CNTK/Source/ComputationNetworkLib/ComputationNetwork.h

912 строки
40 KiB
C++

//
// Copyright (c) Microsoft. All rights reserved.
// Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
//
#pragma once
#include "Basics.h"
#include "File.h"
#include "Matrix.h"
#include "Config.h"
#include "ComputationNode.h"
#include "ScriptableObjects.h"
#include <map>
#include <string>
#include <stdexcept>
#include <list>
#include <vector>
#include <algorithm>
#include <fstream>
#include <sstream>
#include <stdlib.h>
#include <iostream>
#include <regex>
#include <chrono>
#include <unordered_map>
#include <set>
namespace Microsoft { namespace MSR { namespace CNTK {
// ===========================================================================
// ComputationNetwork -- computation graph and operations
// ===========================================================================
class ComputationNetwork : public ScriptableObjects::Object, public ScriptableObjects::HasToString, public ScriptableObjects::IConfigRecord
{
public:
typedef shared_ptr<ComputationNetwork> ComputationNetworkPtr;
// -----------------------------------------------------------------------
// construction
// -----------------------------------------------------------------------
ComputationNetwork()
: m_randomSeedOffset(0),
m_isCompiled(false),
m_pMBLayout(make_shared<MBLayout>())
{
}
ComputationNetwork(DEVICEID_TYPE deviceId)
: ComputationNetwork()
{
SetDeviceId(deviceId);
}
ComputationNetwork(const ScriptableObjects::IConfigRecordPtr configp); // construct from config
virtual ~ComputationNetwork()
{
ClearNetwork(); // This will explicitly remove all nodes. This is needed to break circular references in loops.
}
void ClearNetwork();
void InvalidateCompiledNetwork();
void SetDeviceId(DEVICEID_TYPE deviceId)
{
m_deviceId = deviceId;
}
DEVICEID_TYPE GetDeviceId() const { return m_deviceId; }
// -----------------------------------------------------------------------
// (de-)serialization
// -----------------------------------------------------------------------
template <class ElemType>
void ReadPersistableParameters(File& fstream, bool create);
// reload node content only, e.g. used by SGD::Train() when going back to an older model that had better training objective
template <class ElemType>
void RereadPersistableParameters(const std::wstring& fileName)
{
File fstream(fileName, FileOptions::fileOptionsBinary | FileOptions::fileOptionsRead);
ReadPersistableParameters<ElemType>(fstream, false);
}
// design BUGBUG: binary files do not know whether they are float or double.
// TODO: modify file format to know this; then eliminate the <ElemType> dependency (and in some future, allow nodes to be different)
template <class ElemType> void Read(const std::wstring& fileName);
template <class ElemType> void Load(const std::wstring& fileName)
{
Read<ElemType>(fileName);
// perform all further post-processing, caching, etc.
CompileNetwork();
// To ensure that all the BN nodes changed to eval mode unless it's in Training mode.
SetBatchNormalizationNodesBelowEvalMode(true);
}
// static helper to instantiate a network from a file
template <class ElemType>
static ComputationNetworkPtr CreateFromFile(DEVICEID_TYPE deviceId, const std::wstring& fileName)
{
auto net = make_shared<ComputationNetwork>(deviceId);
net->Load<ElemType>(fileName);
return net;
}
void Save(const std::wstring& fileName, const FileOptions fileFormat = FileOptions::fileOptionsBinary) const;
void SaveEdited(const std::wstring& fileName, const FileOptions fileFormat = FileOptions::fileOptionsBinary);
template <class ElemType>
void SaveToDbnFile(ComputationNetworkPtr net, const std::wstring& fileName) const;
private:
void SaveToFileImpl(const std::wstring& fileName, const FileOptions fileFormat) const;
public:
// -----------------------------------------------------------------------
// evaluation
// -----------------------------------------------------------------------
// main entry point for forward prop
void ForwardProp(const ComputationNodeBasePtr rootNode);
// main entry point for backprop
void Backprop(const ComputationNodeBasePtr rootNode);
template <class NODESET> // version that takes multiple nodes
void ForwardProp(const NODESET& nodes)
{
for (auto& node : nodes)
ForwardProp(node);
}
static void BumpEvalTimeStamp(const std::vector<ComputationNodeBasePtr>& nodes);
void ResetEvalTimeStamps();
// and for a set of nodes
void StartEvaluateMinibatchLoop(const ComputationNodeBasePtr& rootNode) // (ugly name; meant to be unique so we can rename if needed)
{
VerifyIsCompiled("StartEvaluateMinibatchLoop");
ResetEvalTimeStamps(); // invalidate all m_value fields --TODO: redundant (called over again for every root node). Make this private and only call for sets of nodes.
}
template <class NODESET>
void StartEvaluateMinibatchLoop(const NODESET& nodes) // (ugly name; meant to be unique so we can rename if needed)
{
for (auto& node : nodes)
StartEvaluateMinibatchLoop(node);
}
template <class NODESET>
void StartEvaluateMinibatchLoop(const NODESET& nodes1, const NODESET& nodes2) // often needed for two sets (training & evaluation criteria)
{
StartEvaluateMinibatchLoop(nodes1);
StartEvaluateMinibatchLoop(nodes2);
}
// -----------------------------------------------------------------------
// evaluation: preparation
// -----------------------------------------------------------------------
void CompileNetwork(); // call this after creation, Load(), and any modification
private:
void ValidateNetwork();
void ValidateNodes(list<ComputationNodeBasePtr> nodes, bool isFinalValidationPass, size_t& todo);
void MarkValueNonSharableNodes();
private:
void DetermineSetOfAllRoots();
void CollectInputAndLearnableParameters(const ComputationNodeBasePtr& rootNode);
void CollectInputAndLearnableParametersRec(const ComputationNodeBasePtr& node, set<ComputationNodeBasePtr>& visited, list<ComputationNodeBasePtr>& inputs, list<ComputationNodeBasePtr>& learnableParameters);
bool IsCompiled() const { return m_isCompiled; }
void VerifyIsCompiled(const char* where) const;
public:
void AllocateAllMatrices(const std::vector<ComputationNodeBasePtr>& evalRootNodes, const std::vector<ComputationNodeBasePtr>& outValueRootNodes, ComputationNodeBasePtr trainRootNode);
private:
void ReleaseMatricesAfterEvalForChildren(ComputationNodeBasePtr n, std::unordered_map<ComputationNodeBasePtr, int>& parentCount);
void AllocateGradientMatricesForInputs(ComputationNodeBasePtr parentNode);
public:
// -----------------------------------------------------------------------
// evaluation: execution plan and network recurrent-loop analysis
// -----------------------------------------------------------------------
void FormNestedNetwork(const ComputationNodeBasePtr& rootNode);
ComputationNodeBasePtr GetNestedNetwork(const ComputationNodeBasePtr& rootNode);
// The methods below determine evaluation order, which is tricky in presence of recurrent loops.
// TODO: Can this be moved to a separate class?
private:
// This is part of the FormRecurrentLoops() process, and only called from there.
void FormRecurrentLoops(const ComputationNodeBasePtr& rootNode);
void DetermineSCCs(const ComputationNodeBasePtr& rootNode);
void DetermineSCCsR(ComputationNodeBasePtr cur, std::list<ComputationNodeBasePtr>& sccStack, size_t& index, size_t& loopId);
void DetermineLoopForwardOrder(std::unordered_set<ComputationNodeBasePtr>& visited, std::unordered_set<ComputationNodeBasePtr>& recStack, std::list<ComputationNodeBasePtr>& nodesStack, ComputationNodeBasePtr cur);
void GatherLoopNodesR(const ComputationNodeBasePtr& rootNode, std::unordered_set<ComputationNodeBasePtr>& visited, std::map<int, std::list<ComputationNodeBasePtr>>& recurrentResult, std::list<ComputationNodeBasePtr>& noRecurrentResult);
void ReorderLoops(std::list<ComputationNodeBasePtr>& nodes, const std::map<int, std::list<ComputationNodeBasePtr>>& /*recurrentNodes*/, const std::list<ComputationNodeBasePtr>& /*noRecurrentNodes*/);
public:
// -----------------------------------------------------------------------
// evaluation: traversal
// These three functions create and cache traversal orders of the network.
// -----------------------------------------------------------------------
// determine the required order in which nodes must be computed in order to compute 'rootNode'
// skipPairNetwork == true is only used when called from FormRecurrentLoops()
void FormEvalOrder(const ComputationNodeBasePtr& rootNode)
{
if (m_evalOrders.find(rootNode) != m_evalOrders.end())
{
if (rootNode)
fprintf(stderr, "FormEvalOrder: WARNING: Was called twice for %ls %ls operation.\n", rootNode->NodeName().c_str(), rootNode->OperationName().c_str());
else
fprintf(stderr, "FormEvalOrder: WARNING: Was called twice.\n");
}
if (rootNode)
m_evalOrders[rootNode] = rootNode->EnumerateNodes();
else
m_evalOrders[rootNode] = ComputationNodeBase::EnumerateNodes(m_allRoots);
}
// replace an existing eval order with an updated one
// This is meant to be used by FormRecurrentLoops(). TODO: Hopefully this can be not done anymore some day.
void UpdateEvalOrder(const ComputationNodeBasePtr& rootNode, std::list<ComputationNodeBasePtr>& nodes)
{
GetEvalOrder(rootNode); // verify that there is already an entry for rootNode
m_evalOrders[rootNode] = nodes;
}
std::list<ComputationNodeBasePtr>& GetEvalOrder(const ComputationNodeBasePtr& rootNode)
{
if (m_evalOrders.find(rootNode) == m_evalOrders.end())
LogicError("GetEvalOrder: Called without prior call to FormEvalOrder() for %ls %ls operation", rootNode->NodeName().c_str(), rootNode->OperationName().c_str());
return m_evalOrders[rootNode];
}
protected:
class SEQTraversalFlowControlNode;
private:
static std::shared_ptr<SEQTraversalFlowControlNode> FindInRecurrentLoops(const std::vector<std::shared_ptr<SEQTraversalFlowControlNode>>& recurrentInfo, const ComputationNodeBasePtr& node);
public:
// -----------------------------------------------------------------------
// MBLayouts
// -----------------------------------------------------------------------
// Note: this is also used to copy MBLayouts into our existing MBLayout instance, which is a somewhat questionable design.
const MBLayoutPtr& GetMBLayoutPtr() { return m_pMBLayout; }
size_t GetNumParallelSequences() const { return m_pMBLayout->GetNumParallelSequences(); }
// determine the actual MB size from the feature nodes
// This returns max number of columns over the feature nodes.
// Note that if we have multiple slices, MB size != #frames.
// BUGBUG: This will break once we have inconsistent layouts.
size_t DetermineActualMBSizeFromFeatures() const
{
size_t actualMBSize = 0;
const auto& featureNodes = FeatureNodes(); // TODO: a getter; should be called GetFeatureNodes()
for (auto& nodeIter : featureNodes)
actualMBSize = max(actualMBSize, nodeIter->GetMBLayout()->GetNumCols());
return actualMBSize;
}
// When external code (readers, namely) updates InputValue's m_value,
// calling this function is required to make sure that any internal state gets updated correctly.
// Only a change to the column dimension i sallowed
void NotifyInputNodesFunctionValuesMBSizeModified()
{
for (auto& nodeIter : FeatureNodes())
nodeIter->NotifyFunctionValuesMBSizeModified();
for (auto& nodeIter : LabelNodes())
nodeIter->NotifyFunctionValuesMBSizeModified();
}
// this counts the actual number of frames in a minibatch (not counting gaps in parallel sequences)
// TODO: Instead of passing numAllSamples in here, we should determine it from the inputs in case of no layout. Or simply forbid this case.
size_t GetNumSamplesWithLabel(const size_t numAllSamples) const
{
if (m_pMBLayout)
return m_pMBLayout->GetActualNumSamples();
else
return numAllSamples; // TODO: Return the actual number of samples, by inquiring our own input nodes; then eliminate the numAllSamples parameter.
}
// -----------------------------------------------------------------------
// node construction
// -----------------------------------------------------------------------
// non-static version needed because it accesses m_randomSeedOffset
// Excessively used by SimpleNetworkBuilder, but always after CreateLearnableParameter(), so we should really absorb it there
template <class ElemType>
void InitLearnableParameters(const ComputationNodeBasePtr& node,
const bool uniformInit,
const unsigned long randomSeed,
const ElemType initValueScale,
bool initOnCPUOnly = false);
template <typename N>
static shared_ptr<N> AsNodePtr(const ComputationNodeBasePtr& inode)
{
return dynamic_pointer_cast<N>(inode);
}
template <typename N>
static bool IsNodePtr(const ComputationNodeBasePtr& inode)
{
return AsNodePtr<N>(inode) != nullptr;
}
// -----------------------------------------------------------------------
// network editing
// -----------------------------------------------------------------------
ComputationNodeBasePtr CopyNode(const ComputationNetwork& fromNet, const std::wstring fromName, std::wstring toName, const CopyNodeFlags flags);
void CopySubTree(const ComputationNetwork& fromNet, const std::wstring fromName, std::wstring toNamePrefix, const CopyNodeFlags flags);
void CopyInputs(const std::wstring fromName, std::wstring toName);
void RenameNode(const std::wstring& nodeNameOrig, const std::wstring& nodeNameNew);
void RenameNode(ComputationNodeBasePtr node, const std::wstring& newNodeName);
void DeleteNode(const std::wstring& nodeName);
void ChangeNode(wstring nodeName, ComputationNodeBasePtr newNode);
void ReplaceLeafNode(wstring oldNodeName, ComputationNodeBasePtr newNode);
void ReplaceFinalCriterionNode(wstring oldNodeName, ComputationNodeBasePtr newNode);
void AddFeatureNode(ComputationNodeBasePtr featureNode);
void RemoveFeatureNode(ComputationNodeBasePtr featureNode);
void SetLearnableNodesBelowLearningRateMultiplier(const float learningRateMultiplier, const ComputationNodeBasePtr& rootNode = nullptr);
void SetBatchNormalizationNodesBelowEvalMode(const bool evalMode, const ComputationNodeBasePtr& rootNode = nullptr);
// -----------------------------------------------------------------------
// node access
// -----------------------------------------------------------------------
bool NodeNameExists(const std::wstring& name) const
{
auto iter = m_nameToNodeMap.find(name);
return (iter != m_nameToNodeMap.end());
}
ComputationNodeBasePtr GetNodeFromName(const std::wstring& name) const
{
auto iter = m_nameToNodeMap.find(name);
if (iter == m_nameToNodeMap.end())
RuntimeError("GetNodeFromName: Node name %ls does not exist.", name.c_str());
return iter->second;
}
// GetNodesFromName - Get all the nodes from a name that may match a wildcard '*' pattern
// only patterns with a single '*' at the beginning, in the middle, or at the end are accepted
// name - node name (with possible wildcard)
// returns: vector of nodes that match the pattern, may return an empty vector for no match
std::vector<ComputationNodeBasePtr> GetNodesFromName(const std::wstring& name) const
{
std::vector<ComputationNodeBasePtr> nodes;
size_t found = name.find_first_of(L'*');
if (found == std::wstring::npos)
{
if (NodeNameExists(name))
nodes.push_back(GetNodeFromName(name));
}
else
{
std::wstring head = name.substr(0, found);
std::wstring tail = name.substr(found + 1);
for (auto nodeIter = m_nameToNodeMap.begin(); nodeIter != m_nameToNodeMap.end(); nodeIter++)
{
const wstring& nodeName = nodeIter->first;
// if it matches on both ends (we only support A*B patterns it's a match
bool headMatch = head.empty() || nodeName.find(head) == 0;
bool tailMatch = tail.empty() || nodeName.rfind(tail) == nodeName.size() - tail.size();
if (headMatch && tailMatch)
nodes.push_back(nodeIter->second);
}
}
return nodes;
}
// -----------------------------------------------------------------------
// functions to pass on specific SGD options to nodes
// -----------------------------------------------------------------------
template <class ElemType>
static void SetDropoutRate(ComputationNetworkPtr net, const ComputationNodeBasePtr& criterionNode, const double dropoutRate, double& prevDropoutRate, unsigned long& dropOutSeed);
template <class ElemType>
static void SetSeqParam(ComputationNetworkPtr net,
const ComputationNodeBasePtr criterionNode,
const double& hsmoothingWeight,
const double& frameDropThresh,
const bool& doreferencealign,
const double& amf = 14.0f,
const double& lmf = 14.0f,
const double& wp = 0.0f,
const double& bMMIfactor = 0.0f,
const bool& sMBR = false);
static void SetMaxTempMemSizeForCNN(ComputationNetworkPtr net, const ComputationNodeBasePtr& criterionNode, const size_t maxTempMemSizeInSamples);
// -----------------------------------------------------------------------
// node-group access
// -----------------------------------------------------------------------
// these two groups are determined from the network to be executed
// They depend on the root node that is being evaluated.
const std::list<ComputationNodeBasePtr>& InputNodes(const ComputationNodeBasePtr& rootNode /*, bool bNoBuild = false*/)
{
auto iter = m_inputValues.find(rootNode);
if (iter == m_inputValues.end())
LogicError("InputNodes() called for root %ls %ls operation for the set of inputs has not (yet?) been determined.", rootNode->NodeName().c_str(), rootNode->OperationName().c_str());
return iter->second;
}
const std::list<ComputationNodeBasePtr>& LearnableParameterNodes(const ComputationNodeBasePtr& rootNode)
{
auto iter = m_learnableParameters.find(rootNode);
if (iter == m_learnableParameters.end())
LogicError("LearnableParameterNodes() called for root %ls %ls operation for which the set of learnable parameters has not (yet?) been determined.", rootNode->NodeName().c_str(), rootNode->OperationName().c_str());
return iter->second;
}
// these are specified as such by the user
inline std::vector<ComputationNodeBasePtr>& FeatureNodes()
{
return m_features;
}
inline const std::vector<ComputationNodeBasePtr>& FeatureNodes() const
{
return m_features;
}
inline std::vector<ComputationNodeBasePtr>& LabelNodes()
{
return m_labels;
}
inline std::vector<ComputationNodeBasePtr>& FinalCriterionNodes()
{
return m_finalCriteria;
}
inline std::vector<ComputationNodeBasePtr> CriterionNodesFrom(const wstring& criterionNodeName)
{
ComputationNodeBasePtr node = GetNodeFromName(criterionNodeName);
if (node->HasMBLayout() || node->GetSampleLayout().GetNumElements() != 1)
InvalidArgument("%ls %ls operation is not a valid training or eval criterion node.", node->NodeName().c_str(), node->OperationName().c_str());
return std::vector<ComputationNodeBasePtr>{node};
}
inline std::vector<ComputationNodeBasePtr>& EvaluationNodes()
{
return m_evalNodes;
}
inline std::vector<ComputationNodeBasePtr>& OutputNodes()
{
return m_outputNodes;
}
// -----------------------------------------------------------------------
// node access
// -----------------------------------------------------------------------
size_t GetTotalNumberOfNodes() const
{
return m_nameToNodeMap.size();
}
// TODO: could be a dup
std::map<const std::wstring, ComputationNodeBasePtr, nocase_compare>& GetNameToNodeMap() // specially for ExperimentalNetworkBuilder; don't use this otherwise
{
return m_nameToNodeMap;
}
std::vector<ComputationNodeBasePtr> GetAllNodes() const
{
std::vector<ComputationNodeBasePtr> nodes;
for (auto nodeIter = m_nameToNodeMap.begin(); nodeIter != m_nameToNodeMap.end(); nodeIter++)
{
ComputationNodeBasePtr node = nodeIter->second;
nodes.push_back(node);
}
return nodes;
}
std::list<ComputationNodeBasePtr> GetNodesWithType(const wstring typeName, const ComputationNodeBasePtr& rootNode = nullptr)
{
std::list<ComputationNodeBasePtr> nodesWithType;
// find nodes from all available nodes
if (rootNode == nullptr)
{
for (auto nodeIter = m_nameToNodeMap.begin(); nodeIter != m_nameToNodeMap.end(); nodeIter++)
{
ComputationNodeBasePtr node = nodeIter->second;
if (node->OperationName() == typeName)
nodesWithType.push_back(node);
}
}
else
{
// for calculating a specific node
const std::list<ComputationNodeBasePtr>& nodes = GetEvalOrder(rootNode);
for (auto nodeIter = nodes.begin(); nodeIter != nodes.end(); nodeIter++)
{
ComputationNodeBasePtr node = (*nodeIter);
if (node->OperationName() == typeName)
nodesWithType.push_back(node);
}
}
return nodesWithType;
}
public:
// return list of nodes that require precomputation and not precomputed yet
std::list<ComputationNodeBasePtr> GetNodesRequiringPreComputation(const ComputationNodeBasePtr& rootNode = nullptr, bool checkComputed = true);
// -----------------------------------------------------------------------
// unit testing
// -----------------------------------------------------------------------
bool UnitTest(bool allowFragment = false);
bool UnitTest(const ComputationNodeBasePtr& rootNode);
// -----------------------------------------------------------------------
// specialized operations
// -----------------------------------------------------------------------
template <class ElemType>
void PerformSVDecomposition(const map<wstring, float>& SVDConfig, size_t AlignedSize);
// -----------------------------------------------------------------------
// construction
// -----------------------------------------------------------------------
protected:
// Copy constructor, should never be called.
#pragma warning(push)
#pragma warning(disable : 4702) // this function is flagged but unclear why
ComputationNetwork(const ComputationNetwork& /*deepCopyFrom*/)
{
// TODO: can we just define it as private without implementation?
LogicError("'ComputationNetwork(const ComputationNetwork& deepCopyFrom)' should never be called.");
}
#pragma warning(pop)
// Assignment operator, should never be called.
ComputationNetwork& operator=(const ComputationNetwork& /*deepCopyFrom*/)
{
// TODO: can we just define it as private without implementation?
LogicError("'ComputationNetwork& operator=(const ComputationNetwork& deepCopyFrom)' should never be called.");
}
// -----------------------------------------------------------------------
// node creation
// -----------------------------------------------------------------------
public:
// TODO: move these close to where they are used
// add a node to m_nameToNodeMap[], which is our node holder
// Duplicate node names are rejected.
ComputationNodeBasePtr AddNodeToNet(const ComputationNodeBasePtr& nodePtr)
{
// found
// TODO: use .insert() and test result.second == false means not inserted since already exists
if (m_nameToNodeMap.find(nodePtr->NodeName()) != m_nameToNodeMap.end())
RuntimeError("Duplicated computation node name.");
m_nameToNodeMap[nodePtr->NodeName()] = nodePtr;
return nodePtr; // allows e.g. return AddNodeToNet(New...);
}
// TODO: not very nice--need to fix way more outside to get this right
template <class N>
shared_ptr<N> AddNodeToNetWithElemType(const shared_ptr<N> nodePtr)
{
return dynamic_pointer_cast<N>(AddNodeToNet(nodePtr));
}
template <class N, class... _Types>
shared_ptr<N> AddNodeToNetAndAttachInputs(const shared_ptr<N> nodePtr, _Types&&... _Args)
{
nodePtr->AttachInputs(std::forward<_Types>(_Args)...);
return AddNodeToNetWithElemType(nodePtr);
// return nodePtr; // allows e.g. return AddNodeToNetAndAttachInputs(New..., inputs);
}
public:
// -----------------------------------------------------------------------
// evaluation
// -----------------------------------------------------------------------
// zeroes out all gradients except the root itself
// TODO: why not the root?
// (Note that inside the nodes this only really sets a flag to do it later when needed, but that's not our concern.)
void ZeroGradients(const ComputationNodeBasePtr& rootNode)
{
for (auto& node : GetEvalOrder(rootNode)) // note: any order will do
node->ZeroGradientsOfInputs();
}
private:
bool IsTypicalCriterionNode(ComputationNodeBasePtr nodePtr);
void PrintComputationTree(const ComputationNodeBasePtr& rootNode, const bool forwardCompute, const bool printMatrices = false);
public:
// -----------------------------------------------------------------------
// diagnostics
// -----------------------------------------------------------------------
// if node name is not found, dump all nodes
// otherwise dump just that node
// This function is called from MEL, i.e. must be prepared to operate on an uncompiled network (only m_nameToNodeMap is valid).
void DumpNodeInfoToFile(const std::wstring& nodeName, const bool printValues, const bool printMetadata, const std::wstring outputFile, const std::wstring& nodeNameInRegEx = L"")
{
if (nodeNameInRegEx.empty())
{
if (NodeNameExists(nodeName))
{
File fstream(outputFile,
FileOptions::fileOptionsText | FileOptions::fileOptionsWrite);
const ComputationNodeBasePtr& nodePtr = GetNodeFromName(nodeName);
nodePtr->DumpNodeInfo(printValues, printMetadata, fstream);
}
else // node name is not found, dump all nodes
{
fprintf(stderr, "Warning: node name %ls does not exist in the network. dumping all nodes.\n",
nodeName.c_str());
DumpAllNodesToFile(printValues, printMetadata, outputFile);
}
}
else
{
std::wregex NameRegEx(nodeNameInRegEx);
std::vector<ComputationNodeBasePtr> NodeList;
std::vector<wstring> NameList;
for (auto m : m_nameToNodeMap)
{
if (regex_match(m.first, NameRegEx))
{
NodeList.push_back(m.second);
NameList.push_back(m.first);
}
}
fprintf(stderr, "DumpNodeInfo: %d nodes matching RegEx(%ls): \n", (int) NameList.size(), nodeNameInRegEx.c_str());
for (auto x : NameList)
{
fprintf(stderr, "\t%ls\n", x.c_str());
}
fprintf(stderr, "DumpNodeInfo: dumping node info (%s printing values) to %ls\n", printValues ? "with" : "without", outputFile.c_str());
DumpNodeInfoToFile(NodeList, printValues, printMetadata, outputFile);
}
}
// dump all nodes in the network to file
void DumpAllNodesToFile(const bool printValues,
const bool printMetadata,
const std::wstring outputFile)
{
File fstream(outputFile,
FileOptions::fileOptionsText | FileOptions::fileOptionsWrite);
for (auto nodeIter = m_nameToNodeMap.begin(); nodeIter != m_nameToNodeMap.end(); nodeIter++)
{
ComputationNodeBasePtr nodePtr = nodeIter->second;
nodePtr->DumpNodeInfo(printValues, printMetadata, fstream);
}
}
// this one is called from MEL and from DumpNodeInfoToFile() above
void DumpNodeInfoToFile(const vector<ComputationNodeBasePtr>& nodes,
const bool printValues,
const bool printMetadata,
const std::wstring outputFile)
{
File fstream(outputFile,
FileOptions::fileOptionsText | FileOptions::fileOptionsWrite);
for (auto nodeIter = nodes.begin(); nodeIter != nodes.end(); nodeIter++)
{
ComputationNodeBasePtr nodePtr = *nodeIter;
nodePtr->DumpNodeInfo(printValues, printMetadata, fstream);
}
}
// -----------------------------------------------------------------------
// topological plot [1/13/2015 erw] plot network topology using dot language
// -----------------------------------------------------------------------
private:
wstring FormSpecialNodes(wstring style, std::vector<ComputationNodeBasePtr>& specialNodes);
typedef std::pair<ComputationNodeBasePtr, ComputationNodeBasePtr> ComputationArc;
public:
void DescribeNetworkUsingDot(std::list<ComputationArc>& arcs, std::wstring outFile);
void PlotNetworkTopology(const std::wstring outputFile);
// -----------------------------------------------------------------------
// scripting integration
// -----------------------------------------------------------------------
// pretend to be a ConfigRecord
const ScriptableObjects::ConfigValuePtr& /*IConfigRecord::*/ operator[](const wstring& id) const override; // e.g. confRec[L"message"]
const ScriptableObjects::ConfigValuePtr* /*IConfigRecord::*/ Find(const wstring& id) const override; // returns nullptr if not found
vector<wstring> /*IConfigRecord::*/ GetMemberIds() const override;
// create a somewhat readable representation, aimed at diagnostics/debugging
wstring /*HasToString::*/ ToString() const
{
wstring args;
for (auto& iter : m_nameToNodeMap)
{
const auto node = iter.second;
if (!args.empty())
args.append(L"\n");
args.append(node->ToString());
}
return TypeId<decltype(*this)>() + L" " + NestString(args, L'[', true, ']');
}
protected:
// FlowControlNodes for internal use by this class:
// -----------------------------------------------------------------------
// SEQTraversalFlowControlNode -- FlowControlNode to traverse a (sub-)network time step by time step
//
// This is to implement recurrent loops. All nodes inside a loop are listed
// inside this node. This node's ForwardProp() function will execute
// them inside a loop over all time steps of the recurrence.
// For every time step, the entire chain of nodes is called, with the time index
// passed as a FrameRange object.
// -----------------------------------------------------------------------
class SEQTraversalFlowControlNode : public FlowControlNode
{
public: // m_nestedNodes needed public by ComputationNetwork::FindInRecurrentLoops(), which really should be part of SEQTraversalFlowControlNode
typedef FlowControlNode Base;
using Base::m_nestedNodes;
public:
virtual const std::wstring OperationName() const override
{
return L"SEQTraversalFlowControlNode";
}
virtual void BeginForwardProp() override;
virtual void ForwardProp(const FrameRange&) override;
virtual void EndForwardProp() override;
virtual void BeginBackprop() override;
virtual void BackpropTo(const size_t inputIndex, const FrameRange&) override
{
NOT_IMPLEMENTED;
}
virtual void EndBackprop() override;
virtual void Backprop(const FrameRange& fr, bool childrenInThisLoop, bool childrenInOuterLoop) override;
virtual void RequestMatricesBeforeForwardProp(MatrixPool& matrixPool);
virtual void ReleaseMatricesAfterForwardProp(MatrixPool& matrixPool);
virtual void AllocateGradientMatricesForInputs(MatrixPool& matrixPool);
virtual void RequestMatricesBeforeBackprop(MatrixPool& matrixPool);
virtual void ReleaseMatricesAfterBackprop(MatrixPool& matrixPool);
virtual bool IsOutOfDateWrtInputs() const override;
public:
// std::vector<ComputationNodeBasePtr> m_nestedNodes; // all nodes involved in this loop, in evaluation order
ComputationNodeBasePtr m_sourceNode; // one of the nodes of the loop --TODO: What is the special meaning of this node? It seems to always be a delay node.
int m_loopId; // unique loop id, index in m_allSEQNodes array
int m_steppingDirection; // +1 if left to right (t=0..T-1), -1 if rightt to left (t=T-1..0)
SEQTraversalFlowControlNode(int loopId, ComputationNodeBasePtr cur)
: m_loopId(loopId),
m_sourceNode(cur)
{
SetNodeName(L"Loop_" + m_sourceNode->NodeName());
}
};
// -----------------------------------------------------------------------
// PARTraversalFlowControlNode -- FlowControlNode that traverses a (sub-)network
//
// This node contains a list of nodes in a (sub-)network. This node's
// ForwardProp() method will execute all those nodes once in PAR mode,
// that is, by passing a FrameRange object that represents to operate
// on all frames in the node simultaneously.
//
// The outermost network level is also represented by this node for execution.
// -----------------------------------------------------------------------
class PARTraversalFlowControlNode : public FlowControlNode
{
typedef FlowControlNode Base;
using Base::m_nestedNodes;
public:
virtual const std::wstring OperationName() const override
{
return L"PARTraversalFlowControlNode";
}
virtual void BeginForwardProp() override
{
}
virtual void ForwardProp(const FrameRange&) override;
virtual void EndForwardProp() override
{
}
virtual void BeginBackprop() override
{
}
virtual void BackpropTo(const size_t inputIndex, const FrameRange&) override
{
NOT_IMPLEMENTED;
} // ugh, call Backprop() instead
virtual void EndBackprop() override
{
}
virtual void Backprop(const FrameRange& fr, bool childrenInThisLoop, bool childrenInOuterLoop) override;
virtual void RequestMatricesBeforeForwardProp(MatrixPool& matrixPool);
virtual void ReleaseMatricesAfterForwardProp(MatrixPool& matrixPool);
virtual void AllocateGradientMatricesForInputs(MatrixPool& matrixPool);
virtual void RequestMatricesBeforeBackprop(MatrixPool& matrixPool);
virtual void ReleaseMatricesAfterBackprop(MatrixPool& matrixPool);
public:
// this special constructor constructs the top-level network node
// There is currently no other constructor for inner nested PAR-traversed sub-networks, but there will be.
PARTraversalFlowControlNode(const std::vector<shared_ptr<SEQTraversalFlowControlNode>>& recurrentInfo, const std::list<ComputationNodeBasePtr>& allNodes);
// Base::m_nestedNodes contains all top-level nodes, in evaluation order
};
public:
// -----------------------------------------------------------------------
// data members
// -----------------------------------------------------------------------
unsigned long GetRandomSeedOffset()
{
return m_randomSeedOffset;
}
void SetRandomSeedOffset(unsigned long value)
{
m_randomSeedOffset = value;
}
protected:
DEVICEID_TYPE m_deviceId; // TODO: is this shared by all nodes?
unsigned long m_randomSeedOffset;
// main node holder
std::map<const std::wstring, ComputationNodeBasePtr, nocase_compare> m_nameToNodeMap; // [name] -> node; this is the main container that holds this networks' nodes
// node groups
// These are specified by the user by means of tags or explicitly listing the node groups.
// TODO: Are these meant to be disjoint?
std::vector<ComputationNodeBasePtr> m_features;
std::vector<ComputationNodeBasePtr> m_labels;
std::vector<ComputationNodeBasePtr> m_finalCriteria;
std::vector<ComputationNodeBasePtr> m_evalNodes;
std::vector<ComputationNodeBasePtr> m_outputNodes;
vector<std::vector<ComputationNodeBasePtr>*> GetAllNodeGroups() // get all groups to allow to iterate over all of them ...continue
{
return vector<std::vector<ComputationNodeBasePtr>*>{&m_features, &m_labels, &m_finalCriteria, &m_evalNodes, &m_outputNodes};
}
// used for sentence boundary information passed from reader to reset RNN state
// specify how the minibatch is packed for each sample
// TODO: This will change once we allow for multiple inconsistent layouts.
MBLayoutPtr m_pMBLayout; // note that this must be installed before doing anything that needs it (default leaves a nullptr)
private:
// -----------------------------------------------------------------------
// the following members are all result of post-processing by CompileNetwork()
// -----------------------------------------------------------------------
// list of all roots in this network
// A root is a node that can run as a target of ForwardProp(). See DetermineSetOfAllRoots().
std::vector<ComputationNodeBasePtr> m_allRoots;
std::vector<std::shared_ptr<SEQTraversalFlowControlNode>> m_allSEQNodes; // [loopId] cached set of SEQTraversalFlowControlNodes to allow sharing and idempotence of FormRecurrentLoops()
// cache for evaluation ordering:
bool m_isCompiled; // CompileNetwork has been called
// cached network iterations
std::map<const ComputationNodeBasePtr, std::list<ComputationNodeBasePtr>> m_evalOrders; // [out node] flat depth-first traversal starting from out node
std::map<const ComputationNodeBasePtr, ComputationNodeBasePtr> m_nestedNetworks; // [out node] network rewritten as recursive traveral, potentially optimized; execution plan
// cached quick-access list for inputs and parameters
std::map<const ComputationNodeBasePtr, std::list<ComputationNodeBasePtr>> m_inputValues; // [out node] -> all input nodes feeding into out node
std::map<const ComputationNodeBasePtr, std::list<ComputationNodeBasePtr>> m_learnableParameters; // [out node] -> all parameter nodes feeding into out node
private:
// pool for matrices that can be shared across nodes
// TODO: does this apply to anything else besides temporary node-internal intermediate results? What, for example?
MatrixPool m_matrixPool;
};
typedef ComputationNetwork::ComputationNetworkPtr ComputationNetworkPtr;
// The following emits the class and enables the BaseMatrix<double> to be available (used by EvalDll)
// The corresponding Matrix<float> is emitted in the SetDeviceId function above.
template class Matrix<double>;
// TODOs:
// - automatic inference of time window w.r.t. delay nodes (and related nodes such as a temporal pooling)
// - have overrides of RuntimeError etc. in ComputationNode, which prepend the error string with the node name and operation
// - code prettification:
// - sort all node implementations' methods into the same order; esp, ForwardProp() comes before partial
// - sort important nodes first; move unused/experimental nodes into source files named accordingly
} } }