tf.keras.activations.sigmoid
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Sigmoid.
tf.keras.activations.sigmoid(
x
)
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.
Sigmoid activation function.
Arguments |
|---|
x
|
Input tensor.
|
Returns |
|---|
The sigmoid activation: (1.0 / (1.0 + exp(-x))).
|
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Last updated 2020-10-01 UTC.
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TensorFlow 2 version
View source on GitHub