pytorch 實現 tensorflow中 conv 的“same”方式

 問題描述：

tensorflow 中的conv  padding 有 same 模式，在pytorch中 對應的實現代碼如下：

 

Here is a very simple Conv2d layer with same padding for reference. It only support square kernels and stride=1, dilation=1, groups=1.

class Conv2dSame(torch.nn.Module):
    def __init__(self, in_channels, out_channels, kernel_size, bias=True, padding_layer=torch.nn.ReflectionPad2d):
        super().__init__()
        ka = kernel_size // 2
        kb = ka - 1 if kernel_size % 2 == 0 else ka
        self.net = torch.nn.Sequential(
            padding_layer((ka,kb,ka,kb)),
            torch.nn.Conv2d(in_channels, out_channels, kernel_size, bias=bias)
        )
    def forward(self, x):
        return self.net(x)
    
c = Conv2dSame(1,3,5)
print(c(torch.rand((16,1,10,10))).shape)

# torch.Size([16, 3, 10, 10])

 

參考鏈接：https://github.com/pytorch/pytorch/issues/3867