magnitude_pruning_l2.py

# Copy the kernel weights and get ranked indices of the
# column-wise L2 Norms
kernel_weights = np.copy(k_weights)
ind = np.argsort(np.linalg.norm(kernel_weights, axis=0))
    
# Number of indices to be set to 0
sparsity_percentage = 0.7
cutoff = int(len(ind)*sparsity_percentage)

# The indices in the 2D kernel weight matrix to be set to 0
sparse_cutoff_inds = ind[0:cutoff]
kernel_weights[:,sparse_cutoff_inds] = 0.