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It is defined as: sigmoid(x) = 1 / (1 + exp(-x)).

For small values (<-5), sigmoid returns a value close to zero, and for large values (>5) the result of the function gets close to 1.

Sigmoid is equivalent to a 2-element softmax, where the second element is assumed to be zero. The sigmoid function always returns a value between 0 and 1.

Usage

activation_sigmoid(x)

Arguments

x

Input tensor.

Value

A tensor, the result from applying the activation to the input tensor x.