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

TypeError – If dtype of input_x is neither float16 nor float32.
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)
>>> sigmoid = ops.Sigmoid()
>>> output = sigmoid(input_x)
>>> print(output)
[0.7310586  0.880797   0.95257413 0.98201376 0.9933072 ]