softmax:
    description: |
        Applies the Softmax operation to the input tensor on the specified axis.

        Refer to :func:`mindspore.ops.softmax` for more details.
    
        Args:
            axis (Union[int, tuple], optional): The axis to perform the Softmax operation. Default: ``-1`` .
    
        Inputs:
            - **input** (Tensor) - Tensor of shape :math:`(N, *)`, where :math:`*` means, any number of
              additional dimensions. 
    
        Outputs:
            Tensor, with the same type and shape as the input.
    
        Supported Platforms:
            ``Ascend`` ``GPU`` ``CPU``
    
        Examples:
            >>> import mindspore
            >>> import numpy as np
            >>> from mindspore import Tensor, ops
            >>> input = Tensor(np.array([1, 2, 3, 4, 5]), mindspore.float32)
            >>> softmax = ops.Softmax()
            >>> output = softmax(input)
            >>> print(output)
            [0.01165623 0.03168492 0.08612854 0.23412167 0.6364086 ]