Source code for mxnet.random

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# coding: utf-8
# pylint: disable=no-member, protected-access, unused-import, no-name-in-module
"""Random number interface of MXNet."""
from __future__ import absolute_import

import ctypes
from .base import _LIB, check_call
from ._ndarray_internal import _sample_uniform as uniform
from ._ndarray_internal import _sample_normal as normal
from ._ndarray_internal import _sample_gamma as gamma
from ._ndarray_internal import _sample_exponential as exponential
from ._ndarray_internal import _sample_poisson as poisson
from ._ndarray_internal import _sample_negbinomial as negative_binomial
from ._ndarray_internal import _sample_gennegbinomial as generalized_negative_binomial

[docs]def seed(seed_state): """Seeds the random number generators in MXNet. This affects the behavior of modules in MXNet that uses random number generators, like the dropout operator and `NDArray`'s random sampling operators. Parameters ---------- seed_state : int The random number seed to set to all devices. Notes ----- Random number generators in MXNet are device specific. Therefore, random numbers generated from two devices can be different even if they are seeded using the same seed. Example ------- >>> print(mx.nd.random_normal(shape=(2,2)).asnumpy()) [[ 1.36481571 -0.62203991] [-1.4962182 -0.08511394]] >>> print(mx.nd.random_normal(shape=(2,2)).asnumpy()) [[ 1.09544981 -0.20014545] [-0.20808885 0.2527658 ]] >>> >>> mx.random.seed(128) >>> print(mx.nd.random_normal(shape=(2,2)).asnumpy()) [[ 0.47400656 -0.75213492] [ 0.20251541 0.95352972]] >>> mx.random.seed(128) >>> print(mx.nd.random_normal(shape=(2,2)).asnumpy()) [[ 0.47400656 -0.75213492] [ 0.20251541 0.95352972]] """ if not isinstance(seed_state, int): raise ValueError('sd must be int') seed_state = ctypes.c_int(int(seed_state)) check_call(_LIB.MXRandomSeed(seed_state))