RuntimeError: size mismatch, m1: [4 x 512], m2: [1024 x 512]

[Usama_Hasan]

@Tehreem

x = x.view(-1,512)

a better way to write this since it flatten the output of conv layer is

shape = torch.prod(torch.tensor(x.shape[1:])).item()
x =  x.view(-1, shape)

Also

@Tehreem

self.fc1 = nn.Linear(128, 1024, bias=False)

should be

self.fc1 = nn.Linear(Number of Flattened Features from last layer , 1024,...)

Further, read this post for better understanding.

Flatten layer of PyTorch build by sequential container

I am trying to build a cnn by sequential container of PyTorch, my problem is I cannot figure out how to flatten the layer. main = nn.Sequential() self._conv_block(main, 'conv_0', 3, 6, 5) main.add_module('max_pool_0_2_2', nn.MaxPool2d(2,2)) self._conv_block(main, 'conv_1', 6, 16, 3) main.add_module('max_pool_1_2_2', nn.MaxPool2d(2,2)) main.add_module('flatten', make_it_flatten) What should I put in the “make_it_flatten”? I tried to flatten the main but it do not work, main do not exist someth…