split:
    description: |
        Splits the input tensor into output_num of tensors along the given axis and output numbers.

        Refer to :func:`mindspore.ops.split` for more details.
    
        Args:
            axis (int): Index of the split position. Default: ``0`` .
            output_num (int): The number of output tensors. Must be positive int. Default: ``1`` .
    
        Inputs:
            - **input_x** (Tensor) - The shape of tensor is :math:`(x_0, x_1, ..., x_{R-1})`, R >= 1.
    
        Outputs:
            tuple[Tensor], the shape of each output tensor is the same, which is
            :math:`(x_0, x_1, ..., x_{axis}/{output\_num}, ..., x_{R-1})`.
            And the data type is the same as `input_x`.
    
        Supported Platforms:
            ``Ascend`` ``GPU`` ``CPU``
    
        Examples:
            >>> import mindspore
            >>> import numpy as np
            >>> from mindspore import Tensor, ops
            >>> split = ops.Split(1, 2)
            >>> x = Tensor(np.array([[1, 1, 1, 1], [2, 2, 2, 2]]), mindspore.int32)
            >>> print(x)
            [[1 1 1 1]
             [2 2 2 2]]
            >>> output = split(x)
            >>> print(output)
            (Tensor(shape=[2, 2], dtype=Int32, value=
            [[1, 1],
             [2, 2]]), Tensor(shape=[2, 2], dtype=Int32, value=
            [[1, 1],
             [2, 2]]))
            >>> split = ops.Split(1, 4)
            >>> output = split(x)
            >>> print(output)
            (Tensor(shape=[2, 1], dtype=Int32, value=
            [[1],
             [2]]), Tensor(shape=[2, 1], dtype=Int32, value=
            [[1],
             [2]]), Tensor(shape=[2, 1], dtype=Int32, value=
            [[1],
             [2]]), Tensor(shape=[2, 1], dtype=Int32, value=
            [[1],
             [2]]))