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# ELU

public class ELU

Exponential linear unit.

The exponential linear unit (ELU) with alpha > 0 is:

x if x > 0 and alpha * (exp(x) - 1) if x < 0 .

The ELU hyperparameter alpha controls the value to which an ELU saturates for negative net inputs. ELUs diminish the vanishing gradient effect.

ELUs have negative values which pushes the mean of the activations closer to zero. Mean activations that are closer to zero enable faster learning as they bring the gradient closer to the natural gradient. ELUs saturate to a negative value when the argument gets smaller. Saturation means a small derivative which decreases the variation and the information that is propagated to the next layer.

Example Usage:

Operand<TFloat32> input = ...;
ELU<TFloat32> elu = new ELU<>(tf, 2.0f);
Operand<TFloat32> result = elu.call(input);

### Public Constructors

 (Ops tf) Creates a new ELU with alpha= ERROR(/#ALPHA_DEFAULT) . (Ops tf, double alpha) Creates a new ELU

### Public Methods

 Operand ( Operand input) Gets the calculation operation for the activation.

## Public Constructors

#### public ELU (Ops tf)

Creates a new ELU with alpha= ERROR(/#ALPHA_DEFAULT) .

##### Parameters
 tf the TensorFlow Ops

#### public ELU (Ops tf, double alpha)

Creates a new ELU

##### Parameters
 tf the TensorFlow Ops A scalar, slope of negative section. It controls the value to which an ELU saturates for negative net inputs.

## Public Methods

#### public Operand <T> call ( Operand <T> input)

Gets the calculation operation for the activation.

##### Parameters
 input the input tensor
##### Returns
• The operand for the activation
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