//
// 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 "PreComputeNodes.h"
#include "TrainingNodes.h"
#include "EvaluationNodes.h"
#include "SpecialPurposeNodes.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
#ifdef COMING_SOON
         if (nodeType == OperationNameOf(CRFNode))                              return New<CRFNode<ElemType>>(forward<_Types>(_Args)...);
    else
#endif
         if (nodeType == OperationNameOf(ClassBasedCrossEntropyWithSoftmaxNode))return New<ClassBasedCrossEntropyWithSoftmaxNode<ElemType>>(forward<_Types>(_Args)...);
    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(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)...);
#ifdef COMING_SOON
    else if (nodeType == OperationNameOf(GMMLogLikelihoodNode))                 return New<GMMLogLikelihoodNode<ElemType>>(forward<_Types>(_Args)...);
#endif
    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(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(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(TransposeDimensionsNode))                return New<TransposeDimensionsNode<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)...);
    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)...);
    else if (nodeType == OperationNameOf(SequenceWithSoftmaxNode))              return New<SequenceWithSoftmaxNode<ElemType>>(forward<_Types>(_Args)...);
#ifdef COMING_SOON
    else if (nodeType == OperationNameOf(SequenceDecoderNode))                  return New<SequenceDecoderNode<ElemType>>(forward<_Types>(_Args)...);
#endif
#ifdef COMING_SOON
    else if (nodeType == OperationNameOf(ShiftNode))                            return New<ShiftNode<ElemType>>(forward<_Types>(_Args)...);
#endif
    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(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(TimesNode))                            return New<TimesNode<ElemType>>(forward<_Types>(_Args)...);
    else if (nodeType == OperationNameOf(TransposeDimensionsNode))              return New<TransposeDimensionsNode<ElemType>>(forward<_Types>(_Args)...);
    else if (nodeType == OperationNameOf(TransposeTimesNode))                   return New<TransposeTimesNode<ElemType>>(forward<_Types>(_Args)...);
    // legacy names we also support for back compat of model-files
    else if (nodeType == L"ColumnElementTimes")                                 return New<ElementTimesNode<ElemType>>(forward<_Types>(_Args)...);
    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"PerDimMeanVarDeNormalizationNode")                   return New<PerDimMeanVarDeNormalizationNode<ElemType>>(forward<_Types>(_Args)...);
    else if (nodeType == L"RowElementTimes")                                    return New<ElementTimesNode<ElemType>>(forward<_Types>(_Args)...);
    else if (nodeType == L"Scale")                                              return New<ElementTimesNode<ElemType>>(forward<_Types>(_Args)...);
    else if (nodeType == L"Transpose")                                          return New<TransposeDimensionsNode<ElemType>>(forward<_Types>(_Args)...);
#if 1
    else if (nodeType == OperationNameOf(LegacyReshapeNode))                    return New<LegacyReshapeNode<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 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));
}

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>::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>::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);
}

#ifdef COMING_SOON
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);
}
#endif

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);
}

#ifdef COMING_SOON
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);
}
#endif

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>::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);
}

template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::TransposeDimensions(const ComputationNodePtr matrix, int dim1, int dim2, const std::wstring nodeName)
{
    return net.AddNodeToNetAndAttachInputs(New<TransposeDimensionsNode<ElemType>>(net.GetDeviceId(), nodeName, dim1, dim2), matrix);
}

template <class ElemType>
shared_ptr<ComputationNode<ElemType>> ComputationNetworkBuilder<ElemType>::Times(const ComputationNodePtr a, const ComputationNodePtr b, size_t outputRank, const std::wstring nodeName)
{
    return net.AddNodeToNetAndAttachInputs(New<TimesNode<ElemType>>(net.GetDeviceId(), nodeName, outputRank), 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);
}

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>::LegacyReshape(const ComputationNodePtr a,
                                                                                         const size_t numRows,
                                                                                         const TensorShape& imageLayout,
                                                                                         const std::wstring nodeName)
{
    return net.AddNodeToNetAndAttachInputs(New<LegacyReshapeNode<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>::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);
}

#ifdef COMING_SOON
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);
}
#endif

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, double epsilon, bool useCntkEngine, ImageLayoutKind imageLayoutKind, const std::wstring nodeName)
{
    return net.AddNodeToNetAndAttachInputs(New<BatchNormalizationNode<ElemType>>(net.GetDeviceId(), nodeName, eval, spatial, expAvgFactor, epsilon, useCntkEngine, imageLayoutKind),
                                           input, scale, bias, runMean, runInvStdDev);
}

template class ComputationNetworkBuilder<float>;
template class ComputationNetworkBuilder<double>;

} } }