如果没有溢出，Py2D值无法转换为uint8\u t类型

Question

我将带有dtypeof torch.uint8的torch.Tensor传递给nn.Conv2d模块，它给出了错误

RuntimeError: value cannot be converted to type uint8_t without overflow: -0.0344873

我的conv2d定义为self.conv1 = nn.Conv2d(3, 6, 5)。当我将张量传递给像self.conv1(x)这样的模块时，错误出现在我的forward方法中。张量具有形状（4,3,480,640）。我不知道如何解决这个问题。这是堆栈跟踪

Traceback (most recent call last):

  File "cnn.py", line 54, in <module>

    outputs = net(inputs)

  File "/Users/my_repos/venv_projc/lib/python3.7/site-packages/torch/nn/modules/module.py", line 532, in __call__

    result = self.forward(*input, **kwargs)

  File "cnn.py", line 24, in forward

    test = self.conv1(x)

  File "/Users/my_repos/venv_projc/lib/python3.7/site-packages/torch/nn/modules/module.py", line 532, in __call__

    result = self.forward(*input, **kwargs)

  File "/Users/my_repos/venv_projc/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 345, in forward

    return self.conv2d_forward(input, self.weight)

  File "/Users/my_repos/venv_projc/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 342, in conv2d_forward

    self.padding, self.dilation, self.groups)

RuntimeError: value cannot be converted to type uint8_t without overflow: -0.0344873

Answer 1

将张量转换为浮点数似乎可以修复它self.conv1(x.float())