LossLayer.Builder (deeplearning4j-nn 1.0.0-M2.1 API)

java.lang.Object
- org.deeplearning4j.nn.conf.layers.Layer.Builder<T>
- - org.deeplearning4j.nn.conf.layers.BaseLayer.Builder<T>
  - - org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder<T>
    - - org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder<LossLayer.Builder>
      - org.deeplearning4j.nn.conf.layers.LossLayer.Builder

Enclosing class:: LossLayer

public static class LossLayer.Builder
extends BaseOutputLayer.Builder<LossLayer.Builder>

Field Summary
- Fields inherited from class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
  lossFn
- Fields inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
  nIn, nOut
- Fields inherited from class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
  activationFn, biasInit, biasUpdater, gainInit, gradientNormalization, gradientNormalizationThreshold, iupdater, regularization, regularizationBias, weightInitFn, weightNoise
- Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer.Builder
  allParamConstraints, biasConstraints, iDropout, layerName, weightConstraints

Constructor Summary

Constructors
Constructor Description

Builder()

Builder(ILossFunction lossFunction)

Builder(LossFunctions.LossFunction lossFunction)

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`LossLayer`	`build()`
`LossLayer.Builder`	`nIn(int nIn)`	Number of inputs for the layer (usually the size of the last layer).
`LossLayer.Builder`	`nOut(int nOut)`	Number of outputs - used to set the layer size (number of units/nodes for the current layer).

Methods inherited from class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
hasBias, lossFunction, lossFunction

Methods inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
nIn, nOut, units

Methods inherited from class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
activation, activation, biasInit, biasUpdater, dist, gainInit, gradientNormalization, gradientNormalizationThreshold, l1, l1Bias, l2, l2Bias, regularization, regularizationBias, updater, updater, weightDecay, weightDecay, weightDecayBias, weightDecayBias, weightInit, weightInit, weightInit, weightNoise

Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer.Builder
constrainAllParameters, constrainBias, constrainWeights, dropOut, dropOut, name

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - Builder
```
public Builder()
```
  - Builder
```
public Builder(LossFunctions.LossFunction lossFunction)
```
    Parameters:
    
    lossFunction - Loss function for the loss layer
  - Builder
```
public Builder(ILossFunction lossFunction)
```
    Parameters:
    
    lossFunction - Loss function for the loss layer
- Method Detail
  - nIn
```
public LossLayer.Builder nIn(int nIn)
```
    Description copied from class: FeedForwardLayer.Builder
    
    Number of inputs for the layer (usually the size of the last layer).
    Note that for Convolutional layers, this is the input channels, otherwise is the previous layer size.
    
    Overrides:
    
    nIn in class FeedForwardLayer.Builder<LossLayer.Builder>
    
    Parameters:
    
    nIn - Number of inputs for the layer
  - nOut
```
public LossLayer.Builder nOut(int nOut)
```
    Description copied from class: FeedForwardLayer.Builder
    
    Number of outputs - used to set the layer size (number of units/nodes for the current layer). Note that this is equivalent to FeedForwardLayer.Builder.units(int)
    
    Overrides:
    
    nOut in class FeedForwardLayer.Builder<LossLayer.Builder>
    
    Parameters:
    
    nOut - Number of outputs / layer size
  - build
```
public LossLayer build()
```
    Specified by:
    
    build in class Layer.Builder<LossLayer.Builder>