Collectives™ on Stack Overflow

Find centralized, trusted content and collaborate around the technologies you use most.

Teams

Q&A for work

Connect and share knowledge within a single location that is structured and easy to search.

RuntimeError: Given groups=1, weight of size [64, 3, 7, 7], expected input[3, 1, 224, 224] to have 3 channels, but got 1 channels instead

    model_ft.eval()
    test_data, test_target = image_datasets['train'][idx]
    test_data = test_data.cuda()
    #test_target = test_target.cuda()
    test_target = torch.tensor(test_target)
    test_target = test_target.cuda()
    test_data.unsqueeze_(1)
    test_target.unsqueeze_(0)
    print(test_data.shape)
    output = model_ft(test_data)
I get the following error:
Traceback (most recent call last):
  File "test_loocv.py", line 245, in <module>
    output = model_ft(test_data)
  File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
    result = self.forward(*input, **kwargs)
  File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torchvision-0.2.1-py3.6.egg/torchvision/models/resnet.py", line 139, in forward
  File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in __call__
    result = self.forward(*input, **kwargs)
  File "/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 301, in forward
    self.padding, self.dilation, self.groups)
RuntimeError: Given groups=1, weight of size [64, 3, 7, 7], expected input[3, 1, 224, 224] to have 3 channels, but got 1 channels instead
Also, test_data has the shape: torch.Size([3, 1, 224, 224]).
How should I fix this?
test_data, test_target = image_datasets['train'][idx]
test_data = test_data.cuda()
test_target = torch.tensor(test_target)
test_target = test_target.cuda()
test_data.unsqueeze_(0)
test_target.unsqueeze_(0)
output = model_ft(test_data)
I had to change test_data.unsqueeze_(1) to test_data.unsqueeze_(0)
        
Thanks for contributing an answer to Stack Overflow!
Please be sure to answer the question. Provide details and share your research!
But avoid …
Asking for help, clarification, or responding to other answers.
Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.