mindspore.Tensor.sigmoid

Tensor.sigmoid(self) → Tensor

Computes Sigmoid of self 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 x.

Sigmoid Function Graph:

../../../_images/Sigmoid.png
Parameters

self (Tensor) – self is \(x\) in the preceding formula. Tensor of any dimension, the data type is float16, float32, float64, complex64 or complex128.

Returns

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

Raises

  • TypeError – If dtype of self is not float16, float32, float64, complex64 or complex128.

  • TypeError – If self is not a Tensor.

Supported Platforms:

Ascend GPU CPU

Examples

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