Fix googlenet and inception docstring for transform_input parameter

torchvision/models/googlenet.py

@@ -287,7 +287,7 @@ def googlenet(pretrained: bool = False, progress: bool = True, **kwargs: Any) ->
         aux_logits (bool): If True, adds two auxiliary branches that can improve training.
             Default: *False* when pretrained is True otherwise *True*
         transform_input (bool): If True, preprocesses the input according to the method with which it
-            was trained on ImageNet. Default: *False*
+            was trained on ImageNet. Default: True if ``pretrained=True``, else False.
     """
     if pretrained:
         if "transform_input" not in kwargs:

torchvision/models/inception.py

@@ -422,7 +422,7 @@ def inception_v3(pretrained: bool = False, progress: bool = True, **kwargs: Any)
         aux_logits (bool): If True, add an auxiliary branch that can improve training.
             Default: *True*
         transform_input (bool): If True, preprocesses the input according to the method with which it
-            was trained on ImageNet. Default: *False*
+            was trained on ImageNet. Default: True if ``pretrained=True``, else False.
     """
     if pretrained:
         if "transform_input" not in kwargs:

torchvision/models/quantization/googlenet.py

@@ -123,7 +123,7 @@ def googlenet(
         aux_logits (bool): If True, adds two auxiliary branches that can improve training.
             Default: *False* when pretrained is True otherwise *True*
         transform_input (bool): If True, preprocesses the input according to the method with which it
-            was trained on ImageNet. Default: *False*
+            was trained on ImageNet. Default: True if ``pretrained=True``, else False.
     """
     if pretrained:
         if "transform_input" not in kwargs:

torchvision/models/quantization/inception.py

@@ -197,7 +197,7 @@ def inception_v3(
         aux_logits (bool): If True, add an auxiliary branch that can improve training.
             Default: *True*
         transform_input (bool): If True, preprocesses the input according to the method with which it
-            was trained on ImageNet. Default: *False*
+            was trained on ImageNet. Default: True if ``pretrained=True``, else False.
     """
     if pretrained:
         if "transform_input" not in kwargs: