mindspore.ops.Sigmoid
- class mindspore.ops.Sigmoid[source]
Sigmoid activation function.
Computes Sigmoid of input element-wise. The Sigmoid function is defined as:
\[\text{sigmoid}(x_i) = \frac{1}{1 + \exp(-x_i)}\]where \(x_i\) is an element of the input Tensor.
- Inputs:
input_x (Tensor) - Tensor of shape \((N, *)\), where \(*\) means, any number of additional dimensions, with float16 or float32 data type.
- Outputs:
Tensor, with the same type and shape as the input_x.
- Raises
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> input_x = Tensor(np.array([1, 2, 3, 4, 5]), mindspore.float32) >>> sigmoid = ops.Sigmoid() >>> output = sigmoid(input_x) >>> print(output) [0.7310586 0.880797 0.95257413 0.98201376 0.9933072 ]