Method normal

imperative/python/megengine/random/rng.py:345–374

r"""Random variable with Gaussian distribution :math:`N(\mu, \sigma)`. Args: mean(float): the mean or expectation of the distribution. Default: 0. std(float): the standard deviation of the distribution (variance = :math:`\sigma ^ 2`). Default: 1.

(
        self, mean: float = 0, std: float = 1, size: Optional[Iterable[int]] = None
    )

        )

    def normal(
        self, mean: float = 0, std: float = 1, size: Optional[Iterable[int]] = None
    ):
        r"""Random variable with Gaussian distribution :math:`N(\mu, \sigma)`.

        Args:
            mean(float): the mean or expectation of the distribution. Default: 0.
            std(float): the standard deviation of the distribution (variance = :math:`\sigma ^ 2`).
                Default: 1.
            size(Optional[Iterable[int]]): the size of output tensor. Default: None.

        Returns:
            Return type: tensor. The random variable with Gaussian distribution.

        Examples:
            >>> import megengine.random as rand
            >>> x = rand.normal(mean=0, std=1, size=(2, 2))
            >>> x.numpy()   # doctest: +SKIP
            array([[ 1.5534291 , -0.28356555],
                   [ 2.2230418 , -0.92425716]], dtype=float32)
        """
        _seed = self._seed() if callable(self._seed) else self._seed
        return _normal(
            mean=mean,
            std=std,
            size=size,
            seed=_seed,
            device=self._device,
            handle=self._handle,
        )

    def gamma(
        self,