def forward(self, weight, bias, input):
# Assert we're using cudnn
for i in ([weight, bias, input]):
if i is not None and not(cudnn.is_acceptable(i)):
raise Exception('You must be using CUDNN to use _EfficientBatchNorm')
print(bias)
res = input.new(*self._output_size(input, weight))
self._cudnn_info = torch._C._cudnn_convolution_full_forward(
input, weight, bias, res,
(self.padding, self.padding),
(self.stride, self.stride),
(self.dilation, self.dilation),
self.groups, cudnn.benchmark
)
return res
TypeError: _cudnn_convolution_full_forward received an invalid combination of arguments - got (torch.cuda.FloatTensor, torch.cuda.FloatTensor, NoneType, torch.cuda.FloatTensor, tuple, tuple, tuple, int, bool), but expected (torch.cuda.RealTensor input, torch.cuda.RealTensor weight, torch.cuda.RealTensor bias, torch.cuda.RealTensor output, std::vector<int> pad, std::vector<int> stride, std::vector<int> dilation, int groups, bool benchmark, bool deterministic)
i test the code in pytorch 0.1.12.post2, it work well.
but when to pytorch 0.3 it comes the error as you show.
but i do not know how to modify the code to fit the pytorch 0.3