https://github.com/Microsoft/CNTK
Tip revision: 10a8ffcf50d7b9225f3236ffcfdc422b2014fb92 authored by microsoft-github-policy-service[bot] on 23 September 2022, 14:06:50 UTC
Microsoft mandatory file (#3870)
Microsoft mandatory file (#3870)
Tip revision: 10a8ffc
ComputationNetwork.h
//
// 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 "ComputationEnvironment.h"
#include <map>
#include <string>
#include <stdexcept>
#include <list>
#include <vector>
#include <deque>
#include <algorithm>
#include <fstream>
#include <sstream>
#include <stdlib.h>
#include <iostream>
#include <regex>
#include <chrono>
#include <unordered_map>
#include <set>
#include "ComputationGraphAlgorithms.h"
namespace Microsoft { namespace MSR { namespace CNTK {
inline std::wstring ToString(const ComputationNodeBasePtr& node)
{
return node->NodeName();
}
// ===========================================================================
// ComputationNetwork -- computation graph and operations
// ===========================================================================
class ComputationNetwork :
public ScriptableObjects::Object,
public ScriptableObjects::HasToString,
public ScriptableObjects::CustomConfigRecord
{
public:
typedef shared_ptr<ComputationNetwork> ComputationNetworkPtr;
// -----------------------------------------------------------------------
// construction
// -----------------------------------------------------------------------
ComputationNetwork() :
m_randomSeedOffset(0),
m_isCompiled(false),
m_areMatricesAllocated(false),
m_pMBLayoutOfNetwork(make_shared<MBLayout>(1, 0, ComputationNodeBase::DefaultDynamicAxisName)),
m_environment(make_shared<ComputationEnvironment>())
{
//m_pMBLayoutOfNetwork->SetAxisName(L"T");
}
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; }
void PrintNodeTiming();
protected:
void ConstructFromRoots(DEVICEID_TYPE deviceId, std::deque<ComputationNodeBasePtr>&& roots, const map<ComputationNodeBasePtr, ComputationNodeBasePtr>& replacements);
void ProcessSpecialNodes(const ScriptableObjects::IConfigRecord& config, std::deque<ComputationNodeBasePtr>& roots);
public:
// -----------------------------------------------------------------------
// (de-)serialization
// -----------------------------------------------------------------------
template <class ElemType>
void ReadPersistableParameters(size_t modelVersion, 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);
auto modelVersion = GetModelVersion(fstream);
ReadPersistableParameters<ElemType>(modelVersion, 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();
}
// 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);
private:
void SaveToFileImpl(const std::wstring& fileName, const FileOptions fileFormat) const;
static size_t GetModelVersion(File& fstream);
public:
// -----------------------------------------------------------------------
// evaluation
// -----------------------------------------------------------------------
// main entry point for forward prop
void ForwardProp(const ComputationNodeBasePtr rootNode);
// main entry point for post forward and backward prop
void PostForwardAndBackProp(const ComputationNodeBasePtr rootNode);
// main entry point for backprop
void Backprop(const ComputationNodeBasePtr rootNode);
template <class NODESET> // version that takes multiple nodes
void TravserseInSortedGlobalEvalOrder(const NODESET& nodes, const std::function<void(const ComputationNodeBasePtr&)>& action)
{
// Create a composite evaluation order for all the nodes
std::vector<ComputationNodeBasePtr> combinedEvalOrder;
for (auto node : nodes)
{
auto currentNodeEvalOrder = GetEvalOrder(node);
combinedEvalOrder.insert(combinedEvalOrder.end(), currentNodeEvalOrder.begin(), currentNodeEvalOrder.end());
}
combinedEvalOrder = SortByGlobalEvalOrder(combinedEvalOrder);
set<ComputationNodeBasePtr> completedSEQNodes;
for (auto& node : combinedEvalOrder)
{
if (node->IsPartOfLoop())
{
shared_ptr<SEQTraversalFlowControlNode> recInfo = FindInRecurrentLoops(m_allSEQNodes, node);
assert(recInfo != nullptr);
if (completedSEQNodes.insert(recInfo).second)
node = recInfo;
else
node = nullptr;
}
if (node)
action(node);
}
}
template <class NODESET> // version that takes multiple nodes
void ForwardProp(const NODESET& nodes)
{
TravserseInSortedGlobalEvalOrder(nodes, [](const ComputationNodeBasePtr& node) {
PARTraversalFlowControlNode::ForwardProp(node, FrameRange(nullptr));
});
}
template <class NODESET> // version that takes multiple nodes
void PostForwardAndBackProp(const NODESET& nodes)
{
TravserseInSortedGlobalEvalOrder(nodes, [](const ComputationNodeBasePtr& node) {
PARTraversalFlowControlNode::PostForwardAndBackProp(node);
});
}
template <class NODESET_FROM, class NODESET_TO> // version that takes both initial and final set of nodes
void ForwardPropFromTo(const NODESET_FROM& nodesFrom, const NODESET_TO& nodesTo)
{
// Compute the set of nodes to do forward on.
std::set<ComputationNodeBasePtr> nodesToForward;
TravserseInSortedGlobalEvalOrder(nodesTo, [&](const ComputationNodeBasePtr& node) {
for (const ComputationNodeBasePtr& input : node->GetInputs())
{
if (std::find(nodesFrom.begin(), nodesFrom.end(), input) != nodesFrom.end()
|| nodesToForward.find(input) != nodesToForward.end())
{
nodesToForward.insert(node);
}
}
});
// Perform forward on resulting nodes in global evaluation order.
for (const auto& node : SortByGlobalEvalOrder(nodesToForward))
{
ComputationNetwork::PARTraversalFlowControlNode::ForwardProp(node, FrameRange(nullptr));
}
}
static void BumpEvalTimeStamp(const std::vector<ComputationNodeBasePtr>& nodes);
void ResetEvalTimeStamps();
void SetEvalTimeStampsOutdatedWithRegardToAll();
// 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.
for (auto& node : GetEvalOrder(rootNode))
node->OnEpochStart();
}
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
void ValidateNetwork();
private:
size_t ValidateNodes(list<ComputationNodeBasePtr> nodes, bool isFirstPass, bool isFinalValidationPass);
bool ValidateNode(ComputationNodeBasePtr node, bool isFinalValidationPass) const;
void MarkValueNonSharableNodes();
void ChangeNodeInputs(ComputationNodeBasePtr fromNode, ComputationNodeBasePtr toNode);
private:
void DetermineSetOfAllRoots();
void CollectInputAndLearnableParameters(const ComputationNodeBasePtr& rootNode);
void CollectInputAndLearnableParametersRec(const ComputationNodeBasePtr& node, set<ComputationNodeBasePtr>& visited, list<ComputationNodeBasePtr>& inputs, list<ComputationNodeBasePtr>& learnableParameters);
void ResetMBLayouts();
bool IsCompiled() const { return m_isCompiled; }
bool AreMatricesAllocated() const { return m_areMatricesAllocated; }
void VerifyIsCompiled(const char* where) const;
public:
void AllocateAllMatrices(const std::vector<ComputationNodeBasePtr>& evalRootNodes, const std::vector<ComputationNodeBasePtr>& outValueRootNodes, ComputationNodeBasePtr trainRootNode);
// From the set of nodes extract all nodes which are used as accumulator nodes.
std::set<ComputationNodeBasePtr> ExtractNodesWhichAccumulateResult(std::set<ComputationNodeBasePtr> nodes);
private:
void PrintMemorySharingStructure(const std::vector<ComputationNodeBasePtr>& nodes);
void ReleaseMatricesAfterEvalForChildren(ComputationNodeBasePtr n, std::unordered_map<ComputationNodeBasePtr, std::unordered_set<ComputationNodeBasePtr>>& parentsMap);
public:
// -----------------------------------------------------------------------
// evaluation: execution plan and network recurrent-loop analysis
// -----------------------------------------------------------------------
void FormNestedNetwork(const ComputationNodeBasePtr& rootNode);
ComputationNodeBasePtr GetNestedNetwork(const ComputationNodeBasePtr& rootNode);
private:
// The method below determines evaluation order, which is tricky in presence of recurrent loops.
void FormRecurrentLoops();
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'
// If passed nullptr, this will traverse the entire net.
// If passed non-null, it will take the global traveral in ITS order and sub-filter against root's dependents.
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");
}
std::list<ComputationNodeBasePtr> evalOrder;
ExecutionGraph graph(m_allRoots);
if (!rootNode) // this creates the global list of nodes
{
evalOrder = ::CNTK::PostOrderTraversal(graph, m_allRoots);
}
else // this creates a subset of the global eval order of all nodes that rootNode depends on
{
auto rawTraversalForRoot = ::CNTK::PostOrderTraversal(graph, { rootNode });// traverse to find the set (we ignore the order)
set<ComputationNodeBasePtr> rawSet(rawTraversalForRoot.begin(), rawTraversalForRoot.end());
for (const auto& node : GetEvalOrder(nullptr)) // iterate over global one and pull out everything that is included in the set for rootNode
{
if (rawSet.find(node) != rawSet.end())
evalOrder.push_back(node);
}
}
m_evalOrders[rootNode] = evalOrder;
}
template <typename ContainerType>
std::vector<ComputationNodeBasePtr> SortByGlobalEvalOrder(const ContainerType& nodesToSort)
{
std::vector<ComputationNodeBasePtr> sortedEvalOrder;
if (nodesToSort.size() == 1)
sortedEvalOrder.assign(nodesToSort.cbegin(), nodesToSort.cend());
else
{
const std::list<ComputationNodeBasePtr>& allNodesEvalOrder = GetEvalOrder(nullptr);
for (auto& node : allNodesEvalOrder)
{
if (std::find(nodesToSort.cbegin(), nodesToSort.cend(), node) != nodesToSort.cend())
sortedEvalOrder.push_back(node);
}
}
return sortedEvalOrder;
}
// 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, const std::list<ComputationNodeBasePtr>& nodes)
{
GetEvalOrder(rootNode); // verify that there is already an entry for rootNode
m_evalOrders[rootNode] = nodes;
}
bool EvalOrderExists(const ComputationNodeBasePtr& rootNode) const
{
return m_evalOrders.find(rootNode) != m_evalOrders.end();
}
// get depth-first traversal order
// TODO: This is currently not immutable because it gets patched w.r.t. recurrent loops. Ideally we don't patch. Need to review and verify that it is sufficient.
const std::list<ComputationNodeBasePtr>& GetEvalOrder(const ComputationNodeBasePtr& rootNode) const
{
auto iter = m_evalOrders.find(rootNode);
if (iter == m_evalOrders.end())
{
LogicError("GetEvalOrder: Called without prior call to FormEvalOrder() for %ls %ls operation", rootNode->NodeName().c_str(), rootNode->OperationName().c_str());
}
return iter->second;
}
// same as GetEvalOrder() where ordering is irrelevant
const std::list<ComputationNodeBasePtr>& GetAllNodesForRoot(const ComputationNodeBasePtr& rootNode) const
{
return GetEvalOrder(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.
// BUGBUG (Issue #95): This function will conflict once we have multiple input layouts in the network.
const MBLayoutPtr& GetMBLayoutPtrOfNetwork() { return m_pMBLayoutOfNetwork; }
// 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.
// BUGBUG: The number computed here is completely off (it the layout has gaps
// they will also be counted towards the actualMBSize)
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.
// BUGBUG (Issue #95): With variable-length sequences, this can no longer be a network method.
size_t GetNumSamplesWithLabelOfNetwork(const size_t numAllSamples) const
{
if (m_pMBLayoutOfNetwork)
return m_pMBLayoutOfNetwork->GetActualNumSamples();
else
return numAllSamples; // TODO: Return the actual number of samples, by inquiring our own input nodes; then eliminate the numAllSamples parameter.
}
// -----------------------------------------------------------------------
// node construction
// -----------------------------------------------------------------------
// this function is only for use by NDL (deprecated)
void InitLearnableParameters(const ComputationNodeBasePtr& node,
const wchar_t* initString, // "uniform"|"gaussian"|"fixedValue"
double initValue, // scale | scale | value
unsigned long randomSeed = 0,
bool initOnCPUOnly = false) const;
// non-static version needed because it accesses m_randomSeedOffset
// Legacy version that is for random only.
void RandomInitLearnableParameters(const ComputationNodeBasePtr& node, const bool uniformInit, const unsigned long randomSeed, const double initValueScale, bool initOnCPUOnly = false) const;
template <class ElemType>
void InitLearnableParametersWithBilinearFill(const ComputationNodeBasePtr& node, size_t kernelWidth, size_t kernelHeight);
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 ReplaceNode(wstring nodeName, ComputationNodeBasePtr newNode);
void InsertNode(wstring nodeName, ComputationNodeBasePtr newNode, const std::set<std::wstring>& newNodeTags);
void ReplaceLeafNode(wstring oldNodeName, ComputationNodeBasePtr newNode);
void ReplaceFinalCriterionNode(wstring oldNodeName, ComputationNodeBasePtr newNode);
void AddFeatureNode(ComputationNodeBasePtr featureNode);
//ComputationNodeBasePtr RemoveFeatureNode(ComputationNodeBasePtr featureNode);
void SetLearnableNodesBelowLearningRateMultiplier(const float learningRateMultiplier, 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: Network has no node named '%ls'.", 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;
}
// -----------------------------------------------------------------------
// environment properties
// -----------------------------------------------------------------------
ComputationEnvironment& Environment() const { return *m_environment; }
// -----------------------------------------------------------------------
// functions to pass on specific SGD options to nodes
// -----------------------------------------------------------------------
// TODO: Why are all these static, but then take a network as the first argument? --> make them class members
static void SetDropoutRate(ComputationNetworkPtr net, const ComputationNodeBasePtr& criterionNode, const double dropoutRate, double& prevDropoutRate);
static void SetIRngUserSeed(ComputationNetworkPtr net, const ComputationNodeBasePtr& criterionNode, size_t randSeedBase);
template <class ElemType>
static void SetBatchNormalizationTimeConstants(ComputationNetworkPtr net, const ComputationNodeBasePtr& criterionNode,
double normalizationTimeConstant, double& prevNormalizationTimeConstant,
double blendTimeConstant, double& prevBlendTimeConstant);
template <class ElemType>
static void SetSeqParam(ComputationNetworkPtr net,
const ComputationNodeBasePtr criterionNode,
const double& hsmoothingWeight, // TODO: Why are all these passed by reference?
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;
}
inline const 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());
m_namedCriterionNodes[criterionNodeName] = std::vector<ComputationNodeBasePtr>{node};
return m_namedCriterionNodes[criterionNodeName];
}
std::vector<ComputationNodeBasePtr> OutputNodesByName(const std::vector<std::wstring>& outputNodeNames)
{
std::vector<ComputationNodeBasePtr> outputNodes;
if (outputNodeNames.size() == 0)
{
if (OutputNodes().size() == 0)
RuntimeError("There is no default output node specified in the network.");
outputNodes = OutputNodes();
}
else
{
for (int i = 0; i < outputNodeNames.size(); i++)
outputNodes.push_back(GetNodeFromName(outputNodeNames[i]));
}
return outputNodes;
}
// Collect all input nodes that outputNodes depend on.
std::vector<ComputationNodeBasePtr> InputNodesForOutputs(const std::vector<std::wstring>& outputNodeNames)
{
// use set to remove duplicated items
auto outputNodes = OutputNodesByName(outputNodeNames);
std::set<ComputationNodeBasePtr> inputNodesMap;
for (auto& onode : outputNodes)
{
for (auto& inode : InputNodes(onode))
inputNodesMap.insert(inode);
}
std::vector<ComputationNodeBasePtr> inputNodes;
for (auto& inode : inputNodesMap)
inputNodes.push_back(inode);
return inputNodes;
}
const std::vector<ComputationNodeBasePtr>& RootNodes() const { return m_allRoots; }
// these are specified as such by the user
const std::vector<ComputationNodeBasePtr>& FeatureNodes() const { return m_featureNodes ; }
const std::vector<ComputationNodeBasePtr>& LabelNodes() const { return m_labelNodes ; }
const std::vector<ComputationNodeBasePtr>& FinalCriterionNodes() const { return m_criterionNodes ; }
const std::vector<ComputationNodeBasePtr>& EvaluationNodes() const { return m_evaluationNodes; }
const std::vector<ComputationNodeBasePtr>& OutputNodes() const { return m_outputNodes ; }
private:
// determine the node-group array by the group tag
std::vector<ComputationNodeBasePtr>& GetNodeGroup(const std::wstring& groupTag)
{
if (groupTag == L"feature" ) return m_featureNodes;
else if (groupTag == L"label" ) return m_labelNodes;
else if (groupTag == L"criterion" ) return m_criterionNodes;
else if (groupTag == L"evaluation") return m_evaluationNodes;
else if (groupTag == L"output" ) return m_outputNodes;
else InvalidArgument("Invalid group tag '%ls', must be one of 'feature', 'label', 'criterion', 'evaluation', 'output'.", groupTag.c_str());
}
public:
// add a node to a node group
void AddToNodeGroup(const std::wstring& groupTag, const ComputationNodeBasePtr& node)
{
assert(node);
// determine the node group by its group tag string
auto& nodeGroup = GetNodeGroup(groupTag);
// if node is already in the list then we are done
if (node->HasTag(groupTag))
{
for (const auto& groupNode : nodeGroup) // TODO: is there an STL algorithm?
if (groupNode == node)
return;
// we get here if the node has the tag but is not in the node group yet
}
// verify and update the node's tag
node->SetTag(groupTag);
// add to the node group
nodeGroup.push_back(node);
}
// remove a node from its node group
// Returns true if the node was there.
bool RemoveFromNodeGroup(const std::wstring& groupTag, const ComputationNodeBasePtr& node)
{
bool wasActuallySet = node->ClearTag(groupTag);
if (!wasActuallySet) // if node was not member of the group, we are done
return false;
auto& nodeGroup = GetNodeGroup(groupTag);
for (auto iter = nodeGroup.begin(); iter != nodeGroup.end(); iter++)
{
if (*iter == node)
{
nodeGroup.erase(iter);
return true;
}
}
LogicError("RemoveFromNodeGroup: %ls %ls operation not found in its node group '%ls'.", node->NodeName().c_str(), node->OperationName().c_str(), groupTag.c_str());
}
// -----------------------------------------------------------------------
// node access
// -----------------------------------------------------------------------
size_t GetTotalNumberOfNodes() const
{
return m_nameToNodeMap.size();
}
std::vector<ComputationNodeBasePtr> GetAllNodes() const
{
std::vector<ComputationNodeBasePtr> nodes;
for (const auto& iter : m_nameToNodeMap)
nodes.push_back(iter.second);
return nodes;
}
// determine parent map (this is needed in some editing steps)
// Returns a map[node] -> set of parent nodes.
std::map<ComputationNodeBasePtr, std::set<ComputationNodeBasePtr>> CreateParentsMap() const
{
std::map<ComputationNodeBasePtr, std::set<ComputationNodeBasePtr>> parents; // use a set because a node may have the same input multiple times, e.g. to compute x^2 as x.*x
for (const auto& iter : m_nameToNodeMap)
{
const auto& node = iter.second;
parents[node]; // make sure there is an entry for every parent
for (const auto& child : node->GetInputs())
parents[child].insert(node);
}
return parents;
}
// Return set of immediate output (parent) nodes for given input (child) node
// TODO: there should be a map from output nodes to inputs, so that this operation doesn't take square time
std::vector<ComputationNodeBasePtr> GetParentNodes(const std::wstring& inputNodeName)
{
std::set<ComputationNodeBasePtr> outputNodes;
for (const auto& iter : m_nameToNodeMap)
{
const auto& node = iter.second;
//Iterate over inputs of this node
for (const auto& inputNode : node->GetInputs())
{
if (inputNode->GetName() == inputNodeName)
{
outputNodes.insert(node);
}
}
}
return std::vector<ComputationNodeBasePtr>(outputNodes.begin(), outputNodes.end());
}
std::list<ComputationNodeBasePtr> GetNodesWhere(std::function<bool(const ComputationNodeBasePtr&)>& predicate, const ComputationNodeBasePtr& rootNode = nullptr) const
{
std::list<ComputationNodeBasePtr> filteredNodes;
// find nodes from all available nodes
// TODO: This distinction should not be necessary anymore. Calling GetEvalOrder(nullptr) will have the same effect.
if (rootNode == nullptr)
{
for (auto nodeIter = m_nameToNodeMap.begin(); nodeIter != m_nameToNodeMap.end(); nodeIter++)
{
ComputationNodeBasePtr node = nodeIter->second;
if (predicate(node))
filteredNodes.push_back(node);
}
}
else
{
// for calculating a specific node
for (const auto& node : GetEvalOrder(rootNode)) // TODO: verify that no use of this requires the actual eval order, then change to GetAllNodesForRoot()
{
if (predicate(node))
filteredNodes.push_back(node);
}
}
return filteredNodes;
}
std::list<ComputationNodeBasePtr> GetNodesWithType(const wstring typeName, const ComputationNodeBasePtr& rootNode = nullptr) const
{
std::function<bool(const ComputationNodeBasePtr&)> predicate = [typeName](const ComputationNodeBasePtr& node) { return node->OperationName() == typeName; };
return GetNodesWhere(predicate, rootNode);
}
template <typename T>
std::list<ComputationNodeBasePtr> GetNodesWithType(const ComputationNodeBasePtr& rootNode = nullptr) const
{
std::function<bool(const ComputationNodeBasePtr&)> predicate = [](const ComputationNodeBasePtr& node)
{
return (dynamic_cast<T*>(node.get()) != nullptr);
};
return GetNodesWhere(predicate, rootNode);
}
// Get the eval nodes with names
// if evalNodeNames are not specified, return all the default evalnodes and training criterion nodes.
std::vector<ComputationNodeBasePtr> GetEvalNodesWithName(const std::vector<wstring> evalNodeNames)
{
// determine nodes to evaluate
std::vector<ComputationNodeBasePtr> evalNodes;
set<ComputationNodeBasePtr> criteriaLogged; // (keeps track ot duplicates to avoid we don't double-log criteria)
if (evalNodeNames.size() == 0)
{
fprintf(stderr, "evalNodeNames are not specified, using all the default evalnodes and training criterion nodes.\n");
if (EvaluationNodes().empty() && FinalCriterionNodes().empty())
InvalidArgument("There is no default evaluation node or training criterion specified in the network.");
for (const auto& node : EvaluationNodes())
if (criteriaLogged.insert(node).second)
evalNodes.push_back(node);
for (const auto& node : FinalCriterionNodes())
if (criteriaLogged.insert(node).second)
evalNodes.push_back(node);
}
else
{
for (int i = 0; i < evalNodeNames.size(); i++)
{
const auto& node = GetNodeFromName(evalNodeNames[i]);
if (!criteriaLogged.insert(node).second)
continue;
if (node->GetSampleLayout().GetNumElements() != 1)
InvalidArgument("Criterion nodes to evaluate must have dimension 1x1.");
evalNodes.push_back(node);
}
}
return evalNodes;
}
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);
template <class ElemType>
void SaveToDbnFile(ComputationNetworkPtr net, const std::wstring& fileName) const;
// -----------------------------------------------------------------------
// 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 to ComputationNetworkBuilder.cpp
// add a node to m_nameToNodeMap[], which is our node holder
// This only adds the node to the network's node set, without considering linkage.
// Duplicate node names are rejected.
ComputationNodeBasePtr AddNodeToNet(const ComputationNodeBasePtr& node)
{
auto result = m_nameToNodeMap.insert(make_pair(node->NodeName(), node));
if (!result.second)
RuntimeError("AddNodeToNet: Duplicated name for %ls %ls operation.", node->NodeName().c_str(), node->OperationName().c_str());
node->SetEnvironment(m_environment);
return node; // 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> node)
{
return dynamic_pointer_cast<N>(AddNodeToNet(node));
}
template <class N>
shared_ptr<N> AddNodeToNetAndAttachInputs(const shared_ptr<N> nodePtr, const std::vector<ComputationNodeBasePtr>& inputs)
{
nodePtr->AttachInputs(inputs);
return AddNodeToNetWithElemType(nodePtr);
// return nodePtr; // allows e.g. return AddNodeToNetAndAttachInputs(New..., inputs);
}
// add a node to the network unless it's already there
// Returns false if the node was already there.
// If the network already contains a different node with the same name,
// - then the function will fail
// - unless 'makeUniqueName=true', in which case it will patch the node's name to a unique name.
bool AddNodeToNetIfNotYet(const ComputationNodeBasePtr& node, bool makeUniqueName = false)
{
auto result = m_nameToNodeMap.insert(make_pair(node->NodeName(), node));
// if there's already one under this name, it better be node
// unless user requested 'makeUniqueName', then we will modify the name
while (!result.second/*if already there*/ && result.first->second != node)
{
if (!makeUniqueName || node->NodeName().find_first_of(L".[]") == wstring::npos)
RuntimeError("AddNodeToNetIfNotYet: Duplicated name for %ls %ls operation (%d vs. %d).", node->NodeName().c_str(), node->OperationName().c_str(), (int)node->m_uniqueNumericId, (int)result.first->second->m_uniqueNumericId);
node->SetName(L"_" + node->NodeName());
result = m_nameToNodeMap.insert(make_pair(node->NodeName(), node));
}
node->SetEnvironment(m_environment); // (note: redundant if already part of the network)
return result.second;
}
// remove a node from the network's node set
// This does NOT update any links referencing it, or node groups.
// TODO: We should verify that indeed this node is not referenced by other nodes or node groups,
// nor that this node references any node inside the network.
ComputationNodeBasePtr RemoveNodeFromNet(const ComputationNodeBasePtr& node)
{
node->SetEnvironment(nullptr);
m_nameToNodeMap.erase(node->NodeName());
return node;
}
public:
// -----------------------------------------------------------------------
// evaluation
// -----------------------------------------------------------------------
// zeroes out all gradients except the root itself (since its gradient is set from outside rather than propagated down)
// (Note that inside the nodes this only really sets a flag to do it later when needed, but that's not our concern.)
void ZeroInputGradients(const ComputationNodeBasePtr& rootNode)
{
for (auto& node : GetAllNodesForRoot(rootNode))
node->ZeroGradientsOfInputs();
}
private:
bool IsTypicalCriterionNode(ComputationNodeBasePtr nodePtr);
void PrintComputationTree(const ComputationNodeBasePtr& rootNode, const bool forwardCompute, const bool printMatrices = false);
public:
// -----------------------------------------------------------------------
// diagnostics
// -----------------------------------------------------------------------
void SetTrackGapNans(bool enable)
{
m_environment->trackGapNans = enable;
}
bool GetTrackGapNaNs() const { return m_environment->trackGapNans; }
void SetIsV2Library(bool enable)
{
m_environment->isV2Library = enable;
}
bool GetIsV2Library() const { return m_environment->isV2Library; }
void SetTraceLevel(int traceLevel)
{
m_environment->traceLevel = traceLevel;
}
int TraceLevel() const { return m_environment->traceLevel; }
// call EnableNodeTracing() on the given nodes for real, category, and sparse printing
void EnableNodeTracing(const std::vector<std::wstring>& traceNodeNamesReal,
const std::vector<std::wstring>& traceNodeNamesCategory,
const std::vector<std::wstring>& traceNodeNamesSparse)
{
for (const auto& name : traceNodeNamesReal)
if (NodeNameExists(name))
GetNodeFromName(name)->EnableNodeTracing(/*asReal=*/true, /*asCategoryLabel=*/false, /*asSparse=*/false);
else
fprintf(stderr, "EnableNodeTracing: No node named '%ls'; skipping\n", name.c_str());
for (const auto& name : traceNodeNamesCategory)
if (NodeNameExists(name))
GetNodeFromName(name)->EnableNodeTracing(/*asReal=*/false, /*asCategoryLabel=*/true, /*asSparse=*/false);
else
fprintf(stderr, "EnableNodeTracing: No node named '%ls'; skipping\n", name.c_str());
for (const auto& name : traceNodeNamesSparse)
if (NodeNameExists(name))
GetNodeFromName(name)->EnableNodeTracing(/*asReal=*/false, /*asCategoryLabel=*/false, /*asSparse=*/true);
else
fprintf(stderr, "EnableNodeTracing: No node named '%ls'; skipping\n", name.c_str());
}
// 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 instead.\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
void /*CustomConfigRecord::*/ LazyCreateConfigMember(const wstring& id) const override;
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:
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";
}
static void ForwardProp(const ComputationNodeBasePtr& node, const FrameRange& fr);
static void PostForwardAndBackProp(const ComputationNodeBasePtr& node);
virtual void BeginForwardProp() override {}
virtual void ForwardProp(const FrameRange&) override;
virtual void EndForwardProp() override {}
virtual void PostForwardAndBackProp() 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() const
{
return m_randomSeedOffset;
}
void SetRandomSeedOffset(unsigned long value)
{
m_randomSeedOffset = value;
}
private:
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_featureNodes; // tag="feature"
std::vector<ComputationNodeBasePtr> m_labelNodes; // tag="label"
std::vector<ComputationNodeBasePtr> m_criterionNodes; // tag="criterion"
std::vector<ComputationNodeBasePtr> m_evaluationNodes; // tag="evaluation"
std::vector<ComputationNodeBasePtr> m_outputNodes; // tag="output"
vector<std::vector<ComputationNodeBasePtr>*> GetAllNodeGroups() // get all groups to allow to iterate over all of them ...continue
{
return vector<std::vector<ComputationNodeBasePtr>*>{&m_featureNodes, &m_labelNodes, &m_criterionNodes, &m_evaluationNodes, &m_outputNodes};
}
// used for sentence boundary information passed from reader to reset RNN state
// specify how the minibatch is packed for each sample
// BUGBUG (Issue #95): With variable-length inconsistent layouts, this can no longer be a network property.
MBLayoutPtr m_pMBLayoutOfNetwork; // note that this must be installed before doing anything that needs it (default leaves a nullptr)
// environment information that nodes may want to inquire, e.g. to know whether we are training
ComputationEnvironmentPtr m_environment;
std::map<std::wstring, std::vector<ComputationNodeBasePtr>> m_namedCriterionNodes;
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
bool m_areMatricesAllocated; // AllocateAllMatrices 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;
// Implementation of a graph based on ComputationNodes.
class ExecutionGraph : public ::CNTK::DirectedGraph<ComputationNodeBasePtr>
{
std::vector<ComputationNodeBasePtr> m_roots;
public:
ExecutionGraph(const std::vector<ComputationNodeBasePtr>& roots) : m_roots(roots) {}
std::vector<ComputationNodeBasePtr> Predecessors(const ComputationNodeBasePtr& node) const override
{
return node->GetInputs();
}
const std::vector<ComputationNodeBasePtr>& Roots() const override
{
return m_roots;
}
};
};
typedef ComputationNetwork::ComputationNetworkPtr ComputationNetworkPtr;
// helper that returns 'float' or 'double' depending on ElemType
template <typename ElemType> static inline const wchar_t* ElemTypeName();
template <> /*static*/ inline const wchar_t* ElemTypeName<float>() { return L"float"; }
template <> /*static*/ inline const wchar_t* ElemTypeName<double>() { return L"double"; }
template <> /*static*/ inline const wchar_t* ElemTypeName<half>() { return L"half"; }
template <typename ElemType, typename ElemType2> static inline const wchar_t* ElemTypeName2();
template <> /*static*/ inline const wchar_t* ElemTypeName2<float,half>() { return L"float,half"; }
template <> /*static*/ inline const wchar_t* ElemTypeName2<float,double>() { return L"float,double"; }
template <> /*static*/ inline const wchar_t* ElemTypeName2<double,half>() { return L"double,half"; }
template <> /*static*/ inline const wchar_t* ElemTypeName2<double,float>() { return L"double,float"; }
template <> /*static*/ inline const wchar_t* ElemTypeName2<half,float>() { return L"half,float"; }
template <> /*static*/ inline const wchar_t* ElemTypeName2<half,double>() { return L"half,double"; }
// 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>;
template class Matrix<half>;
// 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
} } }