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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

- Incorrect links, empty cells, or wrong formats.

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- Minor inconsistencies between the UI and descriptions.

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mindspore.nn.ELU

class mindspore.nn.ELU(alpha=1.0)

Applies the exponential linear unit function element-wise.

The activation function is defined as:

$$E_i=\{\begin{array}{ll}{x}_i,& \text{if }{x}_i\ge 0;\\ \alpha \ast (\exp (x_i)-1),& \text{otherwise.}\end{array}$$

where $x_i$ represents the element of the input and $\alpha$ represents the alpha parameter.

ELU Activation Function Graph:

Parameters

alpha (float) – The alpha value of ELU, the data type is float. Default: 1.0 . Only alpha equal to 1.0 is supported currently.

Inputs:

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

Outputs:

Tensor, with the same type and shape as the 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
>>> from mindspore import Tensor, nn
>>> import numpy as np
>>> x = Tensor(np.array([-1, -2, 0, 2, 1]), mindspore.float32)
>>> elu = nn.ELU()
>>> result = elu(x)
>>> print(result)
[-0.63212055  -0.86466473  0.  2.  1.]