Pretrained resnet conversion AttributeError

[---------------------------------------------------------------------------]
AttributeError                            Traceback (most recent call last)
<ipython-input-4-2a0f9d424028> in <module>
      4 output_2d = model_2d(input_2d)
      5 
----> 6 model_3d = ACSConverter(model_2d)
      7 # once converted, model_3d is using ACSConv and capable of processing 3D volumes.
      8 B, C_in, D, H, W = (1, 3, 64, 64, 64)

~/miniconda3/envs/rENE/lib/python3.6/site-packages/ACSConv-0.1.0-py3.6.egg/acsconv/converters/acsconv_converter.py in __init__(self, model)
     27         """ Save the weights, convert the model to ACS counterpart, and then reload the weights """
     28         preserve_state_dict = model.state_dict()
---> 29         model = self.convert_module(model)
     30         model.load_state_dict(preserve_state_dict,strict=False) #
     31         self.model = model

~/miniconda3/envs/rENE/lib/python3.6/site-packages/ACSConv-0.1.0-py3.6.egg/acsconv/converters/base_converter.py in convert_module(self, module)
     24             if isinstance(child, nn.Conv2d):
     25                 arguments = nn.Conv2d.__init__.__code__.co_varnames[1:]
---> 26                 kwargs = {k: getattr(child, k) for k in arguments}
     27                 kwargs = self.convert_conv_kwargs(kwargs)
     28                 setattr(module, child_name, self.__class__.target_conv(**kwargs))

~/miniconda3/envs/rENE/lib/python3.6/site-packages/ACSConv-0.1.0-py3.6.egg/acsconv/converters/base_converter.py in <dictcomp>(.0)
     24             if isinstance(child, nn.Conv2d):
     25                 arguments = nn.Conv2d.__init__.__code__.co_varnames[1:]
---> 26                 kwargs = {k: getattr(child, k) for k in arguments}
     27                 kwargs = self.convert_conv_kwargs(kwargs)
     28                 setattr(module, child_name, self.__class__.target_conv(**kwargs))

~/miniconda3/envs/rENE/lib/python3.6/site-packages/torch/nn/modules/module.py in __getattr__(self, name)
    946                 return modules[name]
    947         raise AttributeError("'{}' object has no attribute '{}'".format(
--> 948             type(self).__name__, name))
    949 
    950     def __setattr__(self, name: str, value: Union[Tensor, 'Module']) -> None:

AttributeError: 'Conv2d' object has no attribute 'kernel_size_'

model_2d = resnet18(pretrained=True)

Pretrained resnet is not converted properly.

[seanywang0408]

I assume the corresponding torch version is 1.8 for torchvision 0.9. It is indeed not compatible with our current codebase. We are going to update a compatible version for torch 1.8. You could either wait for the new codebase or downgrade the torch version to 1.0.

Sorry for the trouble.

[seanywang0408]

@seanywang0408 Is it compatible with pytorch=1.4.0? My computing clusters are on CUDA=10.1, so I’m wondering if the repo’s compatible with a version of pytorch that’s compatible with CUDA 10.1. Thanks!

The repo is compatible with PyTorch 1.8 now. Welcome to try it!