Renaming OptimizationTolerance to fix a spelling error.#3199

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Merged
rogancarr merged 2 commits into from
Apr 5, 2019
Merged

Renaming OptimizationTolerance to fix a spelling error. #3199

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Renaming optimizationtolerance to fix a spelling bug.
Apr 4, 2019
c7bb57d
Update manifest and samples.
Apr 5, 2019
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2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.cs
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Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,

@TomFinleyTomFinleyApr 4, 2019

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So, this is desirable, but it is a breaking change, not sure what our procedure and thoughts are about that.

@rogancarrrogancarrApr 5, 2019

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I was going to see if we could Ask it into 1.0. I will ask.

@rogancarrrogancarrApr 5, 2019

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Process: Check into master: Cherry-pick into the release branch. PR into release branch will be part of ask-mode.

L2Regularization = 0.01f
};

Expand Down
2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.tt
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Original file line numberDiff line numberDiff line change
Expand Up@@ -5,7 +5,7 @@ string Trainer = "LbfgsLogisticRegression";
string TrainerOptions = @"LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,
L2Regularization = 0.01f
}";
bool IsCalibrated = true;
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.cs
View file
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Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -6,7 +6,7 @@ string Trainer = "LbfgsPoissonRegression";
string TrainerOptions = @"LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
12 changes: 6 additions & 6 deletions src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LbfgsPredictorBase.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -51,7 +51,7 @@ public abstract class OptionsBase : TrainerInputBaseWithWeight
ShortName = "ot, OptTol", SortOrder = 50)]
[TGUI(Label = "Optimization Tolerance", Description = "Threshold for optimizer convergence", SuggestedSweeps = "1e-4,1e-7")]
[TlcModule.SweepableDiscreteParamAttribute(new object[] { 1e-4f, 1e-7f })]
public float OptmizationTolerance = Defaults.OptimizationTolerance;
public float OptimizationTolerance = Defaults.OptimizationTolerance;

/// <summary>
/// Number of previous iterations to remember for estimating the Hessian. Lower values mean faster but less accurate estimates.
Expand DownExpand Up@@ -198,7 +198,7 @@ internal LbfgsTrainerBase(IHostEnvironment env,
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
},
Expand DownExpand Up@@ -226,20 +226,20 @@ internal LbfgsTrainerBase(IHostEnvironment env,
nameof(LbfgsTrainerOptions.NumberOfThreads), "Must be positive (or empty for default)");
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.OptimizationTolerance > 0, nameof(LbfgsTrainerOptions.OptimizationTolerance), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.HistorySize > 0, nameof(LbfgsTrainerOptions.HistorySize), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.MaximumNumberOfIterations > 0, nameof(LbfgsTrainerOptions.MaximumNumberOfIterations), "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.OptimizationTolerance <= 0), nameof(LbfgsTrainerOptions.OptimizationTolerance), "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;
OptTol = LbfgsTrainerOptions.OptimizationTolerance;
MemorySize =LbfgsTrainerOptions.HistorySize;
MaxIterations = LbfgsTrainerOptions.MaximumNumberOfIterations;
SgdInitializationTolerance = LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance;
Expand DownExpand Up@@ -278,7 +278,7 @@ private static TOptions ArgsInit(string featureColumn, SchemaShape.Column labelC
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
};
Expand Down
6 changes: 3 additions & 3 deletions test/BaselineOutput/Common/EntryPoints/core_manifest.json
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -13390,7 +13390,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -13711,7 +13711,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -14740,7 +14740,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand Down
2 changes: 1 addition & 1 deletion test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -40,7 +40,7 @@ public CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrato
.Append(ml.Clustering.Trainers.KMeans("Features"))
.Append(ml.Transforms.Concatenate("Features", "Features", "Score"))
.Append(ml.BinaryClassification.Trainers.LbfgsLogisticRegression(
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptmizationTolerance = 1e-3f, }));
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptimizationTolerance = 1e-3f, }));

var model = estimatorPipeline.Fit(input);
// Return the last model in the chain.
Expand Down
8 changes: 4 additions & 4 deletions test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -743,15 +743,15 @@ public void TestEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsLogisticRegressionBinaryTrainer.TrainBinary(ML, new LbfgsLogisticRegressionBinaryTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand DownExpand Up@@ -780,15 +780,15 @@ public void TestMulticlassEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all \u003cpre\u003e\u003ccode\u003e blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks"); } } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); } })(); (function(){ try { var __m = "github.com"; var __re = new RegExp('^' + "github\\.com" + '
Skip to content

Renaming OptimizationTolerance to fix a spelling error.#3199

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Merged
rogancarr merged 2 commits into from
Apr 5, 2019
Merged

Renaming OptimizationTolerance to fix a spelling error. #3199

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6151270
Renaming optimizationtolerance to fix a spelling bug.
Apr 4, 2019
c7bb57d
Update manifest and samples.
Apr 5, 2019
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2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.cs
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Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,

@TomFinleyTomFinleyApr 4, 2019

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So, this is desirable, but it is a breaking change, not sure what our procedure and thoughts are about that.

@rogancarrrogancarrApr 5, 2019

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I was going to see if we could Ask it into 1.0. I will ask.

@rogancarrrogancarrApr 5, 2019

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Process: Check into master: Cherry-pick into the release branch. PR into release branch will be part of ask-mode.

L2Regularization = 0.01f
};

Expand Down
2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -5,7 +5,7 @@ string Trainer = "LbfgsLogisticRegression";
string TrainerOptions = @"LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,
L2Regularization = 0.01f
}";
bool IsCalibrated = true;
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.tt
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Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -6,7 +6,7 @@ string Trainer = "LbfgsPoissonRegression";
string TrainerOptions = @"LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
12 changes: 6 additions & 6 deletions src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LbfgsPredictorBase.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -51,7 +51,7 @@ public abstract class OptionsBase : TrainerInputBaseWithWeight
ShortName = "ot, OptTol", SortOrder = 50)]
[TGUI(Label = "Optimization Tolerance", Description = "Threshold for optimizer convergence", SuggestedSweeps = "1e-4,1e-7")]
[TlcModule.SweepableDiscreteParamAttribute(new object[] { 1e-4f, 1e-7f })]
public float OptmizationTolerance = Defaults.OptimizationTolerance;
public float OptimizationTolerance = Defaults.OptimizationTolerance;

/// <summary>
/// Number of previous iterations to remember for estimating the Hessian. Lower values mean faster but less accurate estimates.
Expand DownExpand Up@@ -198,7 +198,7 @@ internal LbfgsTrainerBase(IHostEnvironment env,
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
},
Expand DownExpand Up@@ -226,20 +226,20 @@ internal LbfgsTrainerBase(IHostEnvironment env,
nameof(LbfgsTrainerOptions.NumberOfThreads), "Must be positive (or empty for default)");
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.OptimizationTolerance > 0, nameof(LbfgsTrainerOptions.OptimizationTolerance), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.HistorySize > 0, nameof(LbfgsTrainerOptions.HistorySize), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.MaximumNumberOfIterations > 0, nameof(LbfgsTrainerOptions.MaximumNumberOfIterations), "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.OptimizationTolerance <= 0), nameof(LbfgsTrainerOptions.OptimizationTolerance), "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;
OptTol = LbfgsTrainerOptions.OptimizationTolerance;
MemorySize =LbfgsTrainerOptions.HistorySize;
MaxIterations = LbfgsTrainerOptions.MaximumNumberOfIterations;
SgdInitializationTolerance = LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance;
Expand DownExpand Up@@ -278,7 +278,7 @@ private static TOptions ArgsInit(string featureColumn, SchemaShape.Column labelC
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
};
Expand Down
6 changes: 3 additions & 3 deletions test/BaselineOutput/Common/EntryPoints/core_manifest.json
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -13390,7 +13390,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -13711,7 +13711,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -14740,7 +14740,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand Down
2 changes: 1 addition & 1 deletion test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -40,7 +40,7 @@ public CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrato
.Append(ml.Clustering.Trainers.KMeans("Features"))
.Append(ml.Transforms.Concatenate("Features", "Features", "Score"))
.Append(ml.BinaryClassification.Trainers.LbfgsLogisticRegression(
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptmizationTolerance = 1e-3f, }));
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptimizationTolerance = 1e-3f, }));

var model = estimatorPipeline.Fit(input);
// Return the last model in the chain.
Expand Down
8 changes: 4 additions & 4 deletions test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -743,15 +743,15 @@ public void TestEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsLogisticRegressionBinaryTrainer.TrainBinary(ML, new LbfgsLogisticRegressionBinaryTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand DownExpand Up@@ -780,15 +780,15 @@ public void TestMulticlassEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Renaming OptimizationTolerance to fix a spelling error.#3199

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Merged
rogancarr merged 2 commits into from
Apr 5, 2019
Merged

Renaming OptimizationTolerance to fix a spelling error. #3199

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6151270
Renaming optimizationtolerance to fix a spelling bug.
Apr 4, 2019
c7bb57d
Update manifest and samples.
Apr 5, 2019
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2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,

@TomFinleyTomFinleyApr 4, 2019

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So, this is desirable, but it is a breaking change, not sure what our procedure and thoughts are about that.

@rogancarrrogancarrApr 5, 2019

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I was going to see if we could Ask it into 1.0. I will ask.

@rogancarrrogancarrApr 5, 2019

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Process: Check into master: Cherry-pick into the release branch. PR into release branch will be part of ask-mode.

L2Regularization = 0.01f
};

Expand Down
2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -5,7 +5,7 @@ string Trainer = "LbfgsLogisticRegression";
string TrainerOptions = @"LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,
L2Regularization = 0.01f
}";
bool IsCalibrated = true;
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -6,7 +6,7 @@ string Trainer = "LbfgsPoissonRegression";
string TrainerOptions = @"LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
12 changes: 6 additions & 6 deletions src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LbfgsPredictorBase.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -51,7 +51,7 @@ public abstract class OptionsBase : TrainerInputBaseWithWeight
ShortName = "ot, OptTol", SortOrder = 50)]
[TGUI(Label = "Optimization Tolerance", Description = "Threshold for optimizer convergence", SuggestedSweeps = "1e-4,1e-7")]
[TlcModule.SweepableDiscreteParamAttribute(new object[] { 1e-4f, 1e-7f })]
public float OptmizationTolerance = Defaults.OptimizationTolerance;
public float OptimizationTolerance = Defaults.OptimizationTolerance;

/// <summary>
/// Number of previous iterations to remember for estimating the Hessian. Lower values mean faster but less accurate estimates.
Expand DownExpand Up@@ -198,7 +198,7 @@ internal LbfgsTrainerBase(IHostEnvironment env,
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
},
Expand DownExpand Up@@ -226,20 +226,20 @@ internal LbfgsTrainerBase(IHostEnvironment env,
nameof(LbfgsTrainerOptions.NumberOfThreads), "Must be positive (or empty for default)");
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.OptimizationTolerance > 0, nameof(LbfgsTrainerOptions.OptimizationTolerance), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.HistorySize > 0, nameof(LbfgsTrainerOptions.HistorySize), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.MaximumNumberOfIterations > 0, nameof(LbfgsTrainerOptions.MaximumNumberOfIterations), "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.OptimizationTolerance <= 0), nameof(LbfgsTrainerOptions.OptimizationTolerance), "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;
OptTol = LbfgsTrainerOptions.OptimizationTolerance;
MemorySize =LbfgsTrainerOptions.HistorySize;
MaxIterations = LbfgsTrainerOptions.MaximumNumberOfIterations;
SgdInitializationTolerance = LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance;
Expand DownExpand Up@@ -278,7 +278,7 @@ private static TOptions ArgsInit(string featureColumn, SchemaShape.Column labelC
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
};
Expand Down
6 changes: 3 additions & 3 deletions test/BaselineOutput/Common/EntryPoints/core_manifest.json
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -13390,7 +13390,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -13711,7 +13711,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -14740,7 +14740,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand Down
2 changes: 1 addition & 1 deletion test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -40,7 +40,7 @@ public CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrato
.Append(ml.Clustering.Trainers.KMeans("Features"))
.Append(ml.Transforms.Concatenate("Features", "Features", "Score"))
.Append(ml.BinaryClassification.Trainers.LbfgsLogisticRegression(
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptmizationTolerance = 1e-3f, }));
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptimizationTolerance = 1e-3f, }));

var model = estimatorPipeline.Fit(input);
// Return the last model in the chain.
Expand Down
8 changes: 4 additions & 4 deletions test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -743,15 +743,15 @@ public void TestEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsLogisticRegressionBinaryTrainer.TrainBinary(ML, new LbfgsLogisticRegressionBinaryTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand DownExpand Up@@ -780,15 +780,15 @@ public void TestMulticlassEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length \u003e 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Renaming OptimizationTolerance to fix a spelling error.#3199

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Merged
rogancarr merged 2 commits into from
Apr 5, 2019
Merged

Renaming OptimizationTolerance to fix a spelling error. #3199

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6151270
Renaming optimizationtolerance to fix a spelling bug.
Apr 4, 2019
c7bb57d
Update manifest and samples.
Apr 5, 2019
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2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,

@TomFinleyTomFinleyApr 4, 2019

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So, this is desirable, but it is a breaking change, not sure what our procedure and thoughts are about that.

@rogancarrrogancarrApr 5, 2019

Copy link
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I was going to see if we could Ask it into 1.0. I will ask.

@rogancarrrogancarrApr 5, 2019

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Process: Check into master: Cherry-pick into the release branch. PR into release branch will be part of ask-mode.

L2Regularization = 0.01f
};

Expand Down
2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -5,7 +5,7 @@ string Trainer = "LbfgsLogisticRegression";
string TrainerOptions = @"LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,
L2Regularization = 0.01f
}";
bool IsCalibrated = true;
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -6,7 +6,7 @@ string Trainer = "LbfgsPoissonRegression";
string TrainerOptions = @"LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
12 changes: 6 additions & 6 deletions src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LbfgsPredictorBase.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -51,7 +51,7 @@ public abstract class OptionsBase : TrainerInputBaseWithWeight
ShortName = "ot, OptTol", SortOrder = 50)]
[TGUI(Label = "Optimization Tolerance", Description = "Threshold for optimizer convergence", SuggestedSweeps = "1e-4,1e-7")]
[TlcModule.SweepableDiscreteParamAttribute(new object[] { 1e-4f, 1e-7f })]
public float OptmizationTolerance = Defaults.OptimizationTolerance;
public float OptimizationTolerance = Defaults.OptimizationTolerance;

/// <summary>
/// Number of previous iterations to remember for estimating the Hessian. Lower values mean faster but less accurate estimates.
Expand DownExpand Up@@ -198,7 +198,7 @@ internal LbfgsTrainerBase(IHostEnvironment env,
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
},
Expand DownExpand Up@@ -226,20 +226,20 @@ internal LbfgsTrainerBase(IHostEnvironment env,
nameof(LbfgsTrainerOptions.NumberOfThreads), "Must be positive (or empty for default)");
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.OptimizationTolerance > 0, nameof(LbfgsTrainerOptions.OptimizationTolerance), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.HistorySize > 0, nameof(LbfgsTrainerOptions.HistorySize), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.MaximumNumberOfIterations > 0, nameof(LbfgsTrainerOptions.MaximumNumberOfIterations), "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.OptimizationTolerance <= 0), nameof(LbfgsTrainerOptions.OptimizationTolerance), "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;
OptTol = LbfgsTrainerOptions.OptimizationTolerance;
MemorySize =LbfgsTrainerOptions.HistorySize;
MaxIterations = LbfgsTrainerOptions.MaximumNumberOfIterations;
SgdInitializationTolerance = LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance;
Expand DownExpand Up@@ -278,7 +278,7 @@ private static TOptions ArgsInit(string featureColumn, SchemaShape.Column labelC
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
};
Expand Down
6 changes: 3 additions & 3 deletions test/BaselineOutput/Common/EntryPoints/core_manifest.json
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -13390,7 +13390,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -13711,7 +13711,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -14740,7 +14740,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand Down
2 changes: 1 addition & 1 deletion test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -40,7 +40,7 @@ public CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrato
.Append(ml.Clustering.Trainers.KMeans("Features"))
.Append(ml.Transforms.Concatenate("Features", "Features", "Score"))
.Append(ml.BinaryClassification.Trainers.LbfgsLogisticRegression(
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptmizationTolerance = 1e-3f, }));
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptimizationTolerance = 1e-3f, }));

var model = estimatorPipeline.Fit(input);
// Return the last model in the chain.
Expand Down
8 changes: 4 additions & 4 deletions test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -743,15 +743,15 @@ public void TestEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsLogisticRegressionBinaryTrainer.TrainBinary(ML, new LbfgsLogisticRegressionBinaryTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand DownExpand Up@@ -780,15 +780,15 @@ public void TestMulticlassEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content

Renaming OptimizationTolerance to fix a spelling error.#3199

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Merged
rogancarr merged 2 commits into from
Apr 5, 2019
Merged

Renaming OptimizationTolerance to fix a spelling error. #3199

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Show all changes
2 commits
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6151270
Renaming optimizationtolerance to fix a spelling bug.
Apr 4, 2019
c7bb57d
Update manifest and samples.
Apr 5, 2019
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2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,

@TomFinleyTomFinleyApr 4, 2019

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So, this is desirable, but it is a breaking change, not sure what our procedure and thoughts are about that.

@rogancarrrogancarrApr 5, 2019

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I was going to see if we could Ask it into 1.0. I will ask.

@rogancarrrogancarrApr 5, 2019

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Process: Check into master: Cherry-pick into the release branch. PR into release branch will be part of ask-mode.

L2Regularization = 0.01f
};

Expand Down
2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -5,7 +5,7 @@ string Trainer = "LbfgsLogisticRegression";
string TrainerOptions = @"LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,
L2Regularization = 0.01f
}";
bool IsCalibrated = true;
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -6,7 +6,7 @@ string Trainer = "LbfgsPoissonRegression";
string TrainerOptions = @"LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
12 changes: 6 additions & 6 deletions src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LbfgsPredictorBase.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -51,7 +51,7 @@ public abstract class OptionsBase : TrainerInputBaseWithWeight
ShortName = "ot, OptTol", SortOrder = 50)]
[TGUI(Label = "Optimization Tolerance", Description = "Threshold for optimizer convergence", SuggestedSweeps = "1e-4,1e-7")]
[TlcModule.SweepableDiscreteParamAttribute(new object[] { 1e-4f, 1e-7f })]
public float OptmizationTolerance = Defaults.OptimizationTolerance;
public float OptimizationTolerance = Defaults.OptimizationTolerance;

/// <summary>
/// Number of previous iterations to remember for estimating the Hessian. Lower values mean faster but less accurate estimates.
Expand DownExpand Up@@ -198,7 +198,7 @@ internal LbfgsTrainerBase(IHostEnvironment env,
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
},
Expand DownExpand Up@@ -226,20 +226,20 @@ internal LbfgsTrainerBase(IHostEnvironment env,
nameof(LbfgsTrainerOptions.NumberOfThreads), "Must be positive (or empty for default)");
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.OptimizationTolerance > 0, nameof(LbfgsTrainerOptions.OptimizationTolerance), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.HistorySize > 0, nameof(LbfgsTrainerOptions.HistorySize), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.MaximumNumberOfIterations > 0, nameof(LbfgsTrainerOptions.MaximumNumberOfIterations), "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.OptimizationTolerance <= 0), nameof(LbfgsTrainerOptions.OptimizationTolerance), "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;
OptTol = LbfgsTrainerOptions.OptimizationTolerance;
MemorySize =LbfgsTrainerOptions.HistorySize;
MaxIterations = LbfgsTrainerOptions.MaximumNumberOfIterations;
SgdInitializationTolerance = LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance;
Expand DownExpand Up@@ -278,7 +278,7 @@ private static TOptions ArgsInit(string featureColumn, SchemaShape.Column labelC
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
};
Expand Down
6 changes: 3 additions & 3 deletions test/BaselineOutput/Common/EntryPoints/core_manifest.json
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -13390,7 +13390,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -13711,7 +13711,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -14740,7 +14740,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand Down
2 changes: 1 addition & 1 deletion test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -40,7 +40,7 @@ public CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrato
.Append(ml.Clustering.Trainers.KMeans("Features"))
.Append(ml.Transforms.Concatenate("Features", "Features", "Score"))
.Append(ml.BinaryClassification.Trainers.LbfgsLogisticRegression(
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptmizationTolerance = 1e-3f, }));
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptimizationTolerance = 1e-3f, }));

var model = estimatorPipeline.Fit(input);
// Return the last model in the chain.
Expand Down
8 changes: 4 additions & 4 deletions test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -743,15 +743,15 @@ public void TestEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsLogisticRegressionBinaryTrainer.TrainBinary(ML, new LbfgsLogisticRegressionBinaryTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand DownExpand Up@@ -780,15 +780,15 @@ public void TestMulticlassEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Renaming OptimizationTolerance to fix a spelling error.#3199

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Merged
rogancarr merged 2 commits into from
Apr 5, 2019
Merged

Renaming OptimizationTolerance to fix a spelling error. #3199

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6151270
Renaming optimizationtolerance to fix a spelling bug.
Apr 4, 2019
c7bb57d
Update manifest and samples.
Apr 5, 2019
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2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,

@TomFinleyTomFinleyApr 4, 2019

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So, this is desirable, but it is a breaking change, not sure what our procedure and thoughts are about that.

@rogancarrrogancarrApr 5, 2019

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I was going to see if we could Ask it into 1.0. I will ask.

@rogancarrrogancarrApr 5, 2019

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Process: Check into master: Cherry-pick into the release branch. PR into release branch will be part of ask-mode.

L2Regularization = 0.01f
};

Expand Down
2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -5,7 +5,7 @@ string Trainer = "LbfgsLogisticRegression";
string TrainerOptions = @"LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,
L2Regularization = 0.01f
}";
bool IsCalibrated = true;
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -6,7 +6,7 @@ string Trainer = "LbfgsPoissonRegression";
string TrainerOptions = @"LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
12 changes: 6 additions & 6 deletions src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LbfgsPredictorBase.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -51,7 +51,7 @@ public abstract class OptionsBase : TrainerInputBaseWithWeight
ShortName = "ot, OptTol", SortOrder = 50)]
[TGUI(Label = "Optimization Tolerance", Description = "Threshold for optimizer convergence", SuggestedSweeps = "1e-4,1e-7")]
[TlcModule.SweepableDiscreteParamAttribute(new object[] { 1e-4f, 1e-7f })]
public float OptmizationTolerance = Defaults.OptimizationTolerance;
public float OptimizationTolerance = Defaults.OptimizationTolerance;

/// <summary>
/// Number of previous iterations to remember for estimating the Hessian. Lower values mean faster but less accurate estimates.
Expand DownExpand Up@@ -198,7 +198,7 @@ internal LbfgsTrainerBase(IHostEnvironment env,
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
},
Expand DownExpand Up@@ -226,20 +226,20 @@ internal LbfgsTrainerBase(IHostEnvironment env,
nameof(LbfgsTrainerOptions.NumberOfThreads), "Must be positive (or empty for default)");
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.OptimizationTolerance > 0, nameof(LbfgsTrainerOptions.OptimizationTolerance), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.HistorySize > 0, nameof(LbfgsTrainerOptions.HistorySize), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.MaximumNumberOfIterations > 0, nameof(LbfgsTrainerOptions.MaximumNumberOfIterations), "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.OptimizationTolerance <= 0), nameof(LbfgsTrainerOptions.OptimizationTolerance), "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;
OptTol = LbfgsTrainerOptions.OptimizationTolerance;
MemorySize =LbfgsTrainerOptions.HistorySize;
MaxIterations = LbfgsTrainerOptions.MaximumNumberOfIterations;
SgdInitializationTolerance = LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance;
Expand DownExpand Up@@ -278,7 +278,7 @@ private static TOptions ArgsInit(string featureColumn, SchemaShape.Column labelC
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
};
Expand Down
6 changes: 3 additions & 3 deletions test/BaselineOutput/Common/EntryPoints/core_manifest.json
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -13390,7 +13390,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -13711,7 +13711,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -14740,7 +14740,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand Down
2 changes: 1 addition & 1 deletion test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -40,7 +40,7 @@ public CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrato
.Append(ml.Clustering.Trainers.KMeans("Features"))
.Append(ml.Transforms.Concatenate("Features", "Features", "Score"))
.Append(ml.BinaryClassification.Trainers.LbfgsLogisticRegression(
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptmizationTolerance = 1e-3f, }));
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptimizationTolerance = 1e-3f, }));

var model = estimatorPipeline.Fit(input);
// Return the last model in the chain.
Expand Down
8 changes: 4 additions & 4 deletions test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -743,15 +743,15 @@ public void TestEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsLogisticRegressionBinaryTrainer.TrainBinary(ML, new LbfgsLogisticRegressionBinaryTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand DownExpand Up@@ -780,15 +780,15 @@ public void TestMulticlassEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Renaming OptimizationTolerance to fix a spelling error.#3199

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Merged
rogancarr merged 2 commits into from
Apr 5, 2019
Merged

Renaming OptimizationTolerance to fix a spelling error. #3199

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6151270
Renaming optimizationtolerance to fix a spelling bug.
Apr 4, 2019
c7bb57d
Update manifest and samples.
Apr 5, 2019
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2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,

@TomFinleyTomFinleyApr 4, 2019

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So, this is desirable, but it is a breaking change, not sure what our procedure and thoughts are about that.

@rogancarrrogancarrApr 5, 2019

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I was going to see if we could Ask it into 1.0. I will ask.

@rogancarrrogancarrApr 5, 2019

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Process: Check into master: Cherry-pick into the release branch. PR into release branch will be part of ask-mode.

L2Regularization = 0.01f
};

Expand Down
2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -5,7 +5,7 @@ string Trainer = "LbfgsLogisticRegression";
string TrainerOptions = @"LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,
L2Regularization = 0.01f
}";
bool IsCalibrated = true;
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.cs
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Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.tt
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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,7 +6,7 @@ string Trainer = "LbfgsPoissonRegression";
string TrainerOptions = @"LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
12 changes: 6 additions & 6 deletions src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LbfgsPredictorBase.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -51,7 +51,7 @@ public abstract class OptionsBase : TrainerInputBaseWithWeight
ShortName = "ot, OptTol", SortOrder = 50)]
[TGUI(Label = "Optimization Tolerance", Description = "Threshold for optimizer convergence", SuggestedSweeps = "1e-4,1e-7")]
[TlcModule.SweepableDiscreteParamAttribute(new object[] { 1e-4f, 1e-7f })]
public float OptmizationTolerance = Defaults.OptimizationTolerance;
public float OptimizationTolerance = Defaults.OptimizationTolerance;

/// <summary>
/// Number of previous iterations to remember for estimating the Hessian. Lower values mean faster but less accurate estimates.
Expand DownExpand Up@@ -198,7 +198,7 @@ internal LbfgsTrainerBase(IHostEnvironment env,
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
},
Expand DownExpand Up@@ -226,20 +226,20 @@ internal LbfgsTrainerBase(IHostEnvironment env,
nameof(LbfgsTrainerOptions.NumberOfThreads), "Must be positive (or empty for default)");
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.OptimizationTolerance > 0, nameof(LbfgsTrainerOptions.OptimizationTolerance), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.HistorySize > 0, nameof(LbfgsTrainerOptions.HistorySize), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.MaximumNumberOfIterations > 0, nameof(LbfgsTrainerOptions.MaximumNumberOfIterations), "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.OptimizationTolerance <= 0), nameof(LbfgsTrainerOptions.OptimizationTolerance), "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;
OptTol = LbfgsTrainerOptions.OptimizationTolerance;
MemorySize =LbfgsTrainerOptions.HistorySize;
MaxIterations = LbfgsTrainerOptions.MaximumNumberOfIterations;
SgdInitializationTolerance = LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance;
Expand DownExpand Up@@ -278,7 +278,7 @@ private static TOptions ArgsInit(string featureColumn, SchemaShape.Column labelC
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
};
Expand Down
6 changes: 3 additions & 3 deletions test/BaselineOutput/Common/EntryPoints/core_manifest.json
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Original file line numberDiff line numberDiff line change
Expand Up@@ -13390,7 +13390,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -13711,7 +13711,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -14740,7 +14740,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand Down
2 changes: 1 addition & 1 deletion test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -40,7 +40,7 @@ public CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrato
.Append(ml.Clustering.Trainers.KMeans("Features"))
.Append(ml.Transforms.Concatenate("Features", "Features", "Score"))
.Append(ml.BinaryClassification.Trainers.LbfgsLogisticRegression(
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptmizationTolerance = 1e-3f, }));
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptimizationTolerance = 1e-3f, }));

var model = estimatorPipeline.Fit(input);
// Return the last model in the chain.
Expand Down
8 changes: 4 additions & 4 deletions test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -743,15 +743,15 @@ public void TestEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsLogisticRegressionBinaryTrainer.TrainBinary(ML, new LbfgsLogisticRegressionBinaryTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand DownExpand Up@@ -780,15 +780,15 @@ public void TestMulticlassEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
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Merged
rogancarr merged 2 commits into from
Apr 5, 2019
Merged

Renaming OptimizationTolerance to fix a spelling error. #3199

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6151270
Renaming optimizationtolerance to fix a spelling bug.
Apr 4, 2019
c7bb57d
Update manifest and samples.
Apr 5, 2019
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2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,

@TomFinleyTomFinleyApr 4, 2019

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So, this is desirable, but it is a breaking change, not sure what our procedure and thoughts are about that.

@rogancarrrogancarrApr 5, 2019

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I was going to see if we could Ask it into 1.0. I will ask.

@rogancarrrogancarrApr 5, 2019

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Process: Check into master: Cherry-pick into the release branch. PR into release branch will be part of ask-mode.

L2Regularization = 0.01f
};

Expand Down
2 changes: 1 addition & 1 deletion ...ft.ML.Samples/Dynamic/Trainers/BinaryClassification/LbfgsLogisticRegressionWithOptions.tt
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Original file line numberDiff line numberDiff line change
Expand Up@@ -5,7 +5,7 @@ string Trainer = "LbfgsLogisticRegression";
string TrainerOptions = @"LbfgsLogisticRegressionBinaryTrainer.Options()
{
MaximumNumberOfIterations = 100,
OptmizationTolerance = 1e-8f,
OptimizationTolerance = 1e-8f,
L2Regularization = 0.01f
}";
bool IsCalibrated = true;
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -25,7 +25,7 @@ public static void Example()
var options = new LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
2 changes: 1 addition & 1 deletion ...les/Microsoft.ML.Samples/Dynamic/Trainers/Regression/LbfgsPoissonRegressionWithOptions.tt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -6,7 +6,7 @@ string Trainer = "LbfgsPoissonRegression";
string TrainerOptions = @"LbfgsPoissonRegressionTrainer.Options
{
// Reduce optimization tolerance to speed up training at the cost of accuracy.
OptmizationTolerance = 1e-4f,
OptimizationTolerance = 1e-4f,
// Decrease history size to speed up training at the cost of accuracy.
HistorySize = 30,
// Specify scale for initial weights.
Expand Down
12 changes: 6 additions & 6 deletions src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/LbfgsPredictorBase.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -51,7 +51,7 @@ public abstract class OptionsBase : TrainerInputBaseWithWeight
ShortName = "ot, OptTol", SortOrder = 50)]
[TGUI(Label = "Optimization Tolerance", Description = "Threshold for optimizer convergence", SuggestedSweeps = "1e-4,1e-7")]
[TlcModule.SweepableDiscreteParamAttribute(new object[] { 1e-4f, 1e-7f })]
public float OptmizationTolerance = Defaults.OptimizationTolerance;
public float OptimizationTolerance = Defaults.OptimizationTolerance;

/// <summary>
/// Number of previous iterations to remember for estimating the Hessian. Lower values mean faster but less accurate estimates.
Expand DownExpand Up@@ -198,7 +198,7 @@ internal LbfgsTrainerBase(IHostEnvironment env,
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
},
Expand DownExpand Up@@ -226,20 +226,20 @@ internal LbfgsTrainerBase(IHostEnvironment env,
nameof(LbfgsTrainerOptions.NumberOfThreads), "Must be positive (or empty for default)");
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.OptimizationTolerance > 0, nameof(LbfgsTrainerOptions.OptimizationTolerance), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.HistorySize > 0, nameof(LbfgsTrainerOptions.HistorySize), "Must be positive");
Host.CheckUserArg(LbfgsTrainerOptions.MaximumNumberOfIterations > 0, nameof(LbfgsTrainerOptions.MaximumNumberOfIterations), "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.OptimizationTolerance <= 0), nameof(LbfgsTrainerOptions.OptimizationTolerance), "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;
OptTol = LbfgsTrainerOptions.OptimizationTolerance;
MemorySize =LbfgsTrainerOptions.HistorySize;
MaxIterations = LbfgsTrainerOptions.MaximumNumberOfIterations;
SgdInitializationTolerance = LbfgsTrainerOptions.StochasticGradientDescentInitilaizationTolerance;
Expand DownExpand Up@@ -278,7 +278,7 @@ private static TOptions ArgsInit(string featureColumn, SchemaShape.Column labelC
ExampleWeightColumnName = weightColumn,
L1Regularization = l1Weight,
L2Regularization = l2Weight,
OptmizationTolerance = optimizationTolerance,
OptimizationTolerance = optimizationTolerance,
HistorySize = memorySize,
EnforceNonNegativity = enforceNoNegativity
};
Expand Down
6 changes: 3 additions & 3 deletions test/BaselineOutput/Common/EntryPoints/core_manifest.json
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Original file line numberDiff line numberDiff line change
Expand Up@@ -13390,7 +13390,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -13711,7 +13711,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand DownExpand Up@@ -14740,7 +14740,7 @@
}
},
{
"Name": "OptmizationTolerance",
"Name": "OptimizationTolerance",
"Type": "Float",
"Desc": "Tolerance parameter for optimization convergence. Low = slower, more accurate",
"Aliases": [
Expand Down
2 changes: 1 addition & 1 deletion test/Microsoft.ML.Benchmarks/KMeansAndLogisticRegressionBench.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -40,7 +40,7 @@ public CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrato
.Append(ml.Clustering.Trainers.KMeans("Features"))
.Append(ml.Transforms.Concatenate("Features", "Features", "Score"))
.Append(ml.BinaryClassification.Trainers.LbfgsLogisticRegression(
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptmizationTolerance = 1e-3f, }));
new LbfgsLogisticRegressionBinaryTrainer.Options { EnforceNonNegativity = true, OptimizationTolerance = 1e-3f, }));

var model = estimatorPipeline.Fit(input);
// Return the last model in the chain.
Expand Down
8 changes: 4 additions & 4 deletions test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -743,15 +743,15 @@ public void TestEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsLogisticRegressionBinaryTrainer.TrainBinary(ML, new LbfgsLogisticRegressionBinaryTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand DownExpand Up@@ -780,15 +780,15 @@ public void TestMulticlassEnsembleCombiner()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-4F,
OptimizationTolerance = 10e-4F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel,
LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options()
{
FeatureColumnName = "Features",
LabelColumnName = DefaultColumnNames.Label,
OptmizationTolerance = 10e-3F,
OptimizationTolerance = 10e-3F,
TrainingData = dataView,
NormalizeFeatures = NormalizeOption.No
}).PredictorModel
Expand Down