CNTK/Source/ComputationNetworkLib/ComputationNetworkScripting...

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C++

//
// Copyright (c) Microsoft. All rights reserved.
// Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
//
#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 "ScriptableObjects.h"
#include "ComputationNode.h"
#include "InputAndParamNodes.h"
#include "RecurrentNodes.h"
#include "NonlinearityNodes.h"
#include "LinearAlgebraNodes.h"
#include "ReshapingNodes.h"
#include "ComputationNetwork.h"
#include "ComputationNetworkBuilder.h"
#include <memory>
#include <deque>
#include <set>
#include <string>
#ifndef let
#define let const auto
#endif
using namespace std;
namespace Microsoft { namespace MSR { namespace CNTK {
using namespace Microsoft::MSR::ScriptableObjects;
// ===================================================================
// construction from config
// ===================================================================
const static set<wstring> nodeGroupNames{ L"feature", L"label", L"criterion", L"evaluation", L"output" };
// construct a ComputationNetwork from a ConfigRecord
ComputationNetwork::ComputationNetwork(const IConfigRecordPtr configp) :
ComputationNetwork()
{
let& config = *configp;
SetTraceLevel(config[L"traceLevel"]);
DEVICEID_TYPE deviceId = (DEVICEID_TYPE)(int)config[L"deviceId"];
deque<ComputationNodeBasePtr> workList;
// process 'special nodes'
ProcessSpecialNodes(config, workList);
// flatten the set of all nodes
// we collect all root ComputationNodes from the config record, and then expand into all their children by work-list processing
// TODO: This currently only supports nodes of the same ElemType. We could allow conversion operators.
for (let& id : config.GetMemberIds())
{
let& value = config[id];
if (value.Is<ComputationNodeBase>())
{
const ComputationNodeBasePtr& node = value;
// top-level defined record members get their top-level name
bool isSpecialNode = false;
for (let& nodeGroupName : nodeGroupNames)
isSpecialNode |= id == nodeGroupName + L"Nodes";
if (!isSpecialNode)
node->SetName(id);
workList.push_back(node);
}
}
// TODO: process "outputNodes" etc. arrays: Sync to node Tags, and make them all roots.
// construct from roots
ConstructFromRoots(deviceId, move(workList), map<ComputationNodeBasePtr, ComputationNodeBasePtr>()/*no mapping*/);
}
// process the special-nodes parameters
void ComputationNetwork::ProcessSpecialNodes(const ScriptableObjects::IConfigRecord& config, std::deque<ComputationNodeBasePtr>& workList)
{
for (let& id : config.GetMemberIds())
{
let pos = id.find(L"Nodes");
if (pos == wstring::npos || pos != id.size() - 5) // special node name = node-group name + L"Nodes"
continue;
let nodeGroup = id.substr(0, id.size() - 5);
if (nodeGroupNames.find(nodeGroup) == nodeGroupNames.end())
continue;
let nodeSet = config[id];
let nodes = ScriptableObjects::ConfigArray::FlattenedVectorFrom<ComputationNodeBasePtr>(nodeSet);
for (let& node : nodes)
{
node->SetTag(nodeGroup);
workList.push_back(node);
}
}
}
// construct a network from a list of roots (passed in 'workList')
// This will add to m_nameToNodeMap[] all roots and all nodes reachable from those roots.
// If 'replacements' is given, all root pointers as well as all input pointers of reachable nodes will be mapped. This is needed for model editing.
void ComputationNetwork::ConstructFromRoots(DEVICEID_TYPE deviceId, deque<ComputationNodeBasePtr>&& workList, const map<ComputationNodeBasePtr, ComputationNodeBasePtr>& replacements)
{
SetDeviceId(deviceId);
assert(this->GetTotalNumberOfNodes() == 0);
// replace if requested
// This happens for model editing.
// workList operates on mapped nodes.
size_t numRelinked = 0;
for (auto& nodeRef : workList)
{
let iter = replacements.find(nodeRef);
if (iter != replacements.end())
{
assert(nodeRef->GetEnvironmentPtr()); // must be in some network if mapped
nodeRef = iter->second; // nodeRef is a reference, so this patches the workList in-place
numRelinked++;
}
}
// process work list
// Also call LateAttachInputs() where needed.
while (!workList.empty())
{
let node = workList.front();
workList.pop_front();
// add to set
let wasAdded = AddNodeToNetIfNotYet(node, /*makeUniqueName=*/ true);
if (!wasAdded) // node already there (above will fail if there is a different node with the same name)
continue;
// If node derives from ILateAttachingNode() then it has unresolved inputs. Resolve them now.
// This may generate a whole new load of nodes, including nodes which in turn have late init.
// Note: In case of editing, we may be adding a new node that references nodes from the old
// network that must be mapped because their inputs have changed. Hence, it is important to
// to the mapping *after* late attaching.
if (node->GetNumInputs() == 0) // (if this function is called during model editing, we may already have our inputs)
{
let lateAttachingNode = dynamic_pointer_cast<ILateAttachingNode>(node);
if (lateAttachingNode)
lateAttachingNode->LateAttachInputs();
}
// add it to the respective node groups based on the tags
for (auto tag : node->GetTags())
{
#if 1 // we keep this for a while (we already verified that our samples no longer use this)
// map legacy names
if (tag == L"criteria") tag = L"criterion";
else if (tag == L"eval" ) tag = L"evaluation";
#endif
AddToNodeGroup(tag, node); // tag may be empty, or may have been set by array parameters
}
// traverse children: append them to the end of the work list
// In case of model editing, map inputs.
for (size_t i = 0; i < node->GetNumInputs(); i++)
{
auto input = node->Input(i);
// replace input if needed
let iter = replacements.find(input);
if (iter != replacements.end())
{
assert(input->GetEnvironmentPtr()); // must be in some network if mapped
input = iter->second;
numRelinked++;
node->SetInput(i, input);
}
workList.push_back(input); // (we could check whether c is in 'nodes' already here to optimize, but this way it is cleaner)
}
}
if (TraceLevel() > 0 && numRelinked > 0)
fprintf(stderr, "ConstructFromRoots: %d references were remapped.", (int)numRelinked);
// perform all necessary post-processing
CompileNetwork();
}
// ===================================================================
// behave like a config
// This allows to access nodes inside a network as if it was an IConfigRecord.
// This is meant to be used by whatever we will replace MEL.
// TODO: Is there more than nodes that we want to return? Node groups? deviceId?
// ===================================================================
// not in the cache yet: create it (or not if no such member)
void /*CustomConfigRecord::*/ ComputationNetwork::LazyCreateConfigMember(const wstring& id) const /*override*/
{
auto iter = m_nameToNodeMap.find(id);
if (iter == m_nameToNodeMap.end())
{
// workaround to allow to access members with '.' inside: change to _
for (iter = m_nameToNodeMap.begin(); iter != m_nameToNodeMap.end(); iter++)
if (msra::strfun::ReplaceAll<wstring>(iter->first, L".", L"_") == id)
break;
if (iter == m_nameToNodeMap.end())
return; // no such node
}
const ComputationNodeBasePtr& node = iter->second;
// TODO: What is the expressionPath?
let& nodeName = node->NodeName(); // failFn lambda below holds a copy of the name for the error message. Let's not hold an unneccessary shared_ptr to the node, risking cycles & stuff.
auto valuep = ConfigValuePtr(node, [nodeName](const std::wstring &) { LogicError("ComputationNetwork: Failed to retrieve node '%ls'.", nodeName.c_str()); }, node->NodeName());
InsertConfigMember(id, move(valuep));
}
vector<wstring> /*IConfigRecord::*/ ComputationNetwork::GetMemberIds() const
{
set<wstring> nodeNames;
for (let& iter : m_nameToNodeMap)
{
const ComputationNodeBasePtr& node = iter.second;
wstring nodeName = node->NodeName();
if (nodeName.find_first_of(L"$") != nodeName.npos) // skip non-top-level names
continue;
// temp solution for composites: use _ instead of .
nodeName = msra::strfun::ReplaceAll<wstring>(nodeName, L".", L"_");
if (nodeName.find_first_of(L".[") != nodeName.npos) // skip composite names
continue;
nodeNames.insert(nodeName);
}
return vector<wstring>(nodeNames.begin(), nodeNames.end());
}
// ===================================================================
// ComputationNetworkFromFile
// scripting wrapper to construct ComputationNetwork from file (aka 'Load')
// ===================================================================
template<class ElemType>
class ComputationNetworkFromFile : public ComputationNetwork
{
public:
ComputationNetworkFromFile(const IConfigRecordPtr configp) :
ComputationNetwork()
{
let& config = *configp;
SetTraceLevel(config[L"traceLevel"]);
SetDeviceId((DEVICEID_TYPE)(int)config[L"deviceId"]);
wstring pathName = config[L"pathName"];
if (TraceLevel() > 0)
fprintf(stderr, "Load: Loading model file: %ls", pathName.c_str());
Load<ElemType>(pathName); // note that for CNTK_MODEL_VERSION_7 and above, 'ElemType' is ignored
}
};
ScriptableObjects::ConfigurableRuntimeTypeRegister::AddFloatDouble<ComputationNetworkFromFile<float>, ComputationNetworkFromFile<double>> registerComputationNetworkFromFile(L"ComputationNetworkFromFile");
// ===================================================================
// ComputationNetworkWithEdits
// scripting wrapper to construct by modifying an input network (aka 'Edit')
// ===================================================================
class ComputationNetworkWithEdits : public ComputationNetwork
{
// helper to execute a BS function that maps a CompuationNode to a ComputationNode
// The function may return:
// - its input --> no edit was made
// - an different existing node --> all nodes that use this input should use the returned node instead
// - a newly created node or sub-graph --> this node should replace the old one
// In the latter two cases, the returned node may have inputs that are totally different
// from the original node's.
ComputationNodeBasePtr CallEditFunction(ComputationNodeBasePtr node, const ConfigLambda& editFn)
{
// wrap the argument in a ConfigValuePtr
const wstring& nodeName = node->NodeName();
const wstring& expressionName = nodeName; // TODO: think this through
auto valuep = ConfigValuePtr(static_pointer_cast<Object>(node), [nodeName](const std::wstring &) { LogicError("CallEditFunction: Failed to retrieve node '%ls'.", nodeName.c_str()); }, expressionName);
vector<ConfigValuePtr> args{ valuep };
// execute the lambda (this executes a function that is BS)
ConfigValuePtr result = editFn.Apply(move(args), ConfigLambda::NamedParams(), expressionName);
// cast the result back
return result.AsPtr<ComputationNodeBase>();
}
public:
// constructor
// This constructs a new model from an existing one by:
// - iterating over all nodes
// - trying a sequence of edit functions until one made an edit
// This is like pattern matching: The first edit function that matches will return an updated node.
// - assemble a new network that consists of the old network with edits applied
// Note that the old model is not edited in-place; instead a new copy is made that shares
// unchanged nodes with the original one.
ComputationNetworkWithEdits(const IConfigRecordPtr configp) :
ComputationNetwork()
{
// get config parameters
let& config = *configp;
SetTraceLevel(config[L"traceLevel"]);
let& net = config[L"inputModel"].AsRef<ComputationNetwork>();
let editFunctions = ScriptableObjects::ConfigArray::FlattenedVectorFrom<ConfigLambda>(config[L"editFunctions"]);
let additionalRoots = ScriptableObjects::ConfigArray::FlattenedVectorFrom<ComputationNodeBasePtr>(config[L"additionalRoots"]);
// gather all the edits
// This runs the edit functions over all nodes.
map<ComputationNodeBasePtr, ComputationNodeBasePtr> replacements; // [orig, replacement] all return values from the Edit-function calls
let allNodes = net.GetAllNodes();
for (let& node : allNodes) // iterate over all nodes
{
for (let& editFn : editFunctions) // try all edit functions until one matched
{
let newNode = CallEditFunction(node, editFn);
if (newNode != node) // true if the edit function provided a replacement (an "edit")
{
replacements[node] = newNode; // remember the replaceent
break; // we only apply the first edit function & stop
}
}
}
if (TraceLevel() > 0)
fprintf(stderr, "Edit: %d nodes were edited.\n", (int)replacements.size());
#ifdef _DEBUG
for (let& replacement : replacements)
fprintf(stderr, "\t%ls = %ls() --> %ls = %ls()\n", replacement.first->NodeName().c_str(), replacement.first->OperationName().c_str(), replacement.second->NodeName().c_str(), replacement.second->OperationName().c_str());
#endif
// also 'edit' all nodes that have updated *inputs*
// All nodes that take inputs that have been edited must have their inputs updated.
// Since we do not update the model in-place, we must also create replacements for these.
// That is achieved by recursively including all parents of edits into the set of edits.
let parents = net.CreateParentsMap();
deque<ComputationNodeBasePtr> workList; // work list for recursion
for (let& replacement : replacements)
workList.push_back(replacement.first);
while (!workList.empty())
{
let node = workList.front();
workList.pop_front();
// loop over the node's parents
for (let& parent : parents.find(node)->second)
{
// "edit" (clone) the parent if not yet
if (replacements.find(parent) != replacements.end())
continue; // already a known replacement
// we must "edit" the parent since it depends on a replaced input
replacements[parent] = parent->Duplicate();
// and put this parent into the workList, so that we will gets its parent in turn, etc.
workList.push_back(parent);
#if 0 //def _DEBUG
fprintf(stderr, "\t%ls = %ls() --> relink %ls\n", parent->NodeName().c_str(), parent->OperationName().c_str(), replacements[parent]->NodeName().c_str());
#endif
}
}
if (TraceLevel() > 0)
fprintf(stderr, "Edit: %d out of %d nodes were either edited or need to be relinked.\n", (int)replacements.size(), (int)net.GetTotalNumberOfNodes());
// Now the keys of replacements[] define the set of all nodes that must be relinked.
// replacements may point to nodes that are replacements themselves
// This really can only happen if a replacement itself is an old node.
for (auto& iter : replacements)
while (replacements.find(iter.second) != replacements.end())
iter.second = replacements.find(iter.second)->second;
// Now we have three kinds of nodes:
// - unmodified nodes that will be shared with the old network
// - modified nodes (user edits and their parents)
// - original nodes that are no longer referenced
// The new network will be constructed to have the same roots as the original.
// determine all roots
deque<ComputationNodeBasePtr> roots;
// process 'special nodes'
// BUGBUG: This does not allow to unset tags. If special nodes are listed, they should completely override existing tags for the same node.
ProcessSpecialNodes(config, workList);
// then the original network
for (let& node : allNodes)
if (parents.find(node)->second.empty()) // no parents: it's a root
roots.push_back(node);
// also add new roots
for (let& node : additionalRoots)
roots.push_back(node);
if (TraceLevel() > 0)
fprintf(stderr, "Edit: %d roots to construct the network from.\n", (int)roots.size());
#ifdef _DEBUG
for (let& node : roots)
fprintf(stderr, "\t%ls = %ls()\n", node->NodeName().c_str(), node->OperationName().c_str());
#endif
// The new network is now defined by roots.
// now construct the new network
DEVICEID_TYPE deviceId = (DEVICEID_TYPE)(int)config[L"deviceId"];
ConstructFromRoots(deviceId, move(roots), replacements);
}
};
ScriptableObjects::ConfigurableRuntimeTypeRegister::Add<ComputationNetworkWithEdits> registerComputationNetworkWithEdits(L"ComputationNetworkWithEdits");
// ===================================================================
// CloneFunctionConfigLambda -- lambda to produce a clone of a network
// - creates a BrainScript function that carbon-copies a subsection of an existing network
// - the copy can be shallow or deep, where a deep copy gets its own copy of LearnableParameters
// - a shallow copy (parameters="shared") is a copy of all nodes that depend on the specified input(s),
// while all other nodes are shared from the original network section
// - a deep copy (parameters="lernable" or "constant") also copies all reachable LearnableParameters and their dependents
// - Input() nodes not listed as `inputNodes` are always shared
// - the source network may be a different network, e.g. loaded with BS.Network.Load()
// - a deep copy can be read-only (parameters="constant")
// - Note: multiple uses of the lambda will not share read-only parameters. This is trickier to implement that one might expect.
// - example use cases:
// - adaptation (KL): a frozen read-only copy of the starting model is used as a KL-regularizer
// - adaptation (DLR): an injected input transform is trained while the network is fixed
// - image: lower layers of ImageNet networks serve as immutable feature extractors for another image task
// - DSSM: applying the same network subsection to two inputs
// Usage:
// f = CloneFunction (inputNodes, outputNodes, parameters="lernable" /*|"constant"|"shared"*/)
// Parameters:
// - inputNodes: single node or array of nodes that will become parameters of the function.
// Commonly, this list will include all Input()s that the outputNode(s) depend on.
// - outputNodes: single node or dictionary of nodes that the function will emit
// Example:
// # create a BS function by copying a piece of network
// net = CloneFunction (network.features, network.logP)
// # apply the copy to a new input
// out = net (myFeatures)
// # This will create a copy of the subsection from network.features to network.logP
// # where all links to network.features get replaced by links to myFeatures.
// Example with multiple input and output nodes:
// # create a BS function by copying a piece of network
// # This specific example converts a network back into a BrainScript function.
// # It passes two input nodes --> the BS function will have 2 inputs;
// # and it passes a record of output nodes --> the BS function will return a record with the same member names
// network = BS.Network.Load ("some.dnn")
// net = CloneFunction ((network.features:network.labels), [ ce = network.ce ; errs = network.errs ])
// # create a network from the BS function
// features = Input (13)
// labels = Input (42)
// out = net (features, labels)
// criterionNodes = (out.ce)
// evaluationNodes = (out.errs)
// A specific example: Adapting a network, while using the original network as a regularizer (KLD)
// # load network
// network = BS.Network.Load ("some.dnn")
// # create a trainable clone and a read-only reference clone
// adaptNet = CloneFunction (network.features, [ z = network.z ], readOnly=false)
// # create a read-only clone
// refNet = CloneFunction (network.features, [ z = network.z ], readOnly=true)
// # create the main network
// features = Input (42)
// labels = Input (9000)
// z = adaptNet (features).z
// zRef = refNet (features).z
// # training criterion
// refWeight = 0.9
// kldLabels = labels * (1-refWeight) + Softmax (zRef) * refWeight # interpolate with ref output
// ce = CrossEntropyWithSoftmax (z, kldLabels)
// errs = ClassificationError (z, labels)
// criterionNodes = (ce)
// evaluationNodes = (errs)
// ===================================================================
class CloneFunctionConfigLambda : public ConfigLambda
{
// how we treat the parameters in the clone
enum class ParameterTreatment
{
learnable, // parameters are copied and kept trainable
constant, // parameters are copied and made immutable (e.g. for use of this as a fixed feature extractor)
shared // parameters are shared with where they came from (e.g. for parallel identical paths through a network)
};
public:
// -----------------------------------------------------------------------
// construction
// -----------------------------------------------------------------------
// Executing this function from BrainScript merely sets up a lambda, but does not actually create any clone.
// This is so that the function can be called multiple times in order to create multiple clones.
CloneFunctionConfigLambda(const IConfigRecordPtr configp) :
ConfigLambda(CreateParamNames(*configp), NamedParams(), [this](vector<ConfigValuePtr> &&args, NamedParams &&namedArgs, const std::wstring &exprName){ return this->DoClone(args, exprName); })
{
let& config = *configp;
// input nodes
inputNodes = GetInputNodes(config);
// output nodes
let outputNodesParam = config[L"outputNodes"]; // can be a node or a record
if (outputNodesParam.Is<ComputationNodeBase>()) // scalar case: result is a single node
outputNodes[L""] = outputNodesParam.AsPtr<ComputationNodeBase>(); // indicated by a "" node name in outputNodes[]
else // multi-valued case: result is a record of nodes
{
let& outputNodesRecord = outputNodesParam.AsRef<IConfigRecord>();
for (let& nodeName : outputNodesRecord.GetMemberIds())
outputNodes[nodeName] = outputNodesRecord[nodeName].AsPtr<ComputationNodeBase>();
if (outputNodes.empty())
InvalidArgument("CloneFunction: At least one output nodes must be specified.");
}
// treatment of parameters
wstring parametersOption = config[L"parameters"];
if (parametersOption == L"learnable") parameterTreatment = ParameterTreatment::learnable;
else if (parametersOption == L"constant") parameterTreatment = ParameterTreatment::constant;
else if (parametersOption == L"shared") parameterTreatment = ParameterTreatment::shared;
else InvalidArgument("CloneFunction: 'parameters' option must be 'learnable', 'constant', or 'shared'.");
// determine which nodes must be cloned
// - intersection of:
// - all indirect inputs of the specified outputs
// - all dependents of leaves
// - where leaves are:
// - specified inputs
// - unless parameters="shared": all parameters the specified outputs depend on
// determine all indirect inputs of the specified outputs
vector<ComputationNodeBasePtr> roots;
for (let& outputNodeKV : outputNodes)
roots.push_back(outputNodeKV.second);
let allInputs = ComputationNodeBase::EnumerateNodes(roots);
// take the chance to validate inputNodes
let allInputsSet = set<ComputationNodeBasePtr>(allInputs.begin(), allInputs.end());
for (let& input : inputNodes)
if (allInputsSet.find(input) == allInputsSet.end())
InvalidArgument("CloneFunction: No specified output depends on the specified input %ls.", input->NodeDescription().c_str());
// TODO: Is this really always an error? Are there valid cases where one would over-specify possible input nodes, even if they are not used/needed?
// determine all leaves and their dependents
dependentSet = set<ComputationNodeBasePtr>(inputNodes.begin(), inputNodes.end()); // start with the specified inputs
bool iterate = true;
// determine all leaves and their dependents
// this needs outer loop to handle cyclic dependencies (PastValue) properly
while (iterate)
{
iterate = false;
for (let& node : allInputs)
{
// add parameters that are to be cloned to dependent set
if (parameterTreatment != ParameterTreatment::shared && node->Is<IFreezable>())
dependentSet.insert(node);
// if at least one input is in the dependent set then this node is, too
else
for (let& input : node->GetInputs())
if (dependentSet.find(input) != dependentSet.end() && dependentSet.find(node) == dependentSet.end())
{
dependentSet.insert(node);
iterate = true;
}
}
}
#if 0
for (let& node : dependentSet)
fprintf(stderr, "CloneFunction: cloning %ls\n", node->NodeDescription().c_str());
#endif
// ensure none of the specified inputs reference back into the cloned set
// The function we extract must be separable.
for (let& input : inputNodes)
for (let& node : ComputationNodeBase::EnumerateNodes(vector<ComputationNodeBasePtr>{input})) // check all indirect inputs of each specified input
{
let iter = dependentSet.find(input);
if (iter != dependentSet.end() && *iter != input)
InvalidArgument("CloneFunction: specified function input %ls recursively depends on %ls inside the function.", input->NodeDescription().c_str(), node->NodeDescription().c_str());
}
}
private:
// get the input nodes from the config
static vector<ComputationNodeBasePtr> GetInputNodes(const IConfigRecord& config)
{
return ScriptableObjects::ConfigArray::FlattenedVectorFrom<ComputationNodeBasePtr>(config[L"inputNodes"]);
}
// create an array of parameter names for all inputs
// These names are never actually used, but required by the ConfigLambda constructor, and maybe useful for debugging.
static vector<wstring> CreateParamNames(const IConfigRecord& config)
{
let inputNodes = GetInputNodes(config);
vector<wstring> paramNames(inputNodes.size());
for (size_t i = 0; i < paramNames.size(); i++)
paramNames[i] = msra::strfun::wstrprintf(L"input_%d", (int)i);
return paramNames;
}
private:
// -----------------------------------------------------------------------
// the cloning operation itself
// -----------------------------------------------------------------------
// execute the lambda
// This will clone all nodes that the outputNodes depend on, and rewire inputs matching inputNodes to inputArgs.
ConfigValuePtr DoClone(const vector<ConfigValuePtr>& inputValues, const std::wstring& exprName)
{
// resolve the input arguments
vector<ComputationNodeBasePtr> inputs;
for (let& inputValue : inputValues)
inputs.push_back(inputValue.ResolveValue());
assert(inputValues.size() == inputNodes.size()); // (this should have been checked by BrainScript)
// do some logging
fprintf(stderr, "CloneFunction: ");
for (size_t i = 0; i < inputs.size(); i++)
fprintf(stderr, "%s%ls : %ls", i == 0 ? "(" : ", ", inputs[i]->NodeName().c_str(), inputs[i]->OperationName().c_str());
fprintf(stderr, ") -> ");
let singleOutput = outputNodes.size() == 1 && outputNodes.begin()->first.empty();
if (singleOutput)
fprintf(stderr, "%ls\n", outputNodes.begin()->second->NodeDescription().c_str());
else
{
fprintf(stderr, "[\n");
for (let& outputNodesKV : outputNodes)
fprintf(stderr, " %ls = %ls : %ls\n", outputNodesKV.first.c_str(), outputNodesKV.second->NodeName().c_str(), outputNodesKV.second->OperationName().c_str());
fprintf(stderr, "]\n");
}
// clone everything in the dependent set
// - specified inputs get mapped to actual parameters
// - all others get duplicated
// Note that at this point, the "shared" option has already been considered,
// and is reflected in whether parameters are included or not in 'dependentSet'.
map<ComputationNodeBasePtr, ComputationNodeBasePtr> clonedNodes;
size_t numCloned = 0;
for (size_t i = 0; i < inputNodes.size(); i++)
clonedNodes[inputNodes[i]] = inputs[i];
for (let& node : dependentSet)
{
// if already there then it's an input that we just mapped above
if (clonedNodes.find(node) != clonedNodes.end())
continue;
// clone
ComputationNodeBasePtr newNode;
let newName = exprName + L"." + node->GetName();
newNode = node->Duplicate(newName, CopyNodeFlags::copyNodeAll);
// make it read-only if desired
if (parameterTreatment == ParameterTreatment::constant && newNode->Is<IFreezable>())
newNode->As<IFreezable>()->FreezeParameters();
// and that's our cloned node
clonedNodes[node] = newNode;
numCloned++;
}
#if 0
for (let& nodeKV : clonedNodes)
fprintf(stderr, "CloneFunction: cloning %ls -> %ls (%d -> %d)\n", nodeKV.first->NodeDescription().c_str(), nodeKV.second->NodeDescription().c_str(), (int)nodeKV.first->m_uniqueNumericId, (int)nodeKV.second->m_uniqueNumericId);
#endif
// all cloned nodes' inputs must be redirected if they reference a node that has been cloned as well
size_t numRelinks = 0; // (statistics: how many inputs have we relinked?)
for (let& clonedNodesKV : clonedNodes)
{
let& node = clonedNodesKV.second;
let& inputs2 = node->GetInputs();
for (size_t i = 0; i < inputs2.size(); i++)
{
fprintf(stderr, "%ls.inputs[%d] = %ls (%d)", node->NodeName().c_str(), (int)i, inputs2[i]->NodeName().c_str(), (int)inputs2[i]->m_uniqueNumericId);
let iter = clonedNodes.find(inputs2[i]);
if (iter == clonedNodes.end())
continue;
// input is also a cloned node: relink
node->SetInput(i, iter->second);
fprintf(stderr, " ==> %ls (%d)\n", inputs2[i]->NodeName().c_str(), (int)inputs2[i]->m_uniqueNumericId);
numRelinks++;
}
}
fprintf(stderr, "CloneFunction: Cloned %d nodes and relinked %d inputs.\n", (int)numCloned, (int)numRelinks);
// return the result
// - if outputNodes was specified as a single node, return a single node
// - if specified as a record, then return a record with the specified names
if (singleOutput)
{
return NodeToConfigValuePtr(clonedNodes.find(outputNodes.begin()->second)->second);
}
else
{
auto record = make_shared<ConfigRecord>(nullptr, [](const std::wstring & msg){ RuntimeError("CloneFunction: %ls", msg.c_str()); });
for (let& outputNodesKV : outputNodes)
record->Add(outputNodesKV.first, [](const wstring&){}, move(NodeToConfigValuePtr(clonedNodes.find(outputNodesKV.second)->second)));
auto valuep = ConfigValuePtr(record, [](const std::wstring& msg) { LogicError("CloneFunction: Unexpected failure: %ls", msg.c_str()); }, exprName);
return valuep;
}
}
ConfigValuePtr NodeToConfigValuePtr(ComputationNodeBasePtr node)
{
assert(node);
auto valuep = ConfigValuePtr(node, [](const std::wstring& msg) { LogicError("CloneFunction (NodeToConfigValuePtr): Unexpected failure: %ls", msg.c_str()); }, node->NodeName());
return valuep;
}
private:
// parameters
vector<ComputationNodeBasePtr> inputNodes;
map<wstring, ComputationNodeBasePtr> outputNodes;
ParameterTreatment parameterTreatment;
// other
set<ComputationNodeBasePtr> dependentSet; // set of nodes that outputNodes depend on
};
ScriptableObjects::ConfigurableRuntimeTypeRegister::Add<CloneFunctionConfigLambda> registerCloneFunctionConfigLambda(L"CloneFunctionConfigLambda");
}}}