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Specifications and Common Mistakes

- Specifications and Common Mistakes:

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

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mindspore.nn.LogSigmoid

class mindspore.nn.LogSigmoid

Applies logsigmoid activation element-wise. The input is a Tensor with any valid shape.

Logsigmoid is defined as:

$$\text{logsigmoid}(x_i)=\log (\frac{1}{1+\exp (-x_i)}),$$

where $x_i$ is the element of the input.

LogSigmoid Activation Function Graph:

Inputs:

• x (Tensor) - The input of LogSigmoid with data type of float16 or float32. The shape is $(N,\ast )$ where $\ast$ means, any number of additional dimensions.

Outputs:

Tensor, with the same type and shape as the x.

Raises

TypeError – If dtype of x is neither float16 nor float32.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> from mindspore import Tensor, nn
>>> import numpy as np
>>> net = nn.LogSigmoid()
>>> x = Tensor(np.array([1.0, 2.0, 3.0]), mindspore.float32)
>>> output = net(x)
>>> print(output)
[-0.31326166 -0.12692806 -0.04858734]