Function remainder

python/paddle/tensor/math.py:1234–1294

r""" Mod two tensors element-wise. The equation is: .. math:: out = x \% y .. 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``. Note: ``paddle.remainder`` supports broadca

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

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

    .. math::

        out = x \% y

    .. 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``.

    Note:
        ``paddle.remainder`` 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

        And `mod`, `floor_mod` are all functions with the same name

    Args:
        x (Tensor): the input tensor, it's data type should be bfloat16, float16, float32, float64, int32, int64.
        y (Tensor): the input tensor, it's data type should be bfloat16, float16, float32, float64, int32, int64.
        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 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, 8, 7])
            >>> y = paddle.to_tensor([1, 5, 3, 3])
            >>> z = paddle.remainder(x, y)
            >>> print(z)
            Tensor(shape=[4], dtype=int64, place=Place(cpu), stop_gradient=True,
            [0, 3, 2, 1])

            >>> z = paddle.floor_mod(x, y)
            >>> print(z)
            Tensor(shape=[4], dtype=int64, place=Place(cpu), stop_gradient=True,
            [0, 3, 2, 1])

            >>> z = paddle.mod(x, y)
            >>> print(z)
            Tensor(shape=[4], dtype=int64, place=Place(cpu), stop_gradient=True,
            [0, 3, 2, 1])

    """
    if in_dynamic_or_pir_mode():
        if isinstance(y, (int, float)):
            y = paddle.full([], y, dtype=x.dtype)