Function pow

python/paddle/tensor/math.py:544–633

Compute the power of Tensor elements. The equation is: .. math:: out = x^{y} Note: ``paddle.pow`` supports broadcasting. If you want know more about broadcasting, please refer to `Introduction to Tensor`_ . .. _Introduction to Tensor: ../../guides/beginner/ten

(
    x: Tensor,
    y: float | Tensor,
    name: str | None = None,
    *,
    out: Tensor | None = None,
)

@param_two_alias(["x", "input"], ["y", "exponent"])
def pow(
    x: Tensor,
    y: float | Tensor,
    name: str | None = None,
    *,
    out: Tensor | None = None,
) -> Tensor:
    """
    Compute the power of Tensor elements. The equation is:

    .. math::
        out = x^{y}

    Note:
        ``paddle.pow`` supports broadcasting. If you want know more about broadcasting, please refer to `Introduction to Tensor`_ .

        .. _Introduction to Tensor: ../../guides/beginner/tensor_en.html#chapter5-broadcasting-of-tensor

    .. note::
        Alias Support: The parameter name ``input`` can be used as an alias for ``x``, The parameter name ``exponent`` can be used as an alias for ``y``.
        For example, ``pow(input=2, exponent=1.1)`` is equivalent to ``pow(x=2, y=1.1)``.

    Args:
        x (Tensor): An N-D Tensor, the data type is bfloat16, float16, float32, float64, int32, int64, complex64 or complex128.
        input: An alias for ``x`` , with identical behavior.
        y (float|int|Tensor): If it is an N-D Tensor, its data type should be the same as `x`.
        exponent: An alias for ``y`` , with identical behavior.
        name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
        out (Tensor, optional): The output tensor. If set, the result will be stored in this tensor. Default is None.

    Returns:
        N-D Tensor. A location into which the result is stored. Its dimension and data type are the same as `x`.

    Examples:

        .. code-block:: pycon

            >>> import paddle

            >>> x = paddle.to_tensor([1, 2, 3], dtype='float32')

            >>> # example 1: y is a float or int
            >>> res = paddle.pow(x, 2)
            >>> print(res)
            Tensor(shape=[3], dtype=float32, place=Place(cpu), stop_gradient=True,
            [1., 4., 9.])
            >>> res = paddle.pow(x, 2.5)
            >>> print(res)
            Tensor(shape=[3], dtype=float32, place=Place(cpu), stop_gradient=True,
            [1.         , 5.65685415 , 15.58845711])

            >>> # example 2: y is a Tensor
            >>> y = paddle.to_tensor([2], dtype='float32')
            >>> res = paddle.pow(x, y)
            >>> print(res)
            Tensor(shape=[3], dtype=float32, place=Place(cpu), stop_gradient=True,
            [1., 4., 9.])