Here is the full error message:
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-225-79567a9d92ae> in <module>
----> 1 cnn(images)

/Applications/anaconda3/envs/masterthesis/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
    887             result = self._slow_forward(*input, **kwargs)
    888         else:
--> 889             result = self.forward(*input, **kwargs)
    890         for hook in itertools.chain(
    891                 _global_forward_hooks.values(),

<ipython-input-222-a9d57d96c2fa> in forward(self, t)
     31         t = F.relu(t)
     32 
---> 33         t = self.fc1(t)
     34         t = F.relu(t)
     35 

/Applications/anaconda3/envs/masterthesis/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
    887             result = self._slow_forward(*input, **kwargs)
    888         else:
--> 889             result = self.forward(*input, **kwargs)
    890         for hook in itertools.chain(
    891                 _global_forward_hooks.values(),

/Applications/anaconda3/envs/masterthesis/lib/python3.8/site-packages/torch/nn/modules/linear.py in forward(self, input)
     92 
     93     def forward(self, input: Tensor) -> Tensor:
---> 94         return F.linear(input, self.weight, self.bias)
     95 
     96     def extra_repr(self) -> str:

/Applications/anaconda3/envs/masterthesis/lib/python3.8/site-packages/torch/nn/functional.py in linear(input, weight, bias)
   1751     if has_torch_function_variadic(input, weight):
   1752         return handle_torch_function(linear, (input, weight), input, weight, bias=bias)
-> 1753     return torch._C._nn.linear(input, weight, bias)
   1754 
   1755 

RuntimeError: mat1 and mat2 shapes cannot be multiplied (32x120 and 33708x120)

So the error appears when t = self.fc1(t) is called - so after I flattened the tensor.
The shape of my batch of images: (32, 3, 224, 224)