mindspore.ops.sigmoid

mindspore.ops.sigmoid(input_x)[source]

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_x.

Parameters

input_x (Tensor) – Tensor of any dimension, the data type is float16, float32, float64, complex64 or complex128.

Returns

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

Raises

TypeError – If dtype of input_x is not float16, float32, float64, complex64 or complex128.
TypeError – If input_x is not a Tensor.

Supported Platforms:: Ascend GPU CPU

Examples

>>> input_x = Tensor(np.array([1, 2, 3, 4, 5]), mindspore.float32)
>>> output = ops.sigmoid(input_x)
>>> print(output)
[0.7310586  0.880797   0.95257413 0.98201376 0.9933072 ]