rrelu function.
activation_rrelu( x, lower = 0.125, upper = 0.333333333333333, training = NULL, seed = NULL )
| x | A `Tensor`. Must be one of the following types: `float16`, `float32`, `float64`. |
|---|---|
| lower | `float`, lower bound for random alpha. |
| upper | `float`, upper bound for random alpha. |
| training | `bool`, indicating whether the `call` is meant for training or inference. |
| seed | `int`, this sets the operation-level seed. Returns: |
A `Tensor`. Has the same type as `x`.
Computes rrelu function: `x if x > 0 else random(lower, upper) * x` or `x if x > 0 else x * (lower + upper) / 2` depending on whether training is enabled. See [Empirical Evaluation of Rectified Activations in Convolutional Network](https://arxiv.org/abs/1505.00853).
`x if x > 0 else random(lower, upper) * x` or `x if x > 0 else x * (lower + upper) / 2` depending on whether training is enabled.