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tf.keras.activations.sigmoid

Sigmoid activation function.

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.

Args
x Input tensor.

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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/activations/sigmoid