weight_init.py 文件源码

def orthogonal(size, sparsity=-1, scale=1, dtype=numpy.float32):
    sizeX = size
    sizeY = size

    if sparsity < 0:
        sparsity = sizeY
    else:
        sparsity = numpy.minimum(sizeY, sparsity)
    values = numpy.zeros((sizeX, sizeY), dtype=dtype)
    for dx in range(sizeX):
        perm = numpy.random.permutation(sizeY)
        new_vals = numpy.random.normal(loc=0, scale=scale, size=(sparsity,))
        values[dx, perm[:sparsity]] = new_vals

    u, s, v = svd(values)
    values = u * scale

    return values.astype(dtype)