updated to the latest version and this is the new error code:
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
/tmp/ipykernel_16674/3188434085.py in <module>
     21 
     22         # Train Generator: min log(1 - D(G(z))) <-> max log(D(G(z))
---> 23         output = disc(adv_ex).view(-1) #discriminator decides if advex is real or fake
     24         lossG = torch.mean(torch.log(1. - output)) #get loss for gen's desired desc pred
     25 

~/.conda/envs/mypytorch19/lib/python3.9/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

~/AdvGan9-4/models.py in forward(self, x)
     28 
     29     def forward(self, x):
---> 30         x = self.fc1(x)
     31         x = nn.ReLU()(x)
     32         x = self.fc2(x)

~/.conda/envs/mypytorch19/lib/python3.9/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

~/.conda/envs/mypytorch19/lib/python3.9/site-packages/torch/nn/modules/linear.py in forward(self, input)
     94 
     95     def forward(self, input: Tensor) -> Tensor:
---> 96         return F.linear(input, self.weight, self.bias)
     97 
     98     def extra_repr(self) -> str:

~/.conda/envs/mypytorch19/lib/python3.9/site-packages/torch/nn/functional.py in linear(input, weight, bias)
   1845     if has_torch_function_variadic(input, weight):
   1846         return handle_torch_function(linear, (input, weight), input, weight, bias=bias)
-> 1847     return torch._C._nn.linear(input, weight, bias)
   1848 
   1849 

RuntimeError: mat1 and mat2 shapes cannot be multiplied (1x25088 and 784x128)

does this mean i need to change the input dimensions?