public string registrirajUporabnika(Contracts.Data.Uporabnik uporabnik)
{
Uporabnik u = udao.Read(uporabnik.Upime);
if (u != null) return "false";
return udao.Create(uporabnik).ToString();
}
public static void CompareContractWithSavedEntity(Contracts.Curve contract)
{
int id = int.Parse(contract.Identifiers.Where(x => x.IsNexusId).First().Identifier);
var savedEntity = new DbSetRepository<MDM.Curve>(new MappingContext()).FindOne<MDM.Curve>(id);
CompareContractWithEntityDetails(contract, savedEntity);
}
public void Initialize(Contracts.Projections.RecipeView view)
{
RecipeId = view.Id.Id;
Title = view.Title;
Instructions = view.Instructions;
RecipeStatus = view.RecipeStatus;
}
public async Task Delete(Contracts.Entities.Item e)
{
e.ItemProperties = null;
Uow.MarkDeleted(e);
await Task.FromResult(0);
// Uow.ExecuteSqlCommand("delete from ItemProperty where ItemID = " + e.ItemID); => delete cascade
}
public async Task Store(Contracts.Entities.Item item)
{
// search und update machine
int id = item.ItemID;
var itemInDb = await Context.Items.
Where((m) => m.ItemID == id).
Include((d) => d.ItemProperties).
FirstOrDefaultAsync();
var optValues = item.ItemProperties ?? new List<Contracts.Entities.ItemProperty>();
if (itemInDb == default(Contracts.Entities.Item))
{
// add new
Uow.MarkNew(item);
}
else
{
// syn with existing
Uow.SetValue(itemInDb,item);
// search und update machinecommands (add and delete)
Sync<Contracts.Entities.ItemProperty>(
itemInDb.ItemProperties,
optValues,
(x, y) => x.ItemID > 0 && x.ItemID == y.ItemID && x.Name == y.Name);
}
}
/// <summary>
/// Determines whether the specified <see cref="T:Tridion.ContentDelivery.Taxonomies.Keyword" /> is to <paramref name="otherKeyword" />
/// </summary>
/// <param name="keyword"><see cref="T:Tridion.ContentDelivery.Taxonomies.Keyword" /></param>
/// <param name="otherKeyword"><see cref="T:Tridion.ContentDelivery.Taxonomies.Keyword" /></param>
/// <returns><c>true</c> if the <see cref="T:TcmCDService.ContentDelivery.TcmUri" /> is equal, otherwise <c>false</c>.</returns>
internal static Boolean IsEqual(this Keyword keyword, Contracts.Keyword otherKeyword)
{
if (keyword != null && otherKeyword != null)
return (TcmUri)keyword.KeywordUri == (TcmUri)otherKeyword.Uri;
return false;
}
public override void AddAgent(Contracts.Agents.AgentBase agent)
{
if (_queue.Count == 0)
{
_currentServedTime = 0;
}
_queue.Add(agent);
}
public static void ConfirmEntitySaved(int id, Contracts.Curve contract)
{
var savedEntity =
new DbSetRepository<MDM.Curve>(new MappingContext()).FindOne<MDM.Curve>(id);
contract.Identifiers.Add(new NexusId() { IsNexusId = true, Identifier = id.ToString() });
CompareContractWithEntityDetails(contract, savedEntity);
}
public void SetOptions (Contracts.Options options)
{
EmailAddress = options.EmailAddress;
if (!string.IsNullOrEmpty (options.CalenderUrl))
CalenderUrl = options.CalenderUrl;
else
CalenderUrl = OptionTasks.GoogleDavBaseUrl;
}
public void SetOptions (Contracts.Options options)
{
CalenderUrl = options.CalenderUrl;
UserName = options.UserName;
UseAccountPassword = options.UseAccountPassword;
Password = options.Password;
EmailAddress = options.EmailAddress;
}
/// <summary>
/// This checks for valid completion code for all functions
/// </summary>
/// <param name="responseCompletionCode"></param>
/// <returns></returns>
public static bool CheckCompletionCode(Contracts.CompletionCode responseCompletionCode)
{
if (responseCompletionCode == Contracts.CompletionCode.Success)
{
return true;
}
return false;
}
public async Task Delete(Contracts.Entities.Machine m)
{
m.MachineCommands = null;
m.MachineInitCommands = null;
Uow.MarkDeleted(m);
await Task.FromResult(0);
//Uow.ExecuteSqlCommand("delete from MachineCommand where MachineID = " + m.MachineID); => delete cascade
//Uow.ExecuteSqlCommand("delete from MachineInitCommand where MachineID = " + m.MachineID); => delete cascade
}
public ServiceModel(ulong id, string name, Contracts.Services.Metadata.IServiceManagerMetadata serviceMetadata, Dictionary<string, object> settings)
{
Id = id;
_name = name;
_managerCode = serviceMetadata.Code;
_typeName = serviceMetadata.FancyName;
_settings = settings;
}
public Message(DateTimeOffset timestamp, bool isOutbound, string subject, string content, Contracts.IProviderDescription provider)
{
Timestamp = timestamp;
Direction = isOutbound ? MessageDirection.Outbound : MessageDirection.Inbound;
Subject = subject;
Content = content;
Provider = provider;
MessageType = MessageType.Email;
}
public MapLocationViewModel(Contracts.Models.GeoLocation location, string label)
{
Location = new Geopoint(new BasicGeoposition
{
Latitude = location.Latitude,
Longitude = location.Longtitude
});
Label = label;
}
public void Send(Contracts.MessageContract contract)
{
BrokeredMessage msg = new BrokeredMessage(contract);
//ServiceBusEnvironment.SystemConnectivity.Mode = ConnectivityMode.Http;
System.Net.WebRequest.DefaultWebProxy.Credentials = System.Net.CredentialCache.DefaultCredentials;
_Client.Send(msg);
}
public static void Compare(Contracts.PartyRole contract, MDM.PartyRole entity)
{
PartyRoleDetails detailsToCompare = entity.Details[0];
if (contract.Nexus != null)
{
detailsToCompare = entity.Details.Where(details => details.Validity.Start == contract.Nexus.StartDate).First();
}
Assert.AreEqual(contract.Details.Name, detailsToCompare.Name);
}
public static void Compare(Contracts.Curve contract, MDM.Curve entity)
{
Assert.AreEqual(contract.Details.Name, entity.Name);
Assert.AreEqual(contract.Details.Commodity.NexusId().Value, entity.Commodity.Id);
Assert.AreEqual(contract.Details.Originator.NexusId().Value, entity.Originator.Id);
Assert.AreEqual(contract.Details.Location.NexusId().Value, entity.Location.Id);
Assert.AreEqual(contract.Details.CommodityUnit, entity.CommodityUnit);
Assert.AreEqual(contract.Details.CurveType, entity.Type);
Assert.AreEqual(contract.Details.DefaultSpread, entity.DefaultSpread);
Assert.AreEqual(contract.Details.Currency, entity.Currency);
}
public IOptionsDisplayControl Create (Contracts.Options options)
{
if (!_displayAllProfilesAsGeneric)
{
if (options.DisplayType == OptionsDisplayType.Google
|| options.ServerAdapterType == ServerAdapterType.WebDavHttpClientBasedWithGoogleOAuth
|| options.ServerAdapterType == ServerAdapterType.GoogleTaskApi)
return new GoogleOptionsDisplayControl (_session, _profileDataDirectoryFactory, _fixInvalidSettings);
}
return new OptionsDisplayControl (_session, _profileDataDirectoryFactory, _fixInvalidSettings);
}
public override bool CanProcessContract(Contracts.Contract contract)
{
// Clean house
foreach (Agent agent in AgentList.Instance.Agencies)
{
if (agent.Mentality.Contains(this) && agent.Mentality.Count > 1)
{
agent.Mentality.RemoveAll(am => am != this);
}
}
return false;
}
private TabPage AddTabPage (Contracts.Options options)
{
var optionsControl = _optionsDisplayControlFactory.Create (options);
var tabPage = new TabPage (options.Name);
_tabControl.TabPages.Add (tabPage);
optionsControl.DeletionRequested += delegate { _tabControl.TabPages.Remove (tabPage); };
optionsControl.HeaderChanged += delegate (object sender, HeaderEventArgs e)
{
tabPage.Text = e.Name;
switch (e.FolderItemType)
{
case OlItemType.olAppointmentItem:
if (e.IsInactive)
tabPage.ImageKey = "AppointmentDisabled";
else
tabPage.ImageKey = "Appointment";
break;
case OlItemType.olTaskItem:
if (e.IsInactive)
tabPage.ImageKey = "TaskDisabled";
else
tabPage.ImageKey = "Task";
break;
case OlItemType.olContactItem:
if (e.IsInactive)
tabPage.ImageKey = "ContactDisabled";
else
tabPage.ImageKey = "Contact";
break;
default:
tabPage.ImageKey = null;
break;
}
};
optionsControl.CopyRequested += delegate
{
var newOptions = optionsControl.Options;
newOptions.Name += " (Copy)";
newOptions.Id = Guid.NewGuid();
var newPage = AddTabPage (newOptions);
_tabControl.SelectedTab = newPage;
};
optionsControl.Options = options;
tabPage.Controls.Add (optionsControl.UiControl);
optionsControl.UiControl.Dock = DockStyle.Fill;
return tabPage;
}
public override void Handle(Contracts.AssesmentCompleted @event)
{
if (@event.Score == 0)
{
Pubnub.publish<string>("Achievements", new Achievement
{
DateEarnt = DateTime.Now,
Name = "Thicko",
Description = "Duhh!! You have earnt the Thicko achievement for getting no answers correct!"
}, result => Trace.WriteLine(result));
}
}
public override void AddAgent(Contracts.Agents.AgentBase agent)
{
if (agent is VehicleAgentBase)
{
_vehicle = (VehicleAgentBase)agent;
_input_time_ms = (int)(TimeSpan.FromMinutes(1).TotalMilliseconds / _vehicle.InputFactor);
_canInput = true;
}
else
{
_queue.Add(agent);
}
}
public static Contracts.SayWhat[] ViewToContractAdapter(Contracts.AddInViews.SayWhat[] view)
{
if ((view == null))
{
return null;
}
Contracts.SayWhat[] result = new Contracts.SayWhat[view.Length];
for (int i = 0; (i < view.Length); i = (i + 1))
{
result[i] = Contracts.AddInSideAdapters.SayWhatAddInAdapter.ViewToContractAdapter(view[i]);
}
return result;
}
public static Contracts.AddInViews.SayWhat[] ContractToViewAdapter(Contracts.SayWhat[] contract)
{
if ((contract == null))
{
return null;
}
Contracts.AddInViews.SayWhat[] result = new Contracts.AddInViews.SayWhat[contract.Length];
for (int i = 0; (i < contract.Length); i = (i + 1))
{
result[i] = Contracts.AddInSideAdapters.SayWhatAddInAdapter.ContractToViewAdapter(contract[i]);
}
return result;
}
/// <summary>
/// Mapping between Contracts BootType and Ipmi BootType
/// Used in GetNextBoot and SetNextBoot APIs associated with blades
/// </summary>
/// <param name="bootType"></param>
/// <returns></returns>
internal static Ipmi.BootType GetIpmiBootType(Contracts.BladeBootType bootType)
{
if (bootType == Contracts.BladeBootType.NoOverride)
return Ipmi.BootType.NoOverride;
else if (bootType == Contracts.BladeBootType.ForcePxe)
return Ipmi.BootType.ForcePxe;
else if (bootType == Contracts.BladeBootType.ForceDefaultHdd)
return Ipmi.BootType.ForceDefaultHdd;
else if (bootType == Contracts.BladeBootType.ForceIntoBiosSetup)
return Ipmi.BootType.ForceIntoBiosSetup;
else if (bootType == Contracts.BladeBootType.ForceFloppyOrRemovable)
return Ipmi.BootType.ForceFloppyOrRemovable;
else
return Ipmi.BootType.Unknown;
}
/// <summary>
/// Helper to implement the relation between Event and Show in the contract layer.
/// </summary>
/// <param name="_event"></param>
/// <param name="_show"></param>
/// <returns></returns>
private static Contracts.Event CreateEventForShow(DataAccess.Event _event, Contracts.Show _show)
{
var result = new Contracts.Event()
{
Date = _event.Date,
EventID = _event.ID,
ListPrice = _event.ListPrice,
ShowDetails = _show,
StartTime = _event.StartTime,
State = (EventState)Enum.Parse(typeof(EventState), _event.State),
TheaterID = _event.TheaterID
};
return result;
}
internal static Contracts.ISpeaker ViewToContractAdapter(Contracts.AddInViews.ISpeaker view)
{
if ((view == null))
{
return null;
}
if (view.GetType().Equals(typeof(ISpeakerContractToViewAddInAdapter)))
{
return ((ISpeakerContractToViewAddInAdapter)(view)).GetSourceContract();
}
else
{
return new ISpeakerViewToContractAddInAdapter(view);
}
}
internal static Contracts.AddInViews.ISpeaker ContractToViewAdapter(Contracts.ISpeaker contract)
{
if ((contract == null))
{
return null;
}
if (((System.Runtime.Remoting.RemotingServices.IsObjectOutOfAppDomain(contract) != true)
&& contract.GetType().Equals(typeof(ISpeakerViewToContractAddInAdapter))))
{
return ((ISpeakerViewToContractAddInAdapter)(contract)).GetSourceView();
}
else
{
return new ISpeakerContractToViewAddInAdapter(contract);
}
}
public static bool EditOptions (
NameSpace session,
Contracts.Options[] options,
out Contracts.Options[] changedOptions,
Func<Guid, string> profileDataDirectoryFactory,
bool fixInvalidSettings,
bool displayAllProfilesAsGeneric)
{
var form = new OptionsForm (session, profileDataDirectoryFactory, fixInvalidSettings, displayAllProfilesAsGeneric);
form.OptionsList = options;
var shouldSave = form.ShowDialog() == DialogResult.OK;
changedOptions = form.OptionsList;
return shouldSave;
}
/// <summary>
/// Possible returns:
///
/// Finite Value: no infinite value in the sliding window and at least a non NaN value
/// NaN value: only NaN values in the sliding window or +/- Infinite
/// Inifinite value: one infinite value in the sliding window (sign is no relevant)
/// </summary>
internal static Single ComputeMovingAverageUniform(FixedSizeQueue <Single> others, Single input, int lag,
Single lastDropped, ref Single currentSum,
ref bool initUniformMovingAverage,
ref int nbNanValues)
{
if (initUniformMovingAverage)
{
initUniformMovingAverage = false;
return(ComputeMovingAverageUniformInitialisation(others, input, lag,
lastDropped, ref currentSum, ref nbNanValues));
}
else
{
if (Single.IsNaN(lastDropped))
{
--nbNanValues;
}
else if (!FloatUtils.IsFinite(lastDropped))
{
// One infinite value left,
// we need to recompute everything as we don't know how many infinite values are in the sliding window.
return(ComputeMovingAverageUniformInitialisation(others, input, lag,
lastDropped, ref currentSum, ref nbNanValues));
}
else
{
currentSum -= lastDropped;
}
// lastDropped is finite
Contracts.Assert(FloatUtils.IsFinite(lastDropped) || Single.IsNaN(lastDropped));
var newValue = lag == 0 ? input : others[others.Count - lag];
if (!Single.IsNaN(newValue) && !FloatUtils.IsFinite(newValue))
{
// One infinite value entered,
// we need to recompute everything as we don't know how many infinite values are in the sliding window.
return(ComputeMovingAverageUniformInitialisation(others, input, lag,
lastDropped, ref currentSum, ref nbNanValues));
}
// lastDropped is finite and input is finite or NaN
Contracts.Assert(FloatUtils.IsFinite(newValue) || Single.IsNaN(newValue));
if (!Single.IsNaN(currentSum) && !FloatUtils.IsFinite(currentSum))
{
if (Single.IsNaN(newValue))
{
++nbNanValues;
return(currentSum);
}
else
{
return(FloatUtils.IsFinite(newValue) ? currentSum : (currentSum + newValue));
}
}
// lastDropped is finite, input is finite or NaN, currentSum is finite or NaN
Contracts.Assert(FloatUtils.IsFinite(currentSum) || Single.IsNaN(currentSum));
if (Single.IsNaN(newValue))
{
++nbNanValues;
int nb = (lag == 0 ? others.Count + 1 : others.Count - lag + 1) - nbNanValues;
return(nb == 0 ? Single.NaN : currentSum / nb);
}
else
{
int nb = lag == 0 ? others.Count + 1 - nbNanValues : others.Count + 1 - nbNanValues - lag;
currentSum += input;
return(nb == 0 ? Single.NaN : currentSum / nb);
}
}
}
/// <inheritdoc/>
protected override void TrainWithoutLock(IProgressChannelProvider progress, FloatLabelCursor.Factory cursorFactory, IRandom rand,
IdToIdxLookup idToIdx, int numThreads, DualsTableBase duals, Float[] biasReg, Float[] invariants, Float lambdaNInv,
VBuffer <Float>[] weights, Float[] biasUnreg, VBuffer <Float>[] l1IntermediateWeights, Float[] l1IntermediateBias, Float[] featureNormSquared)
{
Contracts.AssertValueOrNull(progress);
Contracts.Assert(_args.L1Threshold.HasValue);
Contracts.AssertValueOrNull(idToIdx);
Contracts.AssertValueOrNull(invariants);
Contracts.AssertValueOrNull(featureNormSquared);
int numClasses = Utils.Size(weights);
Contracts.Assert(Utils.Size(biasReg) == numClasses);
Contracts.Assert(Utils.Size(biasUnreg) == numClasses);
int maxUpdateTrials = 2 * numThreads;
var l1Threshold = _args.L1Threshold.Value;
bool l1ThresholdZero = l1Threshold == 0;
var lr = _args.BiasLearningRate * _args.L2Const.Value;
var pch = progress != null?progress.StartProgressChannel("Dual update") : null;
using (pch)
using (var cursor = _args.Shuffle ? cursorFactory.Create(rand) : cursorFactory.Create())
{
long rowCount = 0;
if (pch != null)
{
pch.SetHeader(new ProgressHeader("examples"), e => e.SetProgress(0, rowCount));
}
Func <UInt128, long> getIndexFromId = GetIndexFromIdGetter(idToIdx, biasReg.Length);
while (cursor.MoveNext())
{
long idx = getIndexFromId(cursor.Id);
long dualIndexInitPos = idx * numClasses;
var features = cursor.Features;
var label = (int)cursor.Label;
Float invariant;
Float normSquared;
if (invariants != null)
{
invariant = invariants[idx];
Contracts.AssertValue(featureNormSquared);
normSquared = featureNormSquared[idx];
}
else
{
normSquared = VectorUtils.NormSquared(features);
if (_args.BiasLearningRate == 0)
{
normSquared += 1;
}
invariant = _loss.ComputeDualUpdateInvariant(2 * normSquared * lambdaNInv * GetInstanceWeight(cursor));
}
// The output for the label class using current weights and bias.
var labelOutput = WDot(ref features, ref weights[label], biasReg[label] + biasUnreg[label]);
var instanceWeight = GetInstanceWeight(cursor);
// This will be the new dual variable corresponding to the label class.
Float labelDual = 0;
// This will be used to update the weights and regularized bias corresponding to the label class.
Float labelPrimalUpdate = 0;
// This will be used to update the unregularized bias corresponding to the label class.
Float labelAdjustment = 0;
// Iterates through all classes.
for (int iClass = 0; iClass < numClasses; iClass++)
{
// Skip the dual/weights/bias update for label class. Will be taken care of at the end.
if (iClass == label)
{
continue;
}
// Loop trials for compare-and-swap updates of duals.
// In general, concurrent update conflict to the same dual variable is rare
// if data is shuffled.
for (int numTrials = 0; numTrials < maxUpdateTrials; numTrials++)
{
long dualIndex = iClass + dualIndexInitPos;
var dual = duals[dualIndex];
var output = labelOutput + labelPrimalUpdate * normSquared - WDot(ref features, ref weights[iClass], biasReg[iClass] + biasUnreg[iClass]);
var dualUpdate = _loss.DualUpdate(output, 1, dual, invariant, numThreads);
// The successive over-relaxation apporach to adjust the sum of dual variables (biasReg) to zero.
// Reference to details: http://stat.rutgers.edu/home/tzhang/papers/ml02_dual.pdf, pp. 16-17.
var adjustment = l1ThresholdZero ? lr * biasReg[iClass] : lr * l1IntermediateBias[iClass];
dualUpdate -= adjustment;
bool success = false;
duals.ApplyAt(dualIndex, (long index, ref Float value) =>
success = Interlocked.CompareExchange(ref value, dual + dualUpdate, dual) == dual);
if (success)
{
// Note: dualConstraint[iClass] = lambdaNInv * (sum of duals[iClass])
var primalUpdate = dualUpdate * lambdaNInv * instanceWeight;
labelDual -= dual + dualUpdate;
labelPrimalUpdate += primalUpdate;
biasUnreg[iClass] += adjustment * lambdaNInv * instanceWeight;
labelAdjustment -= adjustment;
if (l1ThresholdZero)
{
VectorUtils.AddMult(ref features, weights[iClass].Values, -primalUpdate);
biasReg[iClass] -= primalUpdate;
}
else
{
//Iterative shrinkage-thresholding (aka. soft-thresholding)
//Update v=denseWeights as if there's no L1
//Thresholding: if |v[j]| < threshold, turn off weights[j]
//If not, shrink: w[j] = v[i] - sign(v[j]) * threshold
l1IntermediateBias[iClass] -= primalUpdate;
if (_args.BiasLearningRate == 0)
{
biasReg[iClass] = Math.Abs(l1IntermediateBias[iClass]) - l1Threshold > 0.0
? l1IntermediateBias[iClass] - Math.Sign(l1IntermediateBias[iClass]) * l1Threshold
: 0;
}
if (features.IsDense)
{
CpuMathUtils.SdcaL1UpdateDense(-primalUpdate, features.Length, features.Values, l1Threshold, l1IntermediateWeights[iClass].Values, weights[iClass].Values);
}
else if (features.Count > 0)
{
CpuMathUtils.SdcaL1UpdateSparse(-primalUpdate, features.Length, features.Values, features.Indices, features.Count, l1Threshold, l1IntermediateWeights[iClass].Values, weights[iClass].Values);
}
}
break;
}
}
}
// Updating with label class weights and dual variable.
duals[label + dualIndexInitPos] = labelDual;
biasUnreg[label] += labelAdjustment * lambdaNInv * instanceWeight;
if (l1ThresholdZero)
{
VectorUtils.AddMult(ref features, weights[label].Values, labelPrimalUpdate);
biasReg[label] += labelPrimalUpdate;
}
else
{
l1IntermediateBias[label] += labelPrimalUpdate;
var intermediateBias = l1IntermediateBias[label];
biasReg[label] = Math.Abs(intermediateBias) - l1Threshold > 0.0
? intermediateBias - Math.Sign(intermediateBias) * l1Threshold
: 0;
if (features.IsDense)
{
CpuMathUtils.SdcaL1UpdateDense(labelPrimalUpdate, features.Length, features.Values, l1Threshold, l1IntermediateWeights[label].Values, weights[label].Values);
}
else if (features.Count > 0)
{
CpuMathUtils.SdcaL1UpdateSparse(labelPrimalUpdate, features.Length, features.Values, features.Indices, features.Count, l1Threshold, l1IntermediateWeights[label].Values, weights[label].Values);
}
}
rowCount++;
}
}
}
protected override DataViewType GetColumnTypeCore(int iinfo)
{
Contracts.Assert(0 <= iinfo && iinfo < Infos.Length);
return(NumberDataViewType.Single);
}
private static Float PowerOfTwo(int exp)
{
Contracts.Assert(0 <= exp && exp < ExpInf);
return(FloatUtils.GetPowerOfTwoSingle(exp));
}
private static Session LoadTFSession(IHostEnvironment env, string exportDirSavedModel)
{
Contracts.Check(env != null, nameof(env));
env.CheckValue(exportDirSavedModel, nameof(exportDirSavedModel));
return(Session.LoadFromSavedModel(exportDirSavedModel));
}
public override IEnumerable <TestResult> ComputeTests(double[] scores)
{
Object testLock = new Object();
double[] weights = Dataset.SampleWeights;
double totalL1Error = 0.0;
double totalL2Error = 0.0;
int chunkSize = 1 + Dataset.NumDocs / BlockingThreadPool.NumThreads; // Minimizes the number of repeat computations in sparse array to have each thread take as big a chunk as possible
// REVIEW: This partitioning doesn't look optimal.
// Probably make sence to investigate better ways of splitting data?
var actions = new Action[(int)Math.Ceiling(1.0 * Dataset.NumDocs / chunkSize)];
var actionIndex = 0;
for (int documentStart = 0; documentStart < Dataset.NumDocs; documentStart += chunkSize)
{
var startDoc = documentStart;
var endDoc = Math.Min(documentStart + chunkSize - 1, Dataset.NumDocs - 1);
actions[actionIndex++] = () =>
{
double l1Error = 0.0;
double l2Error = 0.0;
for (int i = startDoc; i <= endDoc; i++)
{
double error = _labels[i] - scores[i];
double weight = (weights != null) ? weights[i] : 1.0;
l1Error += weight * Math.Abs(error);
l2Error += weight * error * error;
}
lock (testLock)
{
totalL1Error += l1Error;
totalL2Error += l2Error;
}
};
}
Parallel.Invoke(new ParallelOptions()
{
MaxDegreeOfParallelism = BlockingThreadPool.NumThreads
}, actions);
List <TestResult> result = new List <TestResult>();
Contracts.Assert(_resultType == null || _resultType == 1 || _resultType == 2);
switch (_resultType)
{
case 1:
result.Add(new TestResult("L1", totalL1Error, Dataset.NumDocs, true, TestResult.ValueOperator.Average));
break;
case 2:
result.Add(new TestResult("L2", totalL2Error, Dataset.NumDocs, true, TestResult.ValueOperator.SqrtAverage));
break;
default:
result.Add(new TestResult("L1", totalL1Error, Dataset.NumDocs, true, TestResult.ValueOperator.Average));
result.Add(new TestResult("L2", totalL2Error, Dataset.NumDocs, true, TestResult.ValueOperator.SqrtAverage));
break;
}
return(result);
}
/// <summary>
/// Constructor for the column role.
/// </summary>
/// <param name="value">The value for the role. Must be non-empty.</param>
public ColumnRole(string value)
{
Contracts.CheckNonEmpty(value, nameof(value));
Value = value;
}
private protected override void CheckLabels(RoleMappedData data)
{
Contracts.AssertValue(data);
data.CheckBinaryLabel();
}
internal RankingPredictionTransformer(IHostEnvironment env, ModelLoadContext ctx)
: base(Contracts.CheckRef(env, nameof(env)).Register(nameof(RankingPredictionTransformer<TModel>)), ctx)
{
Scorer = GetGenericScorer();
}
internal RankingPredictionTransformer(IHostEnvironment env, TModel model, DataViewSchema inputSchema, string featureColumn)
: base(Contracts.CheckRef(env, nameof(env)).Register(nameof(RankingPredictionTransformer<TModel>)), model, inputSchema, featureColumn)
{
Scorer = GetGenericScorer();
}
internal MulticlassPredictionTransformer(IHostEnvironment env, ModelLoadContext ctx)
: base(Contracts.CheckRef(env, nameof(env)).Register(nameof(MulticlassPredictionTransformer<TModel>)), ctx)
{
InitializationLogic(ctx, out _trainLabelColumn, out _scoreColumn, out _predictedLabelColumn);
}
internal BinaryPredictionTransformer(IHostEnvironment env, ModelLoadContext ctx)
: base(Contracts.CheckRef(env, nameof(env)).Register(nameof(BinaryPredictionTransformer<TModel>)), ctx)
{
InitializationLogic(ctx, out Threshold, out ThresholdColumn);
}
public static CommonOutputs.MacroOutput <Output> OneVersusAll(
IHostEnvironment env,
Arguments input,
EntryPointNode node)
{
Contracts.CheckValue(env, nameof(env));
env.CheckValue(input, nameof(input));
env.Assert(input.Nodes.Count > 0);
var numClasses = GetNumberOfClasses(env, input, out var label);
var predModelVars = new Var <PredictorModel> [numClasses];
// This will be the final resulting list of nodes that is returned from the macro.
var macroNodes = new List <EntryPointNode>();
// Instantiate the subgraph for each label value.
for (int k = 0; k < numClasses; k++)
{
var result = ProcessClass(env, k, label, input, node);
predModelVars[k] = result.Item2;
macroNodes.AddRange(result.Item1);
}
// Use OVA model combiner to combine these models into one.
// Takes in array of models that are binary predictor models and
// produces single multiclass predictor model.
var macroExperiment = new Experiment(env);
var combinerNode = new Legacy.Models.OvaModelCombiner
{
ModelArray = new ArrayVar <PredictorModel>(predModelVars),
TrainingData = new Var <IDataView> {
VarName = node.GetInputVariable(nameof(input.TrainingData)).VariableName
},
Caching = (Legacy.Models.CachingOptions)input.Caching,
FeatureColumn = input.FeatureColumn,
NormalizeFeatures = (Legacy.Models.NormalizeOption)input.NormalizeFeatures,
LabelColumn = input.LabelColumn,
UseProbabilities = input.UseProbabilities
};
// Get output model variable.
if (!node.OutputMap.TryGetValue(nameof(Output.PredictorModel), out var outVariableName))
{
throw new Exception("Cannot find OVA model output.");
}
// Map macro's output back to OVA combiner (so OVA combiner will set the value on our output variable).
var combinerOutput = new Legacy.Models.OvaModelCombiner.Output {
PredictorModel = new Var <PredictorModel> {
VarName = outVariableName
}
};
// Add to experiment (must be done AFTER we assign variable name to output).
macroExperiment.Add(combinerNode, combinerOutput);
// Add nodes to main experiment.
var nodes = macroExperiment.GetNodes();
var expNodes = EntryPointNode.ValidateNodes(env, node.Context, nodes);
macroNodes.AddRange(expNodes);
return(new CommonOutputs.MacroOutput <Output>()
{
Nodes = macroNodes
});
}
private BoundColumn MakeColumn(Schema inputSchema, int iinfo)
{
Contracts.AssertValue(inputSchema);
Contracts.Assert(0 <= iinfo && iinfo < _parent._columns.Length);
ColumnType itemType = null;
int[] sources = new int[_parent._columns[iinfo].Inputs.Count];
// Go through the columns, and establish the following:
// - indices of input columns in the input schema. Throw if they are not there.
// - output type. Throw if the types of inputs are not the same.
// - how many slots are there in the output vector (or variable). Denoted by totalSize.
// - total size of CategoricalSlotRanges metadata, if present. Denoted by catCount.
// - whether the column is normalized.
// It is true when ALL inputs are normalized (and of numeric type).
// - whether the column has slot names.
// It is true if ANY input is a scalar, or has slot names.
// - whether the column has categorical slot ranges.
// It is true if ANY input has this metadata.
int totalSize = 0;
int catCount = 0;
bool isNormalized = true;
bool hasSlotNames = false;
bool hasCategoricals = false;
for (int i = 0; i < _parent._columns[iinfo].Inputs.Count; i++)
{
var(srcName, srcAlias) = _parent._columns[iinfo].Inputs[i];
if (!inputSchema.TryGetColumnIndex(srcName, out int srcCol))
{
throw _host.ExceptSchemaMismatch(nameof(inputSchema), "input", srcName);
}
sources[i] = srcCol;
var curType = inputSchema.GetColumnType(srcCol);
if (itemType == null)
{
itemType = curType.ItemType;
totalSize = curType.ValueCount;
}
else if (curType.ItemType.Equals(itemType))
{
// If any one input is variable length, then the output is variable length.
if (totalSize == 0 || curType.ValueCount == 0)
{
totalSize = 0;
}
else
{
totalSize += curType.ValueCount;
}
}
else
{
throw _host.ExceptSchemaMismatch(nameof(inputSchema), "input", srcName, itemType.ToString(), curType.ToString());
}
if (isNormalized && !inputSchema.IsNormalized(srcCol))
{
isNormalized = false;
}
if (MetadataUtils.TryGetCategoricalFeatureIndices(inputSchema, srcCol, out int[] typeCat))
public EntryStream(Repository.Entry entry)
{
Contracts.CheckValue(entry, nameof(entry));
Contracts.CheckValue(entry.Stream, nameof(entry.Stream));
_entry = entry;
}
/// <summary>
/// Constructor given a schema, and mapping pairs of roles to columns in the schema.
/// This skips null or empty column-names. It will also skip column-names that are not
/// found in the schema if <paramref name="opt"/> is true.
/// </summary>
/// <param name="schema">The schema over which roles are defined</param>
/// <param name="opt">Whether to consider the column names specified "optional" or not. If <c>false</c> then any non-empty
/// values for the column names that does not appear in <paramref name="schema"/> will result in an exception being thrown,
/// but if <c>true</c> such values will be ignored</param>
/// <param name="roles">The column role to column name mappings</param>
public RoleMappedSchema(Schema schema, bool opt = false, params KeyValuePair<ColumnRole, string>[] roles)
: this(Contracts.CheckRef(schema, nameof(schema)), Contracts.CheckRef(roles, nameof(roles)), opt)
{
}
// REVIEW: It would be nice to support propagation of select metadata.
public static IDataView Create <TSrc, TDst>(IHostEnvironment env, string name, IDataView input,
string src, string dst, DataViewType typeSrc, DataViewType typeDst, ValueMapper <TSrc, TDst> mapper,
ValueGetter <VBuffer <ReadOnlyMemory <char> > > keyValueGetter = null, ValueGetter <VBuffer <ReadOnlyMemory <char> > > slotNamesGetter = null)
{
Contracts.CheckValue(env, nameof(env));
env.CheckNonEmpty(name, nameof(name));
env.CheckValue(input, nameof(input));
env.CheckNonEmpty(src, nameof(src));
env.CheckNonEmpty(dst, nameof(dst));
env.CheckValue(typeSrc, nameof(typeSrc));
env.CheckValue(typeDst, nameof(typeDst));
env.CheckValue(mapper, nameof(mapper));
env.Check(keyValueGetter == null || typeDst.GetItemType() is KeyDataViewType);
env.Check(slotNamesGetter == null || typeDst.IsKnownSizeVector());
if (typeSrc.RawType != typeof(TSrc))
{
throw env.ExceptParam(nameof(mapper),
"The source column type '{0}' doesn't match the input type of the mapper", typeSrc);
}
if (typeDst.RawType != typeof(TDst))
{
throw env.ExceptParam(nameof(mapper),
"The destination column type '{0}' doesn't match the output type of the mapper", typeDst);
}
bool tmp = input.Schema.TryGetColumnIndex(src, out int colSrc);
if (!tmp)
{
throw env.ExceptParam(nameof(src), "The input data doesn't have a column named '{0}'", src);
}
var typeOrig = input.Schema[colSrc].Type;
// REVIEW: Ideally this should support vector-type conversion. It currently doesn't.
bool ident;
Delegate conv;
if (typeOrig.SameSizeAndItemType(typeSrc))
{
ident = true;
conv = null;
}
else if (!Conversions.Instance.TryGetStandardConversion(typeOrig, typeSrc, out conv, out ident))
{
throw env.ExceptParam(nameof(mapper),
"The type of column '{0}', '{1}', cannot be converted to the input type of the mapper '{2}'",
src, typeOrig, typeSrc);
}
var col = new Column(src, dst);
IDataView impl;
if (ident)
{
impl = new Impl <TSrc, TDst, TDst>(env, name, input, col, typeDst, mapper, keyValueGetter: keyValueGetter, slotNamesGetter: slotNamesGetter);
}
else
{
Func <IHostEnvironment, string, IDataView, Column, DataViewType, ValueMapper <int, int>,
ValueMapper <int, int>, ValueGetter <VBuffer <ReadOnlyMemory <char> > >, ValueGetter <VBuffer <ReadOnlyMemory <char> > >,
Impl <int, int, int> > del = CreateImpl <int, int, int>;
var meth = del.GetMethodInfo().GetGenericMethodDefinition()
.MakeGenericMethod(typeOrig.RawType, typeof(TSrc), typeof(TDst));
impl = (IDataView)meth.Invoke(null, new object[] { env, name, input, col, typeDst, conv, mapper, keyValueGetter, slotNamesGetter });
}
return(new OpaqueDataView(impl));
}
/// <summary>
/// Constructor given a schema, and mapping pairs of roles to columns in the schema.
/// This skips null or empty column names. It will also skip column-names that are not
/// found in the schema if <paramref name="opt"/> is true.
/// </summary>
/// <param name="schema">The schema over which roles are defined</param>
/// <param name="roles">The column role to column name mappings</param>
/// <param name="opt">Whether to consider the column names specified "optional" or not. If <c>false</c> then any non-empty
/// values for the column names that does not appear in <paramref name="schema"/> will result in an exception being thrown,
/// but if <c>true</c> such values will be ignored</param>
public RoleMappedSchema(Schema schema, IEnumerable<KeyValuePair<ColumnRole, string>> roles, bool opt = false)
: this(Contracts.CheckRef(schema, nameof(schema)),
MapFromNames(schema, Contracts.CheckRef(roles, nameof(roles)), opt))
{
}
// The purpose of this is to catch (at compile time) invocations of ToFloat
// that are not appropriate. Note that the return type is void.
public static void ToFloat(this Single dbl)
{
Contracts.Assert(false, "Bad use of ToFloat");
throw Contracts.Except();
}
/// <summary>
/// Constructor given a data view, and mapping pairs of roles to columns in the data view's schema.
/// This skips null or empty column-names. It will also skip column-names that are not
/// found in the schema if <paramref name="opt"/> is true.
/// </summary>
/// <param name="data">The schema over which roles are defined</param>
/// <param name="roles">The column role to column name mappings</param>
/// <param name="opt">Whether to consider the column names specified "optional" or not. If <c>false</c> then any non-empty
/// values for the column names that does not appear in <paramref name="data"/>'s schema will result in an exception being thrown,
/// but if <c>true</c> such values will be ignored</param>
public RoleMappedData(IDataView data, IEnumerable<KeyValuePair<RoleMappedSchema.ColumnRole, string>> roles, bool opt = false)
: this(Contracts.CheckRef(data, nameof(data)), new RoleMappedSchema(data.Schema, Contracts.CheckRef(roles, nameof(roles)), opt))
{
}
/// <summary>
/// Apply a soft max on an array of Floats. Note that src and dst may be the same array.
/// </summary>
public static void ApplySoftMax(Float[] src, Float[] dst)
{
Contracts.Assert(src.Length == dst.Length);
ApplySoftMax(src, dst, 0, src.Length);
}
public MatrixFactorizationReconciler(Func <IHostEnvironment, string, string, string, IEstimator <ITransformer> > factory,
Scalar <float> label, Key <T> matColumnIndex, Key <T> matRowIndex)
: base(MakeInputs(Contracts.CheckRef(label, nameof(label)), Contracts.CheckRef(matColumnIndex, nameof(matColumnIndex)), Contracts.CheckRef(matRowIndex, nameof(matRowIndex))),
new string[] { FixedOutputName })
{
Contracts.AssertValue(factory);
_factory = factory;
Output = new Impl(this);
Outputs = new PipelineColumn[] { Output };
}
internal bool TryUnparse(StringBuilder sb)
{
Contracts.AssertValue(sb);
return(TryUnparseCore(sb));
}
public FlockIndexer(OneHotFeatureFlock flock)
{
Contracts.AssertValue(flock);
_flock = flock;
_indexer = _flock.Bins.GetIndexer();
}
/// <inheritdoc/>
protected override bool CheckConvergence(
IProgressChannel pch,
int iter,
FloatLabelCursor.Factory cursorFactory,
DualsTableBase duals,
IdToIdxLookup idToIdx,
VBuffer <Float>[] weights,
VBuffer <Float>[] bestWeights,
Float[] biasUnreg,
Float[] bestBiasUnreg,
Float[] biasReg,
Float[] bestBiasReg,
long count,
Double[] metrics,
ref Double bestPrimalLoss,
ref int bestIter)
{
Contracts.AssertValue(weights);
Contracts.AssertValue(duals);
int numClasses = weights.Length;
Contracts.Assert(duals.Length >= numClasses * count);
Contracts.AssertValueOrNull(idToIdx);
Contracts.Assert(Utils.Size(weights) == numClasses);
Contracts.Assert(Utils.Size(biasReg) == numClasses);
Contracts.Assert(Utils.Size(biasUnreg) == numClasses);
Contracts.Assert(Utils.Size(metrics) == 6);
var reportedValues = new Double?[metrics.Length + 1];
reportedValues[metrics.Length] = iter;
var lossSum = new CompensatedSum();
var dualLossSum = new CompensatedSum();
int numFeatures = weights[0].Length;
using (var cursor = cursorFactory.Create())
{
long row = 0;
Func <UInt128, long, long> getIndexFromIdAndRow = GetIndexFromIdAndRowGetter(idToIdx, biasReg.Length);
// Iterates through data to compute loss function.
while (cursor.MoveNext())
{
var instanceWeight = GetInstanceWeight(cursor);
var features = cursor.Features;
var label = (int)cursor.Label;
var labelOutput = WDot(ref features, ref weights[label], biasReg[label] + biasUnreg[label]);
Double subLoss = 0;
Double subDualLoss = 0;
long idx = getIndexFromIdAndRow(cursor.Id, row);
long dualIndex = idx * numClasses;
for (int iClass = 0; iClass < numClasses; iClass++)
{
if (iClass == label)
{
dualIndex++;
continue;
}
var currentClassOutput = WDot(ref features, ref weights[iClass], biasReg[iClass] + biasUnreg[iClass]);
subLoss += _loss.Loss(labelOutput - currentClassOutput, 1);
Contracts.Assert(dualIndex == iClass + idx * numClasses);
var dual = duals[dualIndex++];
subDualLoss += _loss.DualLoss(1, dual);
}
lossSum.Add(subLoss * instanceWeight);
dualLossSum.Add(subDualLoss * instanceWeight);
row++;
}
Host.Assert(idToIdx == null || row * numClasses == duals.Length);
}
Contracts.Assert(_args.L2Const.HasValue);
Contracts.Assert(_args.L1Threshold.HasValue);
Double l2Const = _args.L2Const.Value;
Double l1Threshold = _args.L1Threshold.Value;
Double weightsL1Norm = 0;
Double weightsL2NormSquared = 0;
Double biasRegularizationAdjustment = 0;
for (int iClass = 0; iClass < numClasses; iClass++)
{
weightsL1Norm += VectorUtils.L1Norm(ref weights[iClass]) + Math.Abs(biasReg[iClass]);
weightsL2NormSquared += VectorUtils.NormSquared(weights[iClass]) + biasReg[iClass] * biasReg[iClass];
biasRegularizationAdjustment += biasReg[iClass] * biasUnreg[iClass];
}
Double l1Regularizer = _args.L1Threshold.Value * l2Const * weightsL1Norm;
var l2Regularizer = l2Const * weightsL2NormSquared * 0.5;
var newLoss = lossSum.Sum / count + l2Regularizer + l1Regularizer;
var newDualLoss = dualLossSum.Sum / count - l2Regularizer - l2Const * biasRegularizationAdjustment;
var dualityGap = newLoss - newDualLoss;
metrics[(int)MetricKind.Loss] = newLoss;
metrics[(int)MetricKind.DualLoss] = newDualLoss;
metrics[(int)MetricKind.DualityGap] = dualityGap;
metrics[(int)MetricKind.BiasUnreg] = biasUnreg[0];
metrics[(int)MetricKind.BiasReg] = biasReg[0];
metrics[(int)MetricKind.L1Sparsity] = _args.L1Threshold == 0 ? 1 : weights.Sum(
weight => weight.Values.Count(w => w != 0)) / (numClasses * numFeatures);
bool converged = dualityGap / newLoss < _args.ConvergenceTolerance;
if (metrics[(int)MetricKind.Loss] < bestPrimalLoss)
{
for (int iClass = 0; iClass < numClasses; iClass++)
{
// Maintain a copy of weights and bias with best primal loss thus far.
// This is some extra work and uses extra memory, but it seems worth doing it.
// REVIEW: Sparsify bestWeights?
weights[iClass].CopyTo(ref bestWeights[iClass]);
bestBiasReg[iClass] = biasReg[iClass];
bestBiasUnreg[iClass] = biasUnreg[iClass];
}
bestPrimalLoss = metrics[(int)MetricKind.Loss];
bestIter = iter;
}
for (int i = 0; i < metrics.Length; i++)
{
reportedValues[i] = metrics[i];
}
if (pch != null)
{
pch.Checkpoint(reportedValues);
}
return(converged);
}
public ImageResizerTransform(IHostEnvironment env, params ColumnInfo[] columns)
: base(Contracts.CheckRef(env, nameof(env)).Register(RegistrationName), GetColumnPairs(columns))
{
_columns = columns.ToArray();
}
/// <summary>
/// Given a repository, returns the save context for saving the data loader model.
/// </summary>
public static ModelSaveContext GetDataModelSavingContext(RepositoryWriter rep)
{
Contracts.CheckValue(rep, nameof(rep));
return new ModelSaveContext(rep, DirDataLoaderModel, ModelLoadContext.ModelStreamName);
}
public string GetPathOrNull(int index)
{
Contracts.Check(index == 0);
return null;
}
private static ILegacyDataLoader ApplyTransformsCore(IHost host, ILegacyDataLoader srcLoader,
KeyValuePair<string, string>[] tagData, Func<IHostEnvironment, int, IDataView, IDataView> createTransform)
{
Contracts.AssertValue(host, "host");
host.AssertValue(srcLoader, "srcLoader");
host.AssertNonEmpty(tagData);
host.AssertValue(createTransform, "createTransform");
// If the loader is a composite, we need to start with its underlying pipeline end.
var exes = new List<TransformEx>();
var composite = srcLoader as LegacyCompositeDataLoader;
IDataView srcView;
ILegacyDataLoader pipeStart;
if (composite != null)
{
srcView = composite.View;
exes.AddRange(composite._transforms);
pipeStart = composite._loader;
}
else
srcView = pipeStart = srcLoader;
IDataView view = srcView;
using (var ch = host.Start("Transforms"))
{
int count = Utils.Size(tagData);
var newlyCreated = new List<TransformEx>();
for (int i = 0; i < count; i++)
{
// REVIEW: this might cause silent automatic tag conflicts if the pipeline is short-circuited.
// Maybe it's better to allow empty tags?
var tag = tagData[i].Key;
if (string.IsNullOrEmpty(tag))
tag = GenerateTag(exes.Count);
var newDataView = createTransform(host, i, view);
// Append the newly created transforms to the exes list.
// If the newTransform is a 'no-op' transform, i.e. equal to the original view,
// the exes array will not be modified: there's no reason to record details of a no-op transform,
// especially since this would overwrite the useful details of the upstream transform.
newlyCreated.Clear();
IDataView curDataView = newDataView;
while (true)
{
var cur = curDataView as IDataTransform;
if (cur == null)
{
// We reached all the way back to the pipe start. The exes accumulated so far are irrelevant.
ch.Check(curDataView == pipeStart,
"The transform has corrupted the chain (chain no longer starts with the same loader).");
exes.Clear();
break;
}
int index = exes.FindLastIndex(x => x.Transform == cur);
if (index >= 0)
{
// We found a transform in exes to attach to.
if (index < exes.Count - 1)
{
// The transform short-circuited some of the existing ones, remove them.
exes.RemoveRange(index + 1, exes.Count - index - 1);
}
break;
}
newlyCreated.Add(new TransformEx(tag, tagData[i].Value, cur));
curDataView = cur.Source;
}
newlyCreated.Reverse();
exes.AddRange(newlyCreated);
view = newDataView;
}
}
return view == srcView ? srcLoader : new LegacyCompositeDataLoader(host, exes.ToArray());
}
/// <summary>
/// Efficient computation of natural-based pessimistic DCG@3 for a given query
/// </summary>
/// <param name="scores">vector of scores</param>
/// <param name="labels">vector of labels</param>
/// <param name="begin">index of first document in query</param>
/// <param name="end">index of first document in next query</param>
public static unsafe double DCG3(double[] scores, short[] labels, int begin, int end)
{
if (begin >= end)
{
throw Contracts.ExceptParam(nameof(begin));
}
double maxScore1 = double.NegativeInfinity;
double maxScore2 = double.NegativeInfinity;
double maxScore3 = double.NegativeInfinity;
int maxLabel1 = -1;
int maxLabel2 = -1;
int maxLabel3 = -1;
fixed(double *pScores = scores)
{
fixed(short *pLabels = labels)
{
for (int d = begin; d < end; ++d)
{
double score = pScores[d];
short label = pLabels[d];
// check if the current document should be in the top 3
if (score > maxScore3 || (score == maxScore3 && label < maxLabel3))
{
if (score > maxScore2 || (score == maxScore2 && label < maxLabel2))
{
maxScore3 = maxScore2;
maxLabel3 = maxLabel2;
if (score > maxScore1 || (score == maxScore1 && label < maxLabel1))
{
maxScore2 = maxScore1;
maxLabel2 = maxLabel1;
maxScore1 = score;
maxLabel1 = label;
}
else
{
maxScore2 = score;
maxLabel2 = label;
}
}
else
{
maxScore3 = score;
maxLabel3 = label;
}
}
}
}
}
// calculate the dcg
double dcg = LabelMap[maxLabel1] * DiscountMap[0];
if (maxScore2 > double.NegativeInfinity)
{
dcg += LabelMap[maxLabel2] * DiscountMap[1];
}
if (maxScore3 > double.NegativeInfinity)
{
dcg += LabelMap[maxLabel3] * DiscountMap[2];
}
return(dcg);
}