RuntimeError: size mismatch, m1: [64 x 640], m2: [1792 x 1792] at /opt/conda/conda-bld/pytorch_1550813258230/work/aten/src/THC/generic/THCTensorMathBlas.cu:266

[LotusWhu]

Hello, I am trying to use this with my custom dataset. And I get a mismatch of tensors while training the network.

Traceback (most recent call last):
File "train_lidar.py", line 212, in
main()
File "train_lidar.py", line 181, in main
train(args, model, ad_net, random_layer, train_loader, train_loader1, optimizer, optimizer_ad, epoch, 0, args.method)
File "train_lidar.py", line 84, in train
loss += loss_func.CDAN([feature, softmax_output], ad_net, None, None, random_layer)
File "/home/acharyad/Documents/CDAN/pytorch/loss.py", line 27, in CDAN
ad_out = ad_net(op_out.view(-1, softmax_output.size(1) * feature.size(1)))
File "/home/acharyad/anaconda2/envs/xynet/lib/python3.7/site-packages/torch/nn/modules/module.py", line 489, in call
result = self.forward(*input, **kwargs)
File "/home/acharyad/Documents/CDAN/pytorch/network.py", line 420, in forward
x = self.ad_layer1(x)
File "/home/acharyad/anaconda2/envs/xynet/lib/python3.7/site-packages/torch/nn/modules/module.py", line 489, in call
result = self.forward(*input, **kwargs)
File "/home/acharyad/anaconda2/envs/xynet/lib/python3.7/site-packages/torch/nn/modules/linear.py", line 67, in forward
return F.linear(input, self.weight, self.bias)
File "/home/acharyad/anaconda2/envs/xynet/lib/python3.7/site-packages/torch/nn/functional.py", line 1352, in linear
ret = torch.addmm(torch.jit._unwrap_optional(bias), input, weight.t())
RuntimeError: size mismatch, m1: [64 x 640], m2: [1792 x 1792] at /opt/conda/conda-bld/pytorch_1550813258230/work/aten/src/THC/generic/THCTensorMathBlas.cu:266
(xynet) acharyad@acharyad-G752VY:~/Documents/CDAN/pytorch$