|---| | [ View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.21.0/tensorflow/python/ops/nn_ops.py#L3667-L3699) | Compute the Leaky ReLU activation function. tf.nn.leaky_relu( features, alpha=0.2, name=None ) ### Used in the notebooks | Used in the tutorials | |---| | - [Scalable model compression](https://www.tensorflow.org/tutorials/optimization/compression) | Source: [Rectifier Nonlinearities Improve Neural Network Acoustic Models. AL Maas, AY Hannun, AY Ng - Proc. ICML, 2013](https://ai.stanford.edu/%7Eamaas/papers/relu_hybrid_icml2013_final.pdf).


| ## Args || |---|---| | `features` | A `Tensor` representing preactivation values. Must be one of the following types: `float16`, `float32`, `float64`, `int32`, `int64`. | | `alpha` | Slope of the activation function at x \< 0. | | `name` | A name for the operation (optional). |



| ## Returns || |---|---| | The activation value. ||



| ## References || |---|---| | Rectifier Nonlinearities Improve Neural Network Acoustic Models: [Maas et al., 2013](http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.693.1422) ([pdf](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.693.1422&rep=rep1&type=pdf)) ||