def tril_indices_from(arr,k=0):
    if not arr.ndim==2 and arr.shape[0] == arr.shape[1]:
        raise ValueError("input array must be 2-d and square")
    return tril_indices(arr.shape[0],k)
Initialize affine layer's weights and biases like torch's linear     default behaviour, called by _init_affine_weights
dataset/ETHPy150Open nipy/nitime/nitime/index_utils.py/tril_indices_from--crossover with--dataset/ETHPy150Open dnlcrl/PyFunt/pyfunt/layers/init.py/init_affine_wb_th