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 layer.

1D Convolutional layers, 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

Padding: The amount of zero-filled elements to add to the left and right of the input. Default: 1

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