tf.keras.ops.hard_sigmoid

Hard sigmoid activation function.

It is defined as:

0 if x < -2.5, 1 if x > 2.5, (0.2 * x) + 0.5 if -2.5 <= x <= 2.5.

x Input tensor.

A tensor with the same shape as x.

Example:

x = np.array([-1., 0., 1.])
x_hard_sigmoid = keras.ops.hard_sigmoid(x)
print(x_hard_sigmoid)
array([0.3, 0.5, 0.7], shape=(3,), dtype=float64)