logic.

ci/circleci: cpu_tests are failed due to formatting differences between arc lint and circleci lint. We prefer the arc lint formatting.

Reviewed By: mannatsingh

Differential Revision: D25957137

fbshipit-source-id: 6defbac19e3baddb609ed33b9fd161959eaa7dfe

classy_vision/models/classy_model.py

@@ -407,8 +407,11 @@ def execute_heads(self) -> Dict[str, torch.Tensor]:
 
     @property
     def input_shape(self):
-        """If implemented, returns expected input tensor shape"""
-        raise NotImplementedError
+        """Returns the input shape that the model can accept, excluding the batch dimension.
+
+        By default it returns (3, 224, 224).
+        """
+        return (3, 224, 224)
 
 
 class _ClassyModelAdapter(ClassyModel):

classy_vision/models/densenet.py

@@ -274,10 +274,3 @@ def forward(self, x):
         out = self.features(out)
 
         return out
-
-    @property
-    def input_shape(self):
-        if self.small_input:
-            return (3, 32, 32)
-        else:
-            return (3, 224, 224)

classy_vision/models/mlp.py

@@ -85,7 +85,3 @@ def forward(self, x):
         out = x.view(batchsize_per_replica, -1)
         out = self.mlp(out)
         return out
-
-    @property
-    def input_shape(self):
-        return (self._num_inputs,)

classy_vision/models/regnet.py

@@ -537,10 +537,6 @@ def init_weights(self):
                 m.weight.data.normal_(mean=0.0, std=0.01)
                 m.bias.data.zero_()
 
-    @property
-    def input_shape(self):
-        return (3, 224, 224)
-
 
 # Register some "classic" RegNets
 class _RegNet(RegNet):

classy_vision/models/resnext.py

@@ -434,13 +434,6 @@ def forward(self, x):
 
         return out
 
-    @property
-    def input_shape(self):
-        if self.small_input:
-            return (3, 32, 32)
-        else:
-            return (3, 224, 224)
-
     def _convert_model_state(self, state):
         """Convert model state from the old implementation to the current format.