Hello, I’m currently trying to follow a machine learning pipeline described by a paper. Essentially, I need to create an input matrix which is shaped N x KSDT sized. The paper describes this as: “Here k, ks, kd, and ksd are labels and not indices, and all terms are understood to be matrices of the same N x KSQT size, so e.g. Xk is not an N x K sized matrix, but the full-size N x KSQT matrix with N x k unique values replicated KSQ times”.

Right now, I have three following np.arrays:

bias_block: (348, 2, 151), bias_contrast: (348, 5, 151), and bias_decision: (348, 2, 151).

My understanding is that in order to combine these three arrays, I would need a final size of (348, 20, 20, 20, 151). However, I’m really struggling on how to combine these arrays. Could someone please help with this, thanks a lot.