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Renaming IterationsToRemember to HistorySize for L-BFGS learners. #2894

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Mar 9, 2019
Merged

Renaming IterationsToRemember to HistorySize for L-BFGS learners. #2894

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Renaming IterationsToRemember to HistorySize for L-BFGS learners.
Mar 8, 2019
291b27e
Updating manifest
Mar 9, 2019
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14 changes: 7 additions & 7 deletions src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LbfgsPredictorBase.cs
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Expand Up @@ -54,7 +54,7 @@ public abstract class OptionsBase : TrainerInputBaseWithWeight
ShortName = "m, MemorySize", SortOrder = 50)]
[TGUI(Description = "Memory size for L-BFGS", SuggestedSweeps = "5,20,50")]
[TlcModule.SweepableDiscreteParamAttribute("MemorySize", new object[] { 5, 20, 50 })]
public int IterationsToRemember = Defaults.IterationsToRemember;
public int HistorySize = Defaults.HistorySize;
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@wschin wschin Mar 9, 2019

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nit:

Suggested change
public int HistorySize = Defaults.HistorySize;
public int HistoryLength = Defaults.HistorySize;

Size sounds like the number of parameters we can store.


/// <summary>
/// Number of iterations.
Expand Down Expand Up @@ -121,7 +121,7 @@ internal static class Defaults
public const float L2Regularization = 1;
public const float L1Regularization = 1;
public const float OptimizationTolerance = 1e-7f;
public const int IterationsToRemember = 20;
public const int HistorySize = 20;
public const int NumberOfIterations = int.MaxValue;
public const bool EnforceNonNegativity = false;
}
Expand Down Expand Up @@ -192,7 +192,7 @@ internal LbfgsTrainerBase(IHostEnvironment env,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
IterationsToRemember = memorySize,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
},
labelColumn)
Expand Down Expand Up @@ -220,20 +220,20 @@ internal LbfgsTrainerBase(IHostEnvironment env,
Host.CheckUserArg(LbfgsTrainerOptions.L2Regularization >= 0, nameof(LbfgsTrainerOptions.L2Regularization), "Must be non-negative");
Host.CheckUserArg(LbfgsTrainerOptions.L1Regularization >= 0, nameof(LbfgsTrainerOptions.L1Regularization), "Must be non-negative");
Host.CheckUserArg(LbfgsTrainerOptions.OptmizationTolerance > 0, nameof(LbfgsTrainerOptions.OptmizationTolerance), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.IterationsToRemember > 0, nameof(LbfgsTrainerOptions.IterationsToRemember), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.HistorySize > 0, nameof(LbfgsTrainerOptions.HistorySize), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.NumberOfIterations > 0, nameof(LbfgsTrainerOptions.NumberOfIterations), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance >= 0, nameof(LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance), "Must be non-negative");
Host.CheckUserArg(LbfgsTrainerOptions.NumberOfThreads == null || LbfgsTrainerOptions.NumberOfThreads.Value >= 0, nameof(LbfgsTrainerOptions.NumberOfThreads), "Must be non-negative");

Host.CheckParam(!(LbfgsTrainerOptions.L2Regularization < 0), nameof(LbfgsTrainerOptions.L2Regularization), "Must be non-negative, if provided.");
Host.CheckParam(!(LbfgsTrainerOptions.L1Regularization < 0), nameof(LbfgsTrainerOptions.L1Regularization), "Must be non-negative, if provided");
Host.CheckParam(!(LbfgsTrainerOptions.OptmizationTolerance <= 0), nameof(LbfgsTrainerOptions.OptmizationTolerance), "Must be positive, if provided.");
Host.CheckParam(!(LbfgsTrainerOptions.IterationsToRemember <= 0), nameof(LbfgsTrainerOptions.IterationsToRemember), "Must be positive, if provided.");
Host.CheckParam(!(LbfgsTrainerOptions.HistorySize <= 0), nameof(LbfgsTrainerOptions.HistorySize), "Must be positive, if provided.");

L2Weight = LbfgsTrainerOptions.L2Regularization;
L1Weight = LbfgsTrainerOptions.L1Regularization;
OptTol = LbfgsTrainerOptions.OptmizationTolerance;
MemorySize =LbfgsTrainerOptions.IterationsToRemember;
MemorySize =LbfgsTrainerOptions.HistorySize;
MaxIterations = LbfgsTrainerOptions.NumberOfIterations;
SgdInitializationTolerance = LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance;
Quiet = LbfgsTrainerOptions.Quiet;
Expand Down Expand Up @@ -272,7 +272,7 @@ private static TOptions ArgsInit(string featureColumn, SchemaShape.Column labelC
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
IterationsToRemember = memorySize,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
};

Expand Down
2 changes: 1 addition & 1 deletion src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/LogisticRegression.cs
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Expand Up @@ -83,7 +83,7 @@ internal LogisticRegression(IHostEnvironment env,
float l1Weight = Options.Defaults.L1Regularization,
float l2Weight = Options.Defaults.L2Regularization,
float optimizationTolerance = Options.Defaults.OptimizationTolerance,
int memorySize = Options.Defaults.IterationsToRemember,
int memorySize = Options.Defaults.HistorySize,
bool enforceNoNegativity = Options.Defaults.EnforceNonNegativity)
: base(env, featureColumn, TrainerUtils.MakeBoolScalarLabel(labelColumn), weights,
l1Weight, l2Weight, optimizationTolerance, memorySize, enforceNoNegativity)
Expand Down
2 changes: 1 addition & 1 deletion ...Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs
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Expand Up @@ -90,7 +90,7 @@ internal MulticlassLogisticRegression(IHostEnvironment env,
float l1Weight = Options.Defaults.L1Regularization,
float l2Weight = Options.Defaults.L2Regularization,
float optimizationTolerance = Options.Defaults.OptimizationTolerance,
int memorySize = Options.Defaults.IterationsToRemember,
int memorySize = Options.Defaults.HistorySize,
bool enforceNoNegativity = Options.Defaults.EnforceNonNegativity)
: base(env, featureColumn, TrainerUtils.MakeU4ScalarColumn(labelColumn), weights, l1Weight, l2Weight, optimizationTolerance, memorySize, enforceNoNegativity)
{
Expand Down
2 changes: 1 addition & 1 deletion src/Microsoft.ML.StandardLearners/Standard/PoissonRegression/PoissonRegression.cs
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Expand Up @@ -58,7 +58,7 @@ internal PoissonRegression(IHostEnvironment env,
float l1Weight = Options.Defaults.L1Regularization,
float l2Weight = Options.Defaults.L2Regularization,
float optimizationTolerance = Options.Defaults.OptimizationTolerance,
int memorySize = Options.Defaults.IterationsToRemember,
int memorySize = Options.Defaults.HistorySize,
bool enforceNoNegativity = Options.Defaults.EnforceNonNegativity)
: base(env, featureColumn, TrainerUtils.MakeR4ScalarColumn(labelColumn), weights,
l1Weight, l2Weight, optimizationTolerance, memorySize, enforceNoNegativity)
Expand Down
18 changes: 9 additions & 9 deletions src/Microsoft.ML.StandardLearners/StandardLearnersCatalog.cs
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Expand Up @@ -453,7 +453,7 @@ public static OnlineGradientDescentTrainer OnlineGradientDescent(this Regression
/// <param name="enforceNonNegativity">Enforce non-negative weights.</param>
/// <param name="l1Regularization">Weight of L1 regularization term.</param>
/// <param name="l2Regularization">Weight of L2 regularization term.</param>
/// <param name="iterationsToRemember">Memory size for <see cref="Trainers.LogisticRegression"/>. Low=faster, less accurate.</param>
/// <param name="historySize">Memory size for <see cref="Trainers.LogisticRegression"/>. Low=faster, less accurate.</param>
/// <param name="optimizationTolerance">Threshold for optimizer convergence.</param>
/// <example>
/// <format type="text/markdown">
Expand All @@ -469,12 +469,12 @@ public static LogisticRegression LogisticRegression(this BinaryClassificationCat
float l1Regularization = LROptions.Defaults.L1Regularization,
float l2Regularization = LROptions.Defaults.L2Regularization,
float optimizationTolerance = LROptions.Defaults.OptimizationTolerance,
int iterationsToRemember = LROptions.Defaults.IterationsToRemember,
int historySize = LROptions.Defaults.HistorySize,
bool enforceNonNegativity = LROptions.Defaults.EnforceNonNegativity)
{
Contracts.CheckValue(catalog, nameof(catalog));
var env = CatalogUtils.GetEnvironment(catalog);
return new LogisticRegression(env, labelColumnName, featureColumnName, exampleWeightColumnName, l1Regularization, l2Regularization, optimizationTolerance, iterationsToRemember, enforceNonNegativity);
return new LogisticRegression(env, labelColumnName, featureColumnName, exampleWeightColumnName, l1Regularization, l2Regularization, optimizationTolerance, historySize, enforceNonNegativity);
}

/// <summary>
Expand All @@ -501,7 +501,7 @@ public static LogisticRegression LogisticRegression(this BinaryClassificationCat
/// <param name="l1Regularization">Weight of L1 regularization term.</param>
/// <param name="l2Regularization">Weight of L2 regularization term.</param>
/// <param name="optimizationTolerance">Threshold for optimizer convergence.</param>
/// <param name="iterationsToRemember">Memory size for <see cref="Microsoft.ML.Trainers.PoissonRegression"/>. Low=faster, less accurate.</param>
/// <param name="historySize">Memory size for <see cref="Microsoft.ML.Trainers.PoissonRegression"/>. Low=faster, less accurate.</param>
/// <param name="enforceNonNegativity">Enforce non-negative weights.</param>
public static PoissonRegression PoissonRegression(this RegressionCatalog.RegressionTrainers catalog,
string labelColumnName = DefaultColumnNames.Label,
Expand All @@ -510,12 +510,12 @@ public static PoissonRegression PoissonRegression(this RegressionCatalog.Regress
float l1Regularization = LROptions.Defaults.L1Regularization,
float l2Regularization = LROptions.Defaults.L2Regularization,
float optimizationTolerance = LROptions.Defaults.OptimizationTolerance,
int iterationsToRemember = LROptions.Defaults.IterationsToRemember,
int historySize = LROptions.Defaults.HistorySize,
bool enforceNonNegativity = LROptions.Defaults.EnforceNonNegativity)
{
Contracts.CheckValue(catalog, nameof(catalog));
var env = CatalogUtils.GetEnvironment(catalog);
return new PoissonRegression(env, labelColumnName, featureColumnName, exampleWeightColumnName, l1Regularization, l2Regularization, optimizationTolerance, iterationsToRemember, enforceNonNegativity);
return new PoissonRegression(env, labelColumnName, featureColumnName, exampleWeightColumnName, l1Regularization, l2Regularization, optimizationTolerance, historySize, enforceNonNegativity);
}

/// <summary>
Expand All @@ -542,7 +542,7 @@ public static PoissonRegression PoissonRegression(this RegressionCatalog.Regress
/// <param name="enforceNonNegativity">Enforce non-negative weights.</param>
/// <param name="l1Regularization">Weight of L1 regularization term.</param>
/// <param name="l2Regularization">Weight of L2 regularization term.</param>
/// <param name="iterationsToRemember">Memory size for <see cref="Microsoft.ML.Trainers.MulticlassLogisticRegression"/>. Low=faster, less accurate.</param>
/// <param name="historySize">Memory size for <see cref="Microsoft.ML.Trainers.MulticlassLogisticRegression"/>. Low=faster, less accurate.</param>
/// <param name="optimizationTolerance">Threshold for optimizer convergence.</param>
public static MulticlassLogisticRegression LogisticRegression(this MulticlassClassificationCatalog.MulticlassClassificationTrainers catalog,
string labelColumnName = DefaultColumnNames.Label,
Expand All @@ -551,12 +551,12 @@ public static MulticlassLogisticRegression LogisticRegression(this MulticlassCla
float l1Regularization = LROptions.Defaults.L1Regularization,
float l2Regularization = LROptions.Defaults.L2Regularization,
float optimizationTolerance = LROptions.Defaults.OptimizationTolerance,
int iterationsToRemember = LROptions.Defaults.IterationsToRemember,
int historySize = LROptions.Defaults.HistorySize,
bool enforceNonNegativity = LROptions.Defaults.EnforceNonNegativity)
{
Contracts.CheckValue(catalog, nameof(catalog));
var env = CatalogUtils.GetEnvironment(catalog);
return new MulticlassLogisticRegression(env, labelColumnName, featureColumnName, exampleWeightColumnName, l1Regularization, l2Regularization, optimizationTolerance, iterationsToRemember, enforceNonNegativity);
return new MulticlassLogisticRegression(env, labelColumnName, featureColumnName, exampleWeightColumnName, l1Regularization, l2Regularization, optimizationTolerance, historySize, enforceNonNegativity);
}

/// <summary>
Expand Down
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