Consider an output of a convolution which returns a tensor with F filters where each filter is (W, H, C) tensor (width, height, channels).
Is there a simple way to “unpack” the channels so that there are F * C grayscale filters? In other words, converting a 4D tensor of shape (F, W, H, C) to (F*C, W, H, 1) or (F*C, W, H) respectively, such that it gets sliced among the last dimension and stacked in the first?