regressor.0.weight : torch.Size([16, 0]) 0
regressor.0.bias : torch.Size([16]) 16
regressor.2.weight : torch.Size([1, 16]) 16
File "H:\EXPERIMENTS\ArticlePairMatching-master\src\models\CCIG\models\se_gcn.py", line 151, in forward
out = self.regressor(x)
File "C:\Users\ediso\anaconda3\envs\articlepair\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, *kwargs)
File "C:\Users\ediso\anaconda3\envs\articlepair\lib\site-packages\torch\nn\modules\container.py", line 141, in forward
input = module(input)
File "C:\Users\ediso\anaconda3\envs\articlepair\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(input, **kwargs)
File "C:\Users\ediso\anaconda3\envs\articlepair\lib\site-packages\torch\nn\modules\linear.py", line 103, in forward
return F.linear(input, self.weight, self.bias)
File "C:\Users\ediso\anaconda3\envs\articlepair\lib\site-packages\torch\nn\functional.py", line 1848, in linear
return torch._C._nn.linear(input, weight, bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (1x5 and 0x16)
regressor.0.weight : torch.Size([16, 0]) 0 regressor.0.bias : torch.Size([16]) 16 regressor.2.weight : torch.Size([1, 16]) 16 File "H:\EXPERIMENTS\ArticlePairMatching-master\src\models\CCIG\models\se_gcn.py", line 151, in forward out = self.regressor(x) File "C:\Users\ediso\anaconda3\envs\articlepair\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl return forward_call(*input, *kwargs) File "C:\Users\ediso\anaconda3\envs\articlepair\lib\site-packages\torch\nn\modules\container.py", line 141, in forward input = module(input) File "C:\Users\ediso\anaconda3\envs\articlepair\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl return forward_call(input, **kwargs) File "C:\Users\ediso\anaconda3\envs\articlepair\lib\site-packages\torch\nn\modules\linear.py", line 103, in forward return F.linear(input, self.weight, self.bias) File "C:\Users\ediso\anaconda3\envs\articlepair\lib\site-packages\torch\nn\functional.py", line 1848, in linear return torch._C._nn.linear(input, weight, bias) RuntimeError: mat1 and mat2 shapes cannot be multiplied (1x5 and 0x16)