Function mul

python/paddle/tensor/math.py:1302–1355

multiply two tensors element-wise. The equation is: .. math:: out = x * y Note: Supported shape of :attr:`x` and :attr:`y` for this operator: 1. `x.shape` == `y.shape`. 2. `x.shape` could be the continuous subsequence of `y.shape`. ``paddle.mul`

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

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

    .. math::
        out = x * y

    Note:
        Supported shape of :attr:`x` and :attr:`y` for this operator:
        1. `x.shape` == `y.shape`.
        2. `x.shape` could be the continuous subsequence of `y.shape`.
        ``paddle.mul`` supports broadcasting. If you would like to know more about broadcasting, please refer to `Introduction to Tensor`_ .

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

    Args:
        x (Tensor): the input tensor, its data type should be one of bfloat16, float16, float32, float64, int32, int64, bool, complex64, complex128.
        y (Tensor): the input tensor, its data type should be one of bfloat16, float16, float32, float64, int32, int64, bool, complex64, complex128.
        name (str|None, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.

    Keyword Args:
        out (Tensor|None, 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. If :attr:`x`, :attr:`y` have different shapes and are "broadcastable", the resulting tensor shape is the shape of :attr:`x` and :attr:`y` after broadcasting. If :attr:`x`, :attr:`y` have the same shape, its shape is the same as :attr:`x` and :attr:`y`.

    Examples:

        .. code-block:: pycon

            >>> import paddle

            >>> x = paddle.to_tensor([[1, 2], [3, 4]])
            >>> y = paddle.to_tensor([[5, 6], [7, 8]])
            >>> res = paddle.mul(x, y)
            >>> print(res)
            Tensor(shape=[2, 2], dtype=int64, place=Place(cpu), stop_gradient=True,
            [[5 , 12],
             [21, 32]])
            >>> x = paddle.to_tensor([[[1, 2, 3], [1, 2, 3]]])
            >>> y = paddle.to_tensor([2])
            >>> res = paddle.mul(x, y)
            >>> print(res)
            Tensor(shape=[1, 2, 3], dtype=int64, place=Place(cpu), stop_gradient=True,
            [[[2, 4, 6],
              [2, 4, 6]]])

    """
    if in_dynamic_or_pir_mode():
        return _C_ops.multiply(x, y, out=out)
    else:
        return _elementwise_op(LayerHelper('elementwise_mul', **locals()))


@param_two_alias(["x", "input"], ["y", "other"])