Function divide

python/paddle/tensor/math.py:1027–1114

Divide two tensors element-wise. The equation is: .. math:: out = x / y Note: ``paddle.divide`` supports broadcasting. If you want know more about broadcasting, please refer to `Introduction to Tensor`_ . .. _Introduction to Tensor: ../../guides/beginner/tenso

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

@param_two_alias(["x", "input"], ["y", "other"])
def divide(
    x: Tensor,
    y: Tensor,
    name: str | None = None,
    *,
    rounding_mode: str | None = None,
    out: Tensor | None = None,
) -> Tensor:
    """
    Divide two tensors element-wise. The equation is:

    .. math::
        out = x / y

    Note:
        ``paddle.divide`` 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``, and ``other`` can be used as an alias for ``y``.
        For example, ``divide(input=tensor_x, other=tensor_y)`` is equivalent to ``divide(x=tensor_x, y=tensor_y)``.

    Args:
        x (Tensor): the input tensor, it's data type should be bool, bfloat16, float16, float32, float64,
            int8, int16, int32, int64, uint8, complex64, complex128.
            alias: ``input``.
        y (Tensor): the input tensor, it's data type should be bool, bfloat16, float16, float32, float64,
            int8, int16, int32, int64, uint8, complex64, complex128.
            alias: ``other``.
        rounding_mode (str|None, optional): The rounding mode. Can be None (default), "trunc" (truncate toward zero), or "floor" (round down toward negative infinity).
        out (Tensor, optional): The output tensor. Default: None.
        name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.

    Returns:
        N-D Tensor. A location into which the result is stored. If x, y have different shapes and are "broadcastable", the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape,  its shape is the same as x and y.

    Examples:

        .. code-block:: pycon

            >>> import paddle

            >>> x = paddle.to_tensor([2, 3, 4], dtype='float64')
            >>> y = paddle.to_tensor([1, 5, 2], dtype='float64')
            >>> z = paddle.divide(x, y)
            >>> print(z)
            Tensor(shape=[3], dtype=float64, place=Place(cpu), stop_gradient=True,
            [2.        , 0.60000000, 2.        ])

    """
    if rounding_mode is None:
        if in_dynamic_or_pir_mode():
            res = _C_ops.divide(x, y, out=out)
        else:
            res = _elementwise_op(LayerHelper('elementwise_div', **locals()))

        return res