我正在尝试modify an inference code的pruned SqueezeNet network
但是，我遇到了以下错误。任何人都可以评论如何解决此cpu / gpu后端错误？
[kevin@linux SqueezeNet-Pruning]$ python predict.py --image “3_100.jpg” --model “model_prunned” --num_class “2”
prediction in progress
Traceback (most recent call last):
File “predict.py”, line 63, in
prediction = predict_image(imagepath)
File “predict.py”, line 47, in predict_image
output = model(input)
File “/usr/lib/python3.7/site-packages/torch/nn/modules/module.py”, line 477, in call
result = self.forward(*input, **kwargs)
File “/home/kevin/Documents/Grive/Personal/Coursera/Machine_Learning/pruning/Pruning-CNN/SqueezeNet-Pruning/finetune.py”, line 39, in forward
x = self.features(x)
File “/usr/lib/python3.7/site-packages/torch/nn/modules/module.py”, line 477, in call
result = self.forward(*input, **kwargs)
File “/usr/lib/python3.7/site-packages/torch/nn/modules/container.py”, line 92, in forward
input = module(input)
File “/usr/lib/python3.7/site-packages/torch/nn/modules/module.py”, line 477, in call
result = self.forward(*input, **kwargs)
File “/usr/lib/python3.7/site-packages/torch/nn/modules/conv.py”, line 313, in forward
self.padding, self.dilation, self.groups)
RuntimeError: Expected object of backend CPU but got backend CUDA for argument #2 ‘weight’
[kevin@linux SqueezeNet-Pruning]$