mindspore.ops.logsigmoid
- mindspore.ops.logsigmoid(x)[source]
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:
- Parameters
x (Tensor) – The input of LogSigmoid with data type of float16 or float32. The shape is \((N,*)\) where \(*\) means, any number of additional dimensions.
- Returns
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 >>> import numpy as np >>> from mindspore import Tensor, ops >>> x = Tensor(np.array([1.0, 2.0, 3.0]), mindspore.float32) >>> output = ops.logsigmoid(x) >>> print(output) [-0.31326166 -0.12692806 -0.04858734]