java.lang.Object
- org.deeplearning4j.nn.conf.MultiLayerConfiguration

All Implemented Interfaces:: Serializable, Cloneable

public class MultiLayerConfiguration
extends Object
implements Serializable, Cloneable

See Also:: Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type Class Description

static class MultiLayerConfiguration.Builder

Field Summary

Fields
Modifier and Type	Field	Description
`protected BackpropType`	`backpropType`
`protected CacheMode`	`cacheMode`
`protected List<NeuralNetConfiguration>`	`confs`
`protected DataType`	`dataType`
`protected int`	`epochCount`
`protected WorkspaceMode`	`inferenceWorkspaceMode`
`protected Map<Integer,InputPreProcessor>`	`inputPreProcessors`
`protected int`	`iterationCount`
`protected int`	`tbpttBackLength`
`protected int`	`tbpttFwdLength`
`protected WorkspaceMode`	`trainingWorkspaceMode`
`protected boolean`	`validateOutputLayerConfig`

Constructor Summary

Constructors
Constructor Description

MultiLayerConfiguration()

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`MultiLayerConfiguration`	`clone()`
`static MultiLayerConfiguration`	`fromJson(String json)`	Create a neural net configuration from json
`static MultiLayerConfiguration`	`fromYaml(String json)`	Create a neural net configuration from json
`NeuralNetConfiguration`	`getConf(int i)`
`int`	`getEpochCount()`
`InputPreProcessor`	`getInputPreProcess(int curr)`
`List<InputType>`	`getLayerActivationTypes(@NonNull InputType inputType)`	For the given input shape/type for the network, return a list of activation sizes for each layer in the network. i.e., list.get(i) is the output activation sizes for layer i
`NetworkMemoryReport`	`getMemoryReport(InputType inputType)`	Get a `MemoryReport` for the given MultiLayerConfiguration.
`void`	`setEpochCount(int epochCount)`
`String`	`toJson()`
`String`	`toString()`
`String`	`toYaml()`

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

- Field Detail
  - confs
```
protected List<NeuralNetConfiguration> confs
```
  - inputPreProcessors
```
protected Map<Integer,InputPreProcessor> inputPreProcessors
```
  - backpropType
```
protected BackpropType backpropType
```
  - tbpttFwdLength
```
protected int tbpttFwdLength
```
  - tbpttBackLength
```
protected int tbpttBackLength
```
  - validateOutputLayerConfig
```
protected boolean validateOutputLayerConfig
```
  - trainingWorkspaceMode
```
protected WorkspaceMode trainingWorkspaceMode
```
  - inferenceWorkspaceMode
```
protected WorkspaceMode inferenceWorkspaceMode
```
  - cacheMode
```
protected CacheMode cacheMode
```
  - dataType
```
protected DataType dataType
```
  - iterationCount
```
protected int iterationCount
```
  - epochCount
```
protected int epochCount
```
- Constructor Detail
  - MultiLayerConfiguration
```
public MultiLayerConfiguration()
```
- Method Detail
  - getEpochCount
```
public int getEpochCount()
```
  - setEpochCount
```
public void setEpochCount(int epochCount)
```
  - toYaml
```
public String toYaml()
```
    Returns:
    
    JSON representation of NN configuration
  - fromYaml
```
public static MultiLayerConfiguration fromYaml(String json)
```
    Create a neural net configuration from json
    
    Parameters:
    
    json - the neural net configuration from json
    
    Returns:
    
    MultiLayerConfiguration
  - toJson
```
public String toJson()
```
    Returns:
    
    JSON representation of NN configuration
  - fromJson
```
public static MultiLayerConfiguration fromJson(String json)
```
    Create a neural net configuration from json
    
    Parameters:
    
    json - the neural net configuration from json
    
    Returns:
    
    MultiLayerConfiguration
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - getConf
```
public NeuralNetConfiguration getConf(int i)
```
  - clone
```
public MultiLayerConfiguration clone()
```
    Overrides:
    
    clone in class Object
  - getInputPreProcess
```
public InputPreProcessor getInputPreProcess(int curr)
```
  - getMemoryReport
```
public NetworkMemoryReport getMemoryReport(InputType inputType)
```
    Get a MemoryReport for the given MultiLayerConfiguration. This is used to estimate the memory requirements for the given network configuration and input
    
    Parameters:
    
    inputType - Input types for the network
    
    Returns:
    
    Memory report for the network
  - getLayerActivationTypes
```
public List<InputType> getLayerActivationTypes(@NonNull
                                               @NonNull InputType inputType)
```
    For the given input shape/type for the network, return a list of activation sizes for each layer in the network.
    i.e., list.get(i) is the output activation sizes for layer i
    
    Parameters:
    
    inputType - Input type for the network
    
    Returns:
    
    A lits of activation types for the network, indexed by layer number

Class MultiLayerConfiguration

Nested Class Summary

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

confs

inputPreProcessors

backpropType

tbpttFwdLength

tbpttBackLength

validateOutputLayerConfig

trainingWorkspaceMode

inferenceWorkspaceMode

cacheMode

dataType

iterationCount

epochCount

Constructor Detail

MultiLayerConfiguration

Method Detail

getEpochCount

setEpochCount

toYaml

fromYaml

toJson

fromJson

toString

getConf

clone

getInputPreProcess

getMemoryReport

getLayerActivationTypes