PyTorch 错误 RuntimeError: view size is not compatible with input tensor’s size and stride (at least o

PyTorch 错误 RuntimeError: view size is not compatible with input tensor’s size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(…) instead.

flyfish
具体提示如下

Processinggender.py:212: UserWarning: This overload of cuda is deprecated:
    cuda(torch.device device, bool async, *, torch.memory_format memory_format)
Consider using one of the following signatures instead:
    cuda(torch.device device, bool non_blocking, *, torch.memory_format memory_format) (Triggered internally at  /pytorch/torch/csrc/utils/python_arg_parser.cpp:882.)
  inputs, targets = inputs.cuda(), targets.cuda(async=True)
Traceback (most recent call last):

    correct_k = correct[:k].view(-1)
RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.

    

解决方案
按照提示
correct_k = correct[:k].view(-1)
更改为
correct_k = correct[:k].contiguous().view(-1)

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本文链接:https://blog.csdn.net/flyfish1986/article/details/114410001
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原文链接:https://blog.csdn.net/flyfish1986/article/details/114410001
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RuntimeError: view size is not compatible with input tensor‘s size and stride

在运行程序中:

        def forward(self, x):
            out = self.cnn(x)
            out = out.view(out.size()[0], -1)
            return self.fc(out)

python报错:

RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.

这是因为view()需要Tensor中的元素地址是连续的,但可能出现Tensor不连续的情况,所以先用 .contiguous() 将其在内存中变成连续分布:

        out = out.contiguous().view(out.size()[0], -1)

这样就好了。

版权声明:本文为博主原创文章,遵循 CC 4.0 BY-SA 版权协议,转载请附上原文出处链接和本声明。
本文链接:https://blog.csdn.net/tiao_god/article/details/108189879
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版权声明:本文为CSDN博主「Dezeming」的原创文章,遵循CC 4.0 BY-SA版权协议,转载请附上原文出处链接及本声明。
原文链接:https://blog.csdn.net/tiao_god/article/details/108189879
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