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keras3 (version 1.2.0)

activation_hard_sigmoid: Hard sigmoid activation function.

Description

The hard sigmoid activation is defined as:

  • 0 if if x <= -3

  • 1 if x >= 3

  • (x/6) + 0.5 if -3 < x < 3

It's a faster, piecewise linear approximation of the sigmoid activation.

Usage

activation_hard_sigmoid(x)

Value

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

Arguments

x

Input tensor.

See Also

Other activations:
activation_elu()
activation_exponential()
activation_gelu()
activation_leaky_relu()
activation_linear()
activation_log_softmax()
activation_mish()
activation_relu()
activation_relu6()
activation_selu()
activation_sigmoid()
activation_silu()
activation_softmax()
activation_softplus()
activation_softsign()
activation_tanh()