Mixing
RuntimeError: Given groups=1, weight of size [64, 3, 7, 7], expected input[3, 1, 224, 224] to have 3...
0
In the code below:
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?
python deep-learning pytorch tensor
asked Nov 21 '18 at 16:44
Mona JalalMona Jalal
8,24928110211
add a comment |
0
In the code below:
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?
python deep-learning pytorch tensor
asked Nov 21 '18 at 16:44
Mona JalalMona Jalal
8,24928110211
add a comment |
0
0
0
In the code below:
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?
python deep-learning pytorch tensor
asked Nov 21 '18 at 16:44
Mona JalalMona Jalal
8,24928110211
In the code below:
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?
python deep-learning pytorch tensor
python deep-learning pytorch tensor
asked Nov 21 '18 at 16:44
Mona JalalMona Jalal
8,24928110211
asked Nov 21 '18 at 16:44
Mona JalalMona Jalal
8,24928110211
asked Nov 21 '18 at 16:44
Mona JalalMona Jalal
8,24928110211
asked Nov 21 '18 at 16:44
Mona JalalMona Jalal
8,24928110211
asked Nov 21 '18 at 16:44
Mona JalalMona Jalal
8,24928110211
8,24928110211
add a comment |
add a comment |
1 Answer
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Here's the fix:
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)
answered Nov 21 '18 at 21:52
Mona JalalMona Jalal
8,24928110211
add a comment |
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1 Answer
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Here's the fix:
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)
answered Nov 21 '18 at 21:52
Mona JalalMona Jalal
8,24928110211
add a comment |
0
Here's the fix:
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)
answered Nov 21 '18 at 21:52
Mona JalalMona Jalal
8,24928110211
add a comment |
0
0
0
Here's the fix:
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)
answered Nov 21 '18 at 21:52
Mona JalalMona Jalal
8,24928110211
Here's the fix:
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)
answered Nov 21 '18 at 21:52
Mona JalalMona Jalal
8,24928110211
edited Nov 21 '18 at 22:07
answered Nov 21 '18 at 21:52
Mona JalalMona Jalal
8,24928110211
answered Nov 21 '18 at 21:52
Mona JalalMona Jalal
8,24928110211
answered Nov 21 '18 at 21:52
Mona JalalMona Jalal
8,24928110211
8,24928110211
add a comment |
add a comment |
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