https://github.com/Microsoft/CNTK
Tip revision: 1aefd22f8abd788ac79f7958d75e4d46a533123f authored by Mark Hillebrand on 22 January 2016, 14:46:46 UTC
Change default targets for build-and-test
Change default targets for build-and-test
Tip revision: 1aefd22
ComputationNetworkBuilder.cpp
//
// Copyright (c) Microsoft. All rights reserved.
// Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
//
// ComputationNetworkBuilder -- helper class for constructing ComputationNetworks and ComputationNodes from C++ (internal and external)
//
#define _CRT_SECURE_NO_WARNINGS // "secure" CRT not available on all platforms --add this at the top of all CPP files that give "function or variable may be unsafe" warnings
#include "Basics.h"
#include "ComputationNetworkBuilder.h"
#include "ComputationNode.h"
#include "InputAndParamNodes.h"
#include "LinearAlgebraNodes.h"
#include "NonlinearityNodes.h"
#include "ConvolutionalNodes.h"
#include "RecurrentNodes.h"
#include "ReshapingNodes.h"
#include "TrainingCriterionNodes.h"
#include "CompositeComputationNodes.h"
#include "EvaluationCriterionNodes.h"
#include "EsotericNodes.h"
#include <string>
namespace Microsoft { namespace MSR { namespace CNTK {
using namespace std;
// create a new node of a type given as a string, with var args so that this can be used at multiple places
template <class ElemType, class... _Types>
static shared_ptr<ComputationNode<ElemType>> CreateStandardNode(const std::wstring& nodeType, _Types&&... _Args)
{
// please keep this table sorted
if (nodeType == OperationNameOf(CRFNode))
return New<CRFNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(ClassBasedCrossEntropyWithSoftmaxNode))
return New<ClassBasedCrossEntropyWithSoftmaxNode<ElemType>>(forward<_Types>(_Args)...);
#ifdef ENABLE_BROADCASTING_ELEMENTTIMES
else if (nodeType == L"ColumnElementTimes")
return New<ElementTimesNode<ElemType>>(forward<_Types>(_Args)...);
#else
else if (nodeType == OperationNameOf(ColumnElementTimesNode))
return New<ColumnElementTimesNode<ElemType>>(forward<_Types>(_Args)...);
#endif
else if (nodeType == OperationNameOf(CosDistanceNode))
return New<CosDistanceNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(CosDistanceWithNegativeSamplesNode))
return New<CosDistanceWithNegativeSamplesNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(CosineNode))
return New<CosineNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(CrossEntropyNode))
return New<CrossEntropyNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(CrossEntropyWithSoftmaxNode))
return New<CrossEntropyWithSoftmaxNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(SequenceWithSoftmaxNode))
return New<SequenceWithSoftmaxNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(DiagonalNode))
return New<DiagonalNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(DiagTimesNode))
return New<DiagTimesNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(DropoutNode))
return New<DropoutNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(DummyCriterionNode))
return New<DummyCriterionNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(ElementTimesNode))
return New<ElementTimesNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(ErrorPredictionNode))
return New<ErrorPredictionNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(ExpNode))
return New<ExpNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(FutureValueNode))
return New<FutureValueNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(GMMLogLikelihoodNode))
return New<GMMLogLikelihoodNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(HardmaxNode))
return New<HardmaxNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(InvStdDevNode))
return New<InvStdDevNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(KhatriRaoProductNode))
return New<KhatriRaoProductNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(LSTMNode))
return New<LSTMNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(LogNode))
return New<LogNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(LogSoftmaxNode))
return New<LogSoftmaxNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(LookupTableNode))
return New<LookupTableNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(MatrixL1RegNode))
return New<MatrixL1RegNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(MatrixL2RegNode))
return New<MatrixL2RegNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(MeanNode))
return New<MeanNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(MinusNode))
return New<MinusNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(NegateNode))
return New<NegateNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(NoiseContrastiveEstimationNode))
return New<NoiseContrastiveEstimationNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(PairNetworkNode))
return New<PairNetworkNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(ParallelNode))
return New<ParallelNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(PastValueNode))
return New<PastValueNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(PerDimMeanVarNormalizationNode))
return New<PerDimMeanVarNormalizationNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(PerDimMeanVarDeNormalizationNode))
return New<PerDimMeanVarDeNormalizationNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(PlusNode))
return New<PlusNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(ReconcileMBLayoutNode))
return New<ReconcileMBLayoutNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(RectifiedLinearNode))
return New<RectifiedLinearNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(ReshapeNode))
return New<ReshapeNode<ElemType>>(forward<_Types>(_Args)...);
#ifdef ENABLE_BROADCASTING_ELEMENTTIMES
else if (nodeType == L"RowElementTimes")
return New<ElementTimesNode<ElemType>>(forward<_Types>(_Args)...);
#else
else if (nodeType == OperationNameOf(RowElementTimesNode))
return New<RowElementTimesNode<ElemType>>(forward<_Types>(_Args)...);
#endif
else if (nodeType == OperationNameOf(RowRepeatNode))
return New<RowRepeatNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(RowSliceNode))
return New<RowSliceNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(RowStackNode))
return New<RowStackNode<ElemType>>(forward<_Types>(_Args)...);
#ifdef ENABLE_BROADCASTING_ELEMENTTIMES
else if (nodeType == L"Scale")
return New<ElementTimesNode<ElemType>>(forward<_Types>(_Args)...);
#else
else if (nodeType == OperationNameOf(ScaleNode))
return New<ScaleNode<ElemType>>(forward<_Types>(_Args)...);
#endif
else if (nodeType == OperationNameOf(SequenceDecoderNode))
return New<SequenceDecoderNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(ShiftNode))
return New<ShiftNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(SigmoidNode))
return New<SigmoidNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(SoftmaxNode))
return New<SoftmaxNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(SquareErrorNode))
return New<SquareErrorNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(LogisticNode))
return New<LogisticNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(StrideTimesNode))
return New<StrideTimesNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(SumColumnElementsNode))
return New<SumColumnElementsNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(SumElementsNode))
return New<SumElementsNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(TanhNode))
return New<TanhNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(TimeReverseNode))
return New<TimeReverseNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(TimesNode))
return New<TimesNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(TransposeNode))
return New<TransposeNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(TransposeTimesNode))
return New<TransposeTimesNode<ElemType>>(forward<_Types>(_Args)...);
// old names we also support
else if (nodeType == L"Delay")
return New<PastValueNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == L"PerDimMeanVarNormalizationNode")
return New<PerDimMeanVarNormalizationNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == L"PerDimMeanVarNormalizationNode")
return New<PerDimMeanVarNormalizationNode<ElemType>>(forward<_Types>(_Args)...);
#if 1
else if (nodeType == OperationNameOf(DeprecatedReshapeNode))
return New<DeprecatedReshapeNode<ElemType>>(forward<_Types>(_Args)...);
#endif
else
InvalidArgument("Attempted to instantiate undefined operation %ls.", nodeType.c_str());
}
// create a new node of a type given as a string, with var args so that this can be used at multiple places
// This function is used for loading, while the above is used for creating standard-type networks.
template <class ElemType, class... _Types>
static shared_ptr<ComputationNode<ElemType>> CreateNode(const std::wstring& nodeType, _Types&&... _Args)
{
// check more types
if (nodeType == OperationNameOf(AveragePoolingNode))
return New<AveragePoolingNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(BatchNormalizationNode))
return New<BatchNormalizationNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(ConvolutionNode))
return New<ConvolutionNode<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(SparseInputValue))
return New<SparseInputValue<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(InputValue))
return New<InputValue<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(LearnableParameter))
return New<LearnableParameter<ElemType>>(forward<_Types>(_Args)...);
else if (nodeType == OperationNameOf(MaxPoolingNode))
return New<MaxPoolingNode<ElemType>>(forward<_Types>(_Args)...);
//else if (nodeType == OperationNameOf(SparseLearnableParameter)) return New<SparseLearnableParameter<ElemType>>(forward<_Types>(_Args)...);
else
return CreateStandardNode<ElemType>(nodeType, forward<_Types>(_Args)...);
}
// this function is called from SimpleNetworkBuilder and old NDL
template <class ElemType>
/*static*/ shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::NewStandardNode(const std::wstring& nodeType, DEVICEID_TYPE deviceId, const wstring& name)
{
return CreateStandardNode<ElemType>(nodeType, deviceId, name);
}
// this function is used when loading from file
template <class ElemType>
/*static*/ shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::NewNode(const std::wstring& nodeType, DEVICEID_TYPE deviceId, const wstring& name)
{
return CreateNode<ElemType>(nodeType, deviceId, name);
}
shared_ptr<ComputationNodeBase> NewComputationNodeFromConfig(const Microsoft::MSR::ScriptableObjects::IConfigRecordPtr configp)
{
wstring precision = configp->Get(L"precision"); // dispatch on ElemType
wstring operationName = configp->Get(L"operation");
ComputationNodeBasePtr node;
if (precision == L"float")
node = CreateNode<float>(operationName, configp);
else if (precision == L"double")
node = CreateNode<double>(operationName, configp);
else
RuntimeError("NewStandardNode: Invalid value '%ls' for 'precision' parameter. Must be 'float' or 'double'.", precision.c_str());
// add a tag
// Tags are used to declare special node types tp ComputationNetwork.
const auto nodeWithTag = dynamic_pointer_cast<ScriptableObjects::WithTag>(node);
if (nodeWithTag)
nodeWithTag->SetTag(configp->Get(L"tag"));
return node;
}
// -----------------------------------------------------------------------
// node creation
// -----------------------------------------------------------------------
// The following functions create nodes and add them to the net, but don't attach inputs (some don't have inputs).
// There are special versions for nodes with custom constructors, and a catch-all, CreateComputationNode(), for all others.
// TODO: Do we really need these? Folks who want to use C++ can instead say net->AddNodeToNet(New<>(...)), which is not that different.
// TODO: separate into nodes that have inputs and those that duplicate functions with input adding except just not adding inputs. Clear?
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateLearnableParameter(const std::wstring& paramName, const size_t rows, const size_t cols)
{
// TODO: in SimpleNetworkBuilder, this is very often followed by InitLearnableParameter()--we should have an overload that just does it right away
return net.AddNodeToNetWithElemType(New<LearnableParameter<ElemType>>(net.GetDeviceId(), paramName, rows, cols));
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateLearnableParameter(const std::wstring& paramName, const TensorShape& tensorShape)
{
return net.AddNodeToNetWithElemType(New<LearnableParameter<ElemType>>(net.GetDeviceId(), paramName, tensorShape));
}
#if 0 // not functional at present
//sparse matrix size is optionally specified
template<class ElemType> shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateSparseLearnableParameter(const std::wstring & paramName, const size_t rows, const size_t cols, const size_t size)
{
return net.AddNodeToNetWithElemType(New<SparseLearnableParameter<ElemType>>(net.GetDeviceId(), paramName, rows, cols, size));
}
#endif
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateInputNode(const std::wstring& inputName, const size_t rows)
{
return net.AddNodeToNetWithElemType(New<InputValue<ElemType>>(net.GetDeviceId(), inputName, rows));
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateSparseInputNode(const std::wstring& inputName, const size_t rows)
{
return net.AddNodeToNetWithElemType(New<SparseInputValue<ElemType>>(net.GetDeviceId(), inputName, rows));
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateInputNode(const std::wstring& inputName, const TensorShape& sampleLayout)
{
return net.AddNodeToNetWithElemType(New<InputValue<ElemType>>(net.GetDeviceId(), inputName, sampleLayout));
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateSparseInputNode(const std::wstring& inputName, const TensorShape& imageLayout)
{
return net.AddNodeToNetWithElemType(New<SparseInputValue<ElemType>>(net.GetDeviceId(), inputName, imageLayout));
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreatePairNetworkNode(const std::wstring& inputName, const size_t rows, const size_t cols)
{
return net.AddNodeToNetWithElemType(New<PairNetworkNode<ElemType>>(net.GetDeviceId(), inputName, rows, cols));
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateConvolutionNode(const std::wstring& nodeName,
const size_t kernelWidth, const size_t kernelHeight, const size_t outputChannels,
const size_t horizontalSubsample, const size_t verticalSubsample,
ImageLayoutKind imageLayoutKind, const bool zeroPadding,
const size_t maxTempMemSizeInSamples)
{
return net.AddNodeToNetWithElemType(New<ConvolutionNode<ElemType>>(net.GetDeviceId(), nodeName,
kernelWidth, kernelHeight, outputChannels,
horizontalSubsample, verticalSubsample, imageLayoutKind,
zeroPadding,
maxTempMemSizeInSamples));
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateMaxPoolingNode(const std::wstring& nodeName,
const size_t windowWidth, const size_t windowHeight, const size_t horizontalSubsample, const size_t verticalSubsample, ImageLayoutKind imageLayoutKind)
{
return net.AddNodeToNetWithElemType(New<MaxPoolingNode<ElemType>>(net.GetDeviceId(), nodeName, windowWidth, windowHeight, horizontalSubsample, verticalSubsample, imageLayoutKind));
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateAveragePoolingNode(const std::wstring& nodeName,
const size_t windowWidth, const size_t windowHeight, const size_t horizontalSubsample, const size_t verticalSubsample, ImageLayoutKind imageLayoutKind)
{
return net.AddNodeToNetWithElemType(New<AveragePoolingNode<ElemType>>(net.GetDeviceId(), nodeName, windowWidth, windowHeight, horizontalSubsample, verticalSubsample, imageLayoutKind));
}
// this is the catch-all for all cases not covered as special cases above
// Unlike the specialized ones above, this one creates nodes by type given as a string.
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CreateComputationNode(const std::wstring& nodeType, const std::wstring& nodeName)
{
return net.AddNodeToNetWithElemType(NewStandardNode(nodeType, net.GetDeviceId(), nodeName));
}
// -----------------------------------------------------------------------
// node creation
// -----------------------------------------------------------------------
// The following functions create nodes and link them to the network and their inputs.
// TODO: Do we need both this set and the one above that does not add inputs? Can they share more code?
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::PairNetwork(const ComputationNodePtr& a, const std::wstring nodeName)
{
if (net.GetNodeFromName(a->NodeName(), nullptr, false) != nullptr)
{
fprintf(stderr, "PairNetwork: asked to pair a node with name %ls in another network. However, this network has already a node with the same name. Should avoid this case.\n", a->NodeName().c_str());
RuntimeError("PairNetwork: asked to pair a node with name in another network. However, this network has already a node with the same name. Should avoid this case.\n");
}
return net.AddNodeToNetAndAttachInputs(New<PairNetworkNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Convolution(const ComputationNodePtr weight,
const ComputationNodePtr inputValues,
const size_t kernelWidth, const size_t kernelHeight, const size_t outputChannels, const size_t horizontalSubsample, const size_t verticalSubsample, ImageLayoutKind imageLayoutKind, const bool zeroPadding, const size_t maxTempMemSizeInSamples,
const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<ConvolutionNode<ElemType>>(net.GetDeviceId(), nodeName,
kernelWidth, kernelHeight, outputChannels, horizontalSubsample, verticalSubsample, imageLayoutKind, zeroPadding,
maxTempMemSizeInSamples),
weight, inputValues);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::MaxPooling(const ComputationNodePtr inputValues,
const size_t windowWidth, const size_t windowHeight, const size_t horizontalSubsample, const size_t verticalSubsample, ImageLayoutKind imageLayoutKind,
const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<MaxPoolingNode<ElemType>>(net.GetDeviceId(), nodeName,
windowWidth, windowHeight, horizontalSubsample, verticalSubsample, imageLayoutKind),
inputValues);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::AveragePooling(const ComputationNodePtr inputValues,
const size_t windowWidth, const size_t windowHeight, const size_t horizontalSubsample, const size_t verticalSubsample, ImageLayoutKind imageLayoutKind,
const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<AveragePoolingNode<ElemType>>(net.GetDeviceId(), nodeName,
windowWidth, windowHeight, horizontalSubsample, verticalSubsample, imageLayoutKind),
inputValues);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::ErrorPrediction(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<ErrorPredictionNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::PerDimMeanVarNormalization(const ComputationNodePtr feature, const ComputationNodePtr mean,
const ComputationNodePtr InvStdDev, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<PerDimMeanVarNormalizationNode<ElemType>>(net.GetDeviceId(), nodeName), feature, mean, InvStdDev);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::PerDimMeanVarDeNormalization(const ComputationNodePtr feature, const ComputationNodePtr mean,
const ComputationNodePtr InvStdDev, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<PerDimMeanVarDeNormalizationNode<ElemType>>(net.GetDeviceId(), nodeName), feature, mean, InvStdDev);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::SquareError(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<SquareErrorNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Logistic(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<LogisticNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Logistic(const ComputationNodePtr a, const ComputationNodePtr b, const ComputationNodePtr c, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<LogisticNode<ElemType>>(net.GetDeviceId(), nodeName), a, b, c);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::SequenceDecoder(const ComputationNodePtr label, const ComputationNodePtr prediction, const ComputationNodePtr pairscore, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<SequenceDecoderNode<ElemType>>(net.GetDeviceId(), nodeName), label, prediction, pairscore);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CrossEntropyWithSoftmax(const ComputationNodePtr label, const ComputationNodePtr prediction, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<CrossEntropyWithSoftmaxNode<ElemType>>(net.GetDeviceId(), nodeName), label, prediction);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::SequenceWithSoftmax(const ComputationNodePtr label, const ComputationNodePtr prediction, const ComputationNodePtr loglikelihood, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<SequenceWithSoftmaxNode<ElemType>>(net.GetDeviceId(), nodeName), label, prediction, loglikelihood);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::NoiseContrastiveEstimation(const ComputationNodePtr label, const ComputationNodePtr prediction,
const ComputationNodePtr input_weight,
const ComputationNodePtr input_bias, const std::wstring nodeName,
NCEEvalMode mode)
{
return net.AddNodeToNetAndAttachInputs(New<NoiseContrastiveEstimationNode<ElemType>>(net.GetDeviceId(), nodeName, mode), label, prediction, input_weight, input_bias);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::ClassCrossEntropyWithSoftmax(const ComputationNodePtr label, const ComputationNodePtr prediction,
const ComputationNodePtr input_weight,
const ComputationNodePtr cls_log_post_prob,
const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<ClassBasedCrossEntropyWithSoftmaxNode<ElemType>>(net.GetDeviceId(), nodeName), label, prediction, input_weight, cls_log_post_prob);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CRF(const ComputationNodePtr label,
const ComputationNodePtr postDepScore,
const ComputationNodePtr transition_score,
const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<CRFNode<ElemType>>(net.GetDeviceId(), nodeName), label, postDepScore, transition_score);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::DummyCriterion(const ComputationNodePtr objectives, const ComputationNodePtr derivatives, const ComputationNodePtr prediction, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<DummyCriterionNode<ElemType>>(net.GetDeviceId(), nodeName), objectives, derivatives, prediction);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::LSTM(const ComputationNodePtr obs,
const ComputationNodePtr inputGate,
const ComputationNodePtr forgetGate,
const ComputationNodePtr outputGate,
const ComputationNodePtr memoryCellWgt,
const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<LSTMNode<ElemType>>(net.GetDeviceId(), nodeName), obs, inputGate, forgetGate, outputGate, memoryCellWgt);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CrossEntropy(const ComputationNodePtr label, const ComputationNodePtr prediction, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<CrossEntropyNode<ElemType>>(net.GetDeviceId(), nodeName), label, prediction);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::MatrixL1Reg(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<MatrixL1RegNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::MatrixL2Reg(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<MatrixL2RegNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Mean(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<MeanNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::InvStdDev(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<InvStdDevNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Negate(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<NegateNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::RectifiedLinear(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<RectifiedLinearNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Sigmoid(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<SigmoidNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Tanh(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<TanhNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Exp(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<ExpNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Log(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<LogNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Cos(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<CosineNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Hardmax(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<HardmaxNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Softmax(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<SoftmaxNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::LogSoftmax(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<LogSoftmaxNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Sum(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<SumElementsNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
#ifndef ENABLE_BROADCASTING_ELEMENTTIMES
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Scale(const ComputationNodePtr scalar, const ComputationNodePtr matrix, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<ScaleNode<ElemType>>(net.GetDeviceId(), nodeName), scalar, matrix);
}
#endif
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Transpose(const ComputationNodePtr matrix, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<TransposeNode<ElemType>>(net.GetDeviceId(), nodeName), matrix);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Times(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<TimesNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::TransposeTimes(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<TransposeTimesNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::ElementTimes(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<ElementTimesNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
#ifndef ENABLE_BROADCASTING_ELEMENTTIMES
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::RowElementTimes(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<RowElementTimesNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::ColumnElementTimes(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<ColumnElementTimesNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
#endif
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::StrideTimes(const ComputationNodePtr a, const ComputationNodePtr b, const ComputationNodePtr c, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<StrideTimesNode<ElemType>>(net.GetDeviceId(), nodeName), a, b, c);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::DiagTimes(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<DiagTimesNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::CosDistance(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<CosDistanceNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::KhatriRaoProduct(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<KhatriRaoProductNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Plus(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<PlusNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Minus(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<MinusNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Dropout(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<DropoutNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Reshape(const ComputationNodePtr a,
const TensorShape& imageLayout,
const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<ReshapeNode<ElemType>>(net.GetDeviceId(), nodeName, imageLayout), a);
}
#if 1
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::DeprecatedReshape(const ComputationNodePtr a,
const size_t numRows,
const TensorShape& imageLayout,
const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<DeprecatedReshapeNode<ElemType>>(net.GetDeviceId(), nodeName, numRows, imageLayout), a);
}
#endif
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::RowRepeat(const ComputationNodePtr a, const size_t num_repeat, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<RowRepeatNode<ElemType>>(net.GetDeviceId(), nodeName, num_repeat), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Diagonal(const ComputationNodePtr a, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<DiagonalNode<ElemType>>(net.GetDeviceId(), nodeName), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::PastValue(const ComputationNodePtr a, const float initHiddenActivity, const size_t row_size, size_t timeStep, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<PastValueNode<ElemType>>(net.GetDeviceId(), nodeName, initHiddenActivity, row_size, timeStep), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::FutureValue(const ComputationNodePtr a, const float initHiddenActivity, const size_t row_size, size_t timeStep, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<FutureValueNode<ElemType>>(net.GetDeviceId(), nodeName, initHiddenActivity, row_size, timeStep), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Parallel(const ComputationNodePtr a, const ComputationNodePtr b, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<ParallelNode<ElemType>>(net.GetDeviceId(), nodeName), a, b);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::RowSlice(const ComputationNodePtr a, const size_t start_index, const size_t num_rows, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<RowSliceNode<ElemType>>(net.GetDeviceId(), nodeName, start_index, num_rows), a);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::RowStack(const std::vector<ComputationNodePtr> pinputs, const std::wstring nodeName)
{
vector<ComputationNodeBasePtr> inputs(pinputs.size());
for (size_t i = 0; i < inputs.size(); i++)
inputs[i] = pinputs[i]; // convert to ComputationNodeBasePtr
return net.AddNodeToNetAndAttachInputs(New<RowStackNode<ElemType>>(net.GetDeviceId(), nodeName), inputs);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::GMMLogLikelihood(const ComputationNodePtr unnormedPrior,
const ComputationNodePtr mean,
const ComputationNodePtr logStddev,
const ComputationNodePtr feature,
const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<GMMLogLikelihoodNode<ElemType>>(net.GetDeviceId(), nodeName), unnormedPrior, mean, logStddev, feature);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::TimeReverse(const ComputationNodePtr input, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<TimeReverseNode<ElemType>>(net.GetDeviceId(), nodeName), input);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::LookupTable(const ComputationNodePtr dictionary, const ComputationNodePtr input, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<LookupTableNode<ElemType>>(net.GetDeviceId(), nodeName), dictionary, input);
}
template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::BatchNormalization(const ComputationNodePtr input,
const ComputationNodePtr scale, const ComputationNodePtr bias, const ComputationNodePtr runMean, const ComputationNodePtr runInvStdDev,
bool eval, bool spatial, double expAvgFactor, ImageLayoutKind imageLayoutKind, const std::wstring nodeName)
{
return net.AddNodeToNetAndAttachInputs(New<BatchNormalizationNode<ElemType>>(net.GetDeviceId(), nodeName, eval, spatial, expAvgFactor, imageLayoutKind),
input, scale, bias, runMean, runInvStdDev);
}
template class ComputationNetworkBuilder<float>;
template class ComputationNetworkBuilder<double>;
} } }