mindspore.nn.Sigmoid
- class mindspore.nn.Sigmoid[source]
Applies sigmoid activation function element-wise.
Sigmoid function is defined as:
\[\text{sigmoid}(x_i) = \frac{1}{1 + \exp(-x_i)},\]where \(x_i\) is the element of x.
Sigmoid Activation Function Graph:
- Inputs:
input (Tensor) - input is \(x\) in the preceding formula. Tensor of any dimension, the data type is float16, float32, float64, complex64 or complex128.
- Outputs:
Tensor, with the same type and shape as the input.
- Raises
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore >>> from mindspore import Tensor, nn >>> import numpy as np >>> input = Tensor(np.array([-1, -2, 0, 2, 1]), mindspore.float16) >>> sigmoid = nn.Sigmoid() >>> output = sigmoid(input) >>> print(output) [0.2688 0.11914 0.5 0.881 0.7305 ]