1D Zero padding
This block is used in Convolutional Neural Networks; it represents a padding operation, which means adding zeros “around” the input to get a larger tensor.
This block is typically placed before a 1D Convolutional block.
1D Convolutional blocks, return by default a smaller image than the input. The output size is given by:
\[\omicron = \bigg(\frac{i + 2p - k}{s}\bigg) + 1\]
where: o = output size, i = input size, k = filter (kernel) size, s = stride, p = padding size.
Parameters
Left padding: The amount of zero-filled elements to add to the left of the input. Default: 1
Right padding: The amount of zero-filled elements to add to the right of the input. Default: 1