


input = torch.randn(N, C, H, W)
      >>> # Normalize over the last three dimensions (i.e. the channel and spatial dimensions)
      >>> # as shown in the image below
      >>> layer_norm = nn.LayerNorm([C, H, W])
      >>> output = layer_norm(input)



[image]