hex.deeplearning

Class DeepLearningTask

java.lang.Object

jsr166y.ForkJoinTask<java.lang.Void>

jsr166y.CountedCompleter

water.H2O.H2OCountedCompleter<T>

water.DTask<T>

water.MRTask<T>

hex.FrameTask<DeepLearningTask>

hex.deeplearning.DeepLearningTask

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, java.util.concurrent.Future<java.lang.Void>, jsr166y.ForkJoinPool.ManagedBlocker, water.Freezable

public class DeepLearningTask
extends FrameTask<DeepLearningTask>

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class water.DTask

water.DTask.DKeyTask<T extends water.DTask.DKeyTask,V extends water.Keyed>, water.DTask.RemoveCall

Field Summary

Fields inherited from class hex.FrameTask

_dinfo, _jobKey, _shuffle, _useFraction

Fields inherited from class water.MRTask

_appendables, _fr, _fs, _hi, _keys, _left, _lo, _nhi, _nleft, _nrite, _nxx, _rite, _topLocal

Fields inherited from class water.DTask

_ex, _modifiesInputs

Constructor Summary

Constructors

Constructor and Description
DeepLearningTask(water.Key jobKey, DeepLearningModel.DeepLearningModelInfo input, float fraction)

Method Summary

Methods

Modifier and Type	Method and Description
protected void	chunkDone(long n) Override this to do post-chunk processing work.
protected void	chunkInit() Override this to initialize at the beginning of chunk processing.
static Neurons[]	makeNeuronsForTesting(DeepLearningModel.DeepLearningModelInfo minfo)
static Neurons[]	makeNeuronsForTraining(DeepLearningModel.DeepLearningModelInfo minfo)
DeepLearningModel.DeepLearningModelInfo	model_info()
protected void	postGlobal()
void	processRow(long seed, DataInfo.Row r) Method to process one row of the data for GLM functions.
void	reduce(DeepLearningTask other)
protected void	setupLocal()
static void	step(long seed, Neurons[] neurons, DeepLearningModel.DeepLearningModelInfo minfo, boolean training, double[] responses)

Methods inherited from class hex.FrameTask

closeLocal, dfork, dinfo, map, processRow

Methods inherited from class water.MRTask

appendables, asyncExec, asyncExec, asyncExec, block, compute2, dfork, dfork, dfork, dinvoke, doAll, doAll, doAll, doAll, doAll, doAll, doAll, doAllNodes, getResult, isReleasable, map, map, map, map, map, map, map, map, map, map, map, map, onCompletion, onExceptionalCompletion, outputFrame, outputFrame, outputFrame, outputFrame, priority, profString, setProfile

Methods inherited from class water.DTask

copyOver, getDException, hasException, logVerbose, onAck, onAckAck, setException

Methods inherited from class water.H2O.H2OCountedCompleter

clone, compute, frozenType, icer, nextThrPriority, read_impl, read, readJSON_impl, readJSON, write_impl, write, writeHTML_impl, writeHTML, writeJSON_impl, writeJSON

Methods inherited from class jsr166y.CountedCompleter

addToPendingCount, compareAndSetPendingCount, complete, exec, getCompleter, getPendingCount, getRawResult, setCompleter, setPendingCount, setRawResult, tryComplete

Methods inherited from class jsr166y.ForkJoinTask

adapt, adapt, adapt, cancel, compareAndSetForkJoinTaskTag, completeExceptionally, fork, get, get, getException, getForkJoinTaskTag, getPool, getQueuedTaskCount, getSurplusQueuedTaskCount, helpQuiesce, inForkJoinPool, invoke, invokeAll, invokeAll, invokeAll, isCancelled, isCompletedAbnormally, isCompletedNormally, isDone, join, peekNextLocalTask, pollNextLocalTask, pollTask, quietlyComplete, quietlyInvoke, quietlyJoin, reinitialize, setForkJoinTaskTag, tryUnfork

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

DeepLearningTask

public DeepLearningTask(water.Key jobKey,
                DeepLearningModel.DeepLearningModelInfo input,
                float fraction)

Method Detail

model_info

public final DeepLearningModel.DeepLearningModelInfo model_info()

setupLocal

protected void setupLocal()

Overrides:

setupLocal in class FrameTask<DeepLearningTask>

chunkInit

protected void chunkInit()

Description copied from class: FrameTask

Override this to initialize at the beginning of chunk processing.

Overrides:

chunkInit in class FrameTask<DeepLearningTask>

processRow

public final void processRow(long seed,
              DataInfo.Row r)

Description copied from class: FrameTask

Method to process one row of the data for GLM functions. Numeric and categorical values are passed separately, as is response. Categoricals are passed as absolute indexes into the expanded beta vector, 0-levels are skipped (so the number of passed categoricals will not be the same for every row). Categorical expansion/indexing: Categoricals are placed in the beginning of the beta vector. Each cat variable with n levels is expanded into n-1 independent binary variables. Indexes in cats[] will point to the appropriate coefficient in the beta vector, so e.g. assume we have 2 categorical columns both with values A,B,C, then the following rows will have following indexes: A,A - ncats = 0, we do not pass any categorical here A,B - ncats = 1, indexes = [2] B,B - ncats = 2, indexes = [0,2] and so on

Overrides:

processRow in class FrameTask<DeepLearningTask>

Parameters:

seed - - global id of this row, in [0,_adaptedFrame.numRows())

chunkDone

protected void chunkDone(long n)

Description copied from class: FrameTask

Override this to do post-chunk processing work.

Overrides:

chunkDone in class FrameTask<DeepLearningTask>

Parameters:

n - Number of processed rows

reduce

public void reduce(DeepLearningTask other)

Overrides:

reduce in class water.MRTask<DeepLearningTask>

postGlobal

protected void postGlobal()

Overrides:

postGlobal in class water.MRTask<DeepLearningTask>

makeNeuronsForTraining

public static Neurons[] makeNeuronsForTraining(DeepLearningModel.DeepLearningModelInfo minfo)

makeNeuronsForTesting

public static Neurons[] makeNeuronsForTesting(DeepLearningModel.DeepLearningModelInfo minfo)

step

public static void step(long seed,
        Neurons[] neurons,
        DeepLearningModel.DeepLearningModelInfo minfo,
        boolean training,
        double[] responses)