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TensorFlow 2 version View source on GitHub


Applies the sigmoid activation function. The sigmoid function is defined as 1 divided by (1 + exp(-x)). It's curve is like an "S" and is like a smoothed version of the Heaviside (Unit Step Function) function. For small values (<-5) the sigmoid returns a value close to zero and for larger values (>5) the result of the function gets close to 1. Arguments: x: A tensor or variable.

A tensor.

Sigmoid activation function.

x Input tensor.

The sigmoid activation: (1.0 / (1.0 + exp(-x))).