Hello,
I am trying to use the framework on a custom dataset. In VAEGAN_ADNI_train, I want to resize the images to 128128128 by setting sp_size=128 instead of sp_size=64.
On running the code for training, for the line mean,logvar,code = E(real_images), I get the following exception:
RuntimeError Traceback (most recent call last)
<ipython-input-43-3a5c933a2738> in <cell line: 11>()
19 #real_array.append(real_images)
20 z_rand = Variable(torch.randn((_batch_size, latent_dim)),requires_grad=False).cuda()
---> 21 mean,logvar,code = E(real_images)
22 x_rec = G(code)
23 x_rand = G(z_rand)
5 frames
/usr/local/lib/python3.10/dist-packages/torch/nn/modules/linear.py in forward(self, input)
112
113 def forward(self, input: Tensor) -> Tensor:
--> 114 return F.linear(input, self.weight, self.bias)
115
116 def extra_repr(self) -> str:
RuntimeError: mat1 and mat2 shapes cannot be multiplied (4x262144 and 32768x2048)
What other changes do I need to make to make the framework accept images of various sizes? (64,128,142,256, etc.)
Hello,
I am trying to use the framework on a custom dataset. In VAEGAN_ADNI_train, I want to resize the images to 128128128 by setting sp_size=128 instead of sp_size=64.
On running the code for training, for the line
mean,logvar,code = E(real_images), I get the following exception:What other changes do I need to make to make the framework accept images of various sizes? (64,128,142,256, etc.)