Can't simply replace nn.Conv2d with PSConv2d

[quantumsquirrel]

Thanks to the compact characteristic of PSConv, just replace nn.Conv2d with PSConv2d. Note that there exists another hyperparameter named parts you may set in our PSConv operator.

Originally posted by @d-li14 in https://github.com/d-li14/PSConv/issues/3#issuecomment-659709139

Hi, I'm reading your paper and there comes some problems, hope you could help me figer it out! Origin Conv2d was Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False) PSConv2D are PSGConv2d( (gwconv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) (gwconv_shift): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2), groups=4, bias=False) (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) ) And I add self.weight = self.conv.weight self.bias = self.conv.bias To solve the problem " 'PSGConv2d' object has no attribute 'weight' " during building Resnet, I don't know I'm right or wrong but it works temporarily. After that ,durning training part,in PSConv2d.forward self.gwconv(x).shape: torch.Size([6, 256, 202, 274]) self.conv(x).shape torch.Size([6, 256, 202, 274]) but x_shift.shape: torch.Size([6, 256, 204, 276])

So....The size of tensor a (274) must match the size of tensor b (276) at non-singleton dimension 3

I'm using FCOS original code from tianzhi0549,thanks for the contribution, and add "psconv.py | conv_module.py | conv_ws.py " norm.py" from this respository.

Thank you for your time!

[zhangyuxuan1996]

I think there is few mistake in the code, try to change 'dilation' to 'padding'!

[zyxjtu]

I think there is few mistake in the code, try to change 'dilation' to 'padding'!

你好，请问图片中的这段核心代码怎么理解呢？方便解释一下吗？