mindspore.nn.Sigmoid
- class mindspore.nn.Sigmoid[source]
Sigmoid activation function.
Applies sigmoid-type activation element-wise.
Sigmoid function is defined as:
\[\text{sigmoid}(x_i) = \frac{1}{1 + \exp(-x_i)},\]where \(x_i\) is the element of the input.
The picture about Sigmoid looks like this Sigmoid.
- Inputs:
x (Tensor) - The input of Sigmoid with data type of float16 or float32. The shape is \((N,*)\) where \(*\) 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
>>> x = Tensor(np.array([-1, -2, 0, 2, 1]), mindspore.float16) >>> sigmoid = nn.Sigmoid() >>> output = sigmoid(x) >>> print(output) [0.2688 0.11914 0.5 0.881 0.7305 ]