[mlpack-git] [mlpack] Add hard tanh layer (#540)

[Marcus Edel]

The hard tanh function is sometimes preferred over the tanh function since it is computationally cheaper. It does however saturate for magnitudes of x greater than 1. The activation of the hard tanh is:

```
f(x) = max, if x > max,
f(x) = min, if x < min,
f(x) = x, otherwise.
```
It would be great, if mlpack would provide  an implementation of a ```HardTanHLayer``` that allows the specification of the min and max value.

```
HardTanHLayer(const double minValue = -1, const double maxValue = 1)
```


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Reply to this email directly or view it on GitHub:
https://github.com/mlpack/mlpack/issues/540
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