From what I understand, torch.randn(layers/depth, rows, columns), which can be seen when executing: torch.randn(2, 3, 3) ==> 2 layers (3x3) matrix:
tensor([[[ 1.4838, 1.2926, 1.6147],
[ 0.7923, 0.6414, -0.2676],
[-0.1949, 0.3859, -0.6940]],
[[ 0.2454, -1.9215, -0.3078],
[ 0.8544, 0.9726, 0.0330],
[ 0.3579, 0.8247, 2.1288]]])
But what does adding an extra term in the size* parameter imply? As in: torch.randn(2, 1, 3, 3)
tensor([[[[ 0.6206, -1.3697, -0.2267],
[ 1.0511, 2.3375, -0.9598],
[-0.8148, -0.0911, -2.1211]]],
[[[ 0.0659, 1.0764, 0.6150],
[-1.7226, 0.5038, -0.9544],
[-0.6447, -0.3325, 0.2048]]]])
What did the "1" add into the Tensor created?
Each number you are introducing refers to a dimension of the matrix. It is hard for humans to visualize more than 3 dimensions, but computers are fine with it.
In this particular case, you can think about the extra dimension as something like a batch size.