# tf.keras.activations.relu

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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#L283-L323) |

Applies the rectified linear unit 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.relu\`

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    tf.keras.activations.relu(
        x, alpha=0.0, max_value=None, threshold=0.0
    )

With default values, this returns the standard ReLU activation:
`max(x, 0)`, the element-wise maximum of 0 and the input tensor.

Modifying default parameters allows you to use non-zero thresholds,
change the max value of the activation,
and to use a non-zero multiple of the input for values below the threshold.

#### Example:

    foo = tf.constant([-10, -5, 0.0, 5, 10], dtype = tf.float32)
    tf.keras.activations.relu(foo).numpy()
    array([ 0.,  0.,  0.,  5., 10.], dtype=float32)
    tf.keras.activations.relu(foo, alpha=0.5).numpy()
    array([-5. , -2.5,  0. ,  5. , 10. ], dtype=float32)
    tf.keras.activations.relu(foo, max_value=5.).numpy()
    array([0., 0., 0., 5., 5.], dtype=float32)
    tf.keras.activations.relu(foo, threshold=5.).numpy()
    array([-0., -0.,  0.,  0., 10.], dtype=float32)

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| ## Args ||
|---|---|
| `x` | Input `tensor` or `variable`. |
| `alpha` | A `float` that governs the slope for values lower than the threshold. |
| `max_value` | A `float` that sets the saturation threshold (the largest value the function will return). |
| `threshold` | A `float` giving the threshold value of the activation function below which values will be damped or set to zero. |

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| ## Returns ||
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| A `Tensor` representing the input tensor, transformed by the relu activation function. Tensor will be of the same shape and dtype of input `x`. ||

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