[CUDA/CPU ERROR] when I trained on my data, I found this error:

[Observerspy]

RuntimeError: Caught RuntimeError in replica 0 on device 0.
Original Traceback (most recent call last):
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 60, in _worker
output = module(*input, **kwargs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/weiqiang/cancer/code/models/efficientdet.py", line 130, in forward
P1, P2, P3, P4, P5, P6, P7 = self.efficientnet(inputs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/efficientnet_pytorch/model.py", line 204, in forward
P1, P2, P3, P4, P5, P6, P7 = self.extract_features(inputs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/efficientnet_pytorch/model.py", line 190, in extract_features
x = MBConvBlock(block_args, self._global_params)(x, drop_connect_rate = drop_connect_rate)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/efficientnet_pytorch/model.py", line 78, in forward
x = self._swish(self._bn1(self._depthwise_conv(x)))
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/efficientnet_pytorch/utils.py", line 144, in forward
x = F.conv2d(x, self.weight, self.bias, self.stride, self.padding, self.dilation, self.groups)
RuntimeError: Expected object of backend CUDA but got backend CPU for argument #2 'weight'

[dhananjaisharma10]

RuntimeError: Caught RuntimeError in replica 0 on device 0.
Original Traceback (most recent call last):
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 60, in _worker
output = module(*input, **kwargs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/weiqiang/cancer/code/models/efficientdet.py", line 130, in forward
P1, P2, P3, P4, P5, P6, P7 = self.efficientnet(inputs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/efficientnet_pytorch/model.py", line 204, in forward
P1, P2, P3, P4, P5, P6, P7 = self.extract_features(inputs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/efficientnet_pytorch/model.py", line 190, in extract_features
x = MBConvBlock(block_args, self._global_params)(x, drop_connect_rate = drop_connect_rate)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/efficientnet_pytorch/model.py", line 78, in forward
x = self._swish(self._bn1(self._depthwise_conv(x)))
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/weiqiang/anaconda3/lib/python3.7/site-packages/efficientnet_pytorch/utils.py", line 144, in forward
x = F.conv2d(x, self.weight, self.bias, self.stride, self.padding, self.dilation, self.groups)
RuntimeError: Expected object of backend CUDA but got backend CPU for argument #2 'weight'

Hi! How did you solve this error? I realize that it's because of the new MBConvBlocks being used in the extract features function. In my opinion, it's bad coding as the originally declared self._blocks Module list is not even being used and the newly declared ones do not have their weights on the GPU.

[Observerspy]

@dhananjaisharma10 Infact, I just add
if torch.cuda.is_available(): torch.set_default_tensor_type('torch.cuda.FloatTensor')
in my own train.py.