mindspore.ops.elu

mindspore.ops.elu(input_x, alpha=1.0)

Exponential Linear Unit activation function.

Applies the exponential linear unit function element-wise. The activation function is defined as:

$$\begin{array}{r}\text{ELU}(x)=\{\begin{array}{ll}\alpha (e^x-1)& \text{if }x\le 0\\ x& \text{if }x>0\end{array}\end{array}$$

Where $x$ is the element of input Tensor input_x, $\alpha$ is param alpha, it determines the smoothness of ELU. The picture about ELU looks like this ELU .

ELU function graph:

Parameters

• input_x (Tensor) – The input of ELU is a Tensor of any dimension with data type of float16 or float32.

• alpha (float, optional) – The alpha value of ELU, the data type is float. Only support 1.0 currently. Default: 1.0 .

Returns

Tensor, has the same shape and data type as input_x.

Raises

• TypeError – If alpha is not a float.

• TypeError – If dtype of input_x is neither float16 nor float32.

• ValueError – If alpha is not equal to 1.0.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.array([[-1.0, 4.0, -8.0], [2.0, -5.0, 9.0]]), mindspore.float32)
>>> output = ops.elu(x)
>>> print(output)
[[-0.63212055  4.         -0.99966455]
 [ 2.         -0.99326205  9.        ]]