module that builds max-pool conv features.

The output is concattened height of all kernel-specs which has the max value of the conv-1D across the sliding windows

builds a function which takes a sequence of input nodes and returns the sequence of convolutional features over each window

Input: model: PModel to add kernel params to inputs: seq of n input nodes kernel-spec: width, height, stride (defaults to 1) of kernel

Outputs: Lazy sequence of size (partition width stride inputs) nodes each with dimension height from kernel heights