celu:
    description: |
        celu activation function, computes celu (Continuously differentiable exponential
        linear units) of input tensors element-wise. The formula is defined as follows:
    
        .. math::
        
            \text{CeLU}(x) = \max(0,x) + \min(0, \alpha * (\exp(x/\alpha) - 1))
    
        For more details, please refer to `celu <https://arxiv.org/abs/1704.07483>`_.
    
        .. warning::
            This is an experimental API that is subject to change or deletion.
        
        CELU Activation Function Graph:
        
        .. image:: ../images/CELU.png
            :align: center
    
        Args:
            x (Tensor): The input of celu with data type of float16 or float32.
            alpha (float, optional): The :math:`\alpha` value for the Celu formulation. Default: 1.0
    
        Returns:
            Tensor, has the same data type and shape as the input.
    
        Raises:
            TypeError: If `alpha` is not a float.
            TypeError: If `x` is not a Tensor.
            TypeError: If dtype of `x` is neither float16 nor float32.
            ValueError: If `alpha` has the value of 0.
    
        Supported Platforms:
            ``Ascend`` ``GPU`` ``CPU``
    
        Examples:
            >>> import mindspore
            >>> import numpy as np
            >>> from mindspore import Tensor, ops
            >>> x = Tensor(np.array([-2.0, -1.0, 1.0, 2.0]), mindspore.float32)
            >>> output = ops.celu(x, alpha=1.0)
            >>> print(output)
            [-0.86466473 -0.63212055  1.          2.        ]