def _ortho_init(shape, dtype, partition_info=None):
    shape = tuple(shape)
    if (len(shape) == 2):
        flat_shape = shape
    elif (len(shape) == 4):
        flat_shape = (np.prod(shape[:(- 1)]), shape[(- 1)])
    else:
        raise NotImplementedError
    a = np.random.normal(0.0, 1.0, flat_shape)
    (u, _, v) = np.linalg.svd(a, full_matrices=False)
    q = (u if (u.shape == flat_shape) else v)
    q = q.reshape(shape)
    return (scale * q[:shape[0], :shape[1]]).astype(np.float32)
def _ortho_init(shape, dtype, partition_info=None):
    shape = tuple(shape)
    if (len(shape) == 2):
        flat_shape = shape
    elif (len(shape) == 4):
        flat_shape = (np.prod(shape[:(- 1)]), shape[(- 1)])
    else:
        raise NotImplementedError
    a = np.random.normal(0.0, 1.0, flat_shape)
    (u, _, v) = np.linalg.svd(a, full_matrices=False)
    q = (u if (u.shape == flat_shape) else v)
    q = q.reshape(shape)
    return (scale * q[:shape[0], :shape[1]]).astype(np.float32)