Pytorch模型权重类型转换

Question

我正在尝试对从文件加载的 FlowNet2-C 模型进行推断。但是，我遇到了一些数据类型问题。我该如何解决？

• Source code
• FlowNet2-C pre-trained model

$ python main.py

Initializing Datasets
  [0.000s] Loading checkpoint '/notebooks/data/model/FlowNet2-C_checkpoint.pth.tar'
  [1.293s] Loaded checkpoint '/notebooks/data/model/FlowNet2-C_checkpoint.pth.tar' (at epoch 0)
(1L, 6L, 384L, 512L)
<class 'torch.autograd.variable.Variable'>
  [1.642s] Operation failed


Traceback (most recent call last):
  File "main.py", line 102, in <module>
    main()
  File "main.py", line 98, in main
    summary(input_size, model)
  File "main.py", line 61, in summary
    model(x)
  File "/usr/local/lib/python2.7/dist-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/notebooks/data/vinet/FlowNetC.py", line 75, in forward
    out_conv1a = self.conv1(x1)
  File "/usr/local/lib/python2.7/dist-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/torch/nn/modules/container.py", line 67, in forward
    input = module(input)
  File "/usr/local/lib/python2.7/dist-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/torch/nn/modules/conv.py", line 282, in forward
    self.padding, self.dilation, self.groups)
  File "/usr/local/lib/python2.7/dist-packages/torch/nn/functional.py", line 90, in conv2d
    return f(input, weight, bias)
RuntimeError: Input type (CUDAFloatTensor) and weight type (CPUFloatTensor) should be the same

Answer 1

可能是因为您的模型 和模型的输入x 具有不同的数据类型。似乎模型参数已移至 GPU，但您的输入 x 在 GPU 上。

您可以尝试在第 94 行之后使用 model.cuda()，这会将模型放到 GPU 上。然后错误应该消失。