Method uniform

imperative/python/megengine/random/rng.py:315–343

r"""Random variable with uniform distribution :math:`U(low, high)`. Args: low(float): lower range. Default: 0. high(float): upper range. Default: 1. size(Optional[Iterable[int]]): the size of output tensor. Default: None. Returns: Ret

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

            self._device = None

    def uniform(
        self, low: float = 0, high: float = 1, size: Optional[Iterable[int]] = None
    ):
        r"""Random variable with uniform distribution :math:`U(low, high)`.

        Args:
            low(float): lower range. Default: 0.
            high(float): upper range. Default: 1.
            size(Optional[Iterable[int]]): the size of output tensor. Default: None.

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

        Examples:
            >>> import megengine.random as rand
            >>> x = rand.uniform(size=(2, 2))
            >>> x.numpy()   # doctest: +SKIP
            array([[0.28603864, 0.3156649 ],
                   [0.42066026, 0.9805052 ]], dtype=float32)
        """
        _seed = self._seed() if callable(self._seed) else self._seed
        return _uniform(
            low=low,
            high=high,
            size=size,
            seed=_seed,
            device=self._device,
            handle=self._handle,
        )

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