# tf.keras.activations.hard_sigmoid

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/keras-team/keras/tree/v2.13.1/keras/activations.py#L442-L468) |

Hard sigmoid activation function.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

\`tf.compat.v1.keras.activations.hard_sigmoid\`

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    tf.keras.activations.hard_sigmoid(
        x
    )

A faster approximation of the sigmoid activation.
Piecewise linear approximation of the sigmoid function.
Ref: 'https://en.wikipedia.org/wiki/Hard_sigmoid'

#### Example:

    a = tf.constant([-3.0, -1.0, 0.0, 1.0, 3.0], dtype = tf.float32)
    b = tf.keras.activations.hard_sigmoid(a)
    b.numpy()
    array([0. , 0.3, 0.5, 0.7, 1. ], dtype=float32)

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| ## Args ||
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| `x` | Input tensor. |

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| ## Returns ||
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| The hard sigmoid activation, defined as: <br /> - `if x < -2.5: return 0` - `if x > 2.5: return 1` - `if -2.5 <= x <= 2.5: return 0.2 * x + 0.5` ||

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