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Hard sigmoid activation function.
tf.keras.ops.hard_sigmoid(
x
)
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
.
Args | |
---|---|
x
|
Input tensor. |
Returns | |
---|---|
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)