[AutoML] Fix error handling in CLI. #3618

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Merged
srsaggam merged 2 commits into from
Apr 29, 2019
Merged

[AutoML] Fix error handling in CLI. #3618

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a5008a8
fix error handling
srsaggam Apr 29, 2019
c40cf93
renaming variables
srsaggam Apr 29, 2019
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76 changes: 62 additions & 14 deletions src/mlnet/CodeGenerator/CodeGenerationHelper.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -3,21 +3,17 @@
// See the LICENSE file in the project root for more information.

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.IO;
using System.Linq;
using System.Runtime.ExceptionServices;
using System.Threading;
using System.Threading.Tasks;
using Microsoft.ML.AutoML;
using Microsoft.ML.CLI.CodeGenerator.CSharp;
using Microsoft.ML.CLI.Data;
using Microsoft.ML.CLI.ShellProgressBar;
using Microsoft.ML.CLI.Utilities;
using Microsoft.ML.Data;
using NLog;
using NLog.Targets;

namespace Microsoft.ML.CLI.CodeGenerator
{
Expand DownExpand Up@@ -81,7 +77,7 @@ public void GenerateCode()
// i.e there is no common class/interface to handle all three tasks together.

ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult = default;
ExperimentResult<MulticlassClassificationMetrics> multiExperimentResult = default;
ExperimentResult<MulticlassClassificationMetrics> multiclassExperimentResult = default;
ExperimentResult<RegressionMetrics> regressionExperimentResult = default;
if (verboseLevel > LogLevel.Trace)
{
Expand DownExpand Up@@ -111,20 +107,22 @@ public void GenerateCode()

if (verboseLevel > LogLevel.Trace && !Console.IsOutputRedirected)
{
Exception ex = null;
using (var pbar = new FixedDurationBar(wait, "", options))
{
pbar.Message = Strings.WaitingForFirstIteration;
Thread t = default;
switch (taskKind)
{
// TODO: It may be a good idea to convert the below Threads to Tasks or get rid of this progress bar all together and use an existing one in opensource.
case TaskKind.BinaryClassification:
t = new Thread(() => binaryExperimentResult = automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar));
t = new Thread(() => SafeExecute(() => automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar), out ex, out binaryExperimentResult, pbar));
break;
case TaskKind.Regression:
t = new Thread(() => regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar));
t = new Thread(() => SafeExecute(() => automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar), out ex, out regressionExperimentResult, pbar));
break;
case TaskKind.MulticlassClassification:
t = new Thread(() => multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar));
t = new Thread(() => SafeExecute(() => automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar), out ex, out multiclassExperimentResult, pbar));
break;
default:
logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand All@@ -147,6 +145,10 @@ public void GenerateCode()
pbar.Message = originalMessage;
}
}
if (ex != null)
{
throw ex;
}
}
}
else
Expand All@@ -160,7 +162,7 @@ public void GenerateCode()
regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric);
break;
case TaskKind.MulticlassClassification:
multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
multiclassExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
break;
default:
logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand DownExpand Up@@ -204,11 +206,11 @@ public void GenerateCode()
ConsolePrinter.PrintIterationSummary(regressionExperimentResult.RunDetails, new RegressionExperimentSettings().OptimizingMetric, 5);
break;
case TaskKind.MulticlassClassification:
var bestMultiIteration = multiExperimentResult.BestRun;
bestPipeline = bestMultiIteration.Pipeline;
bestModel = bestMultiIteration.Model;
ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiExperimentResult.RunDetails.Count());
ConsolePrinter.PrintIterationSummary(multiExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
var bestMulticlassIteration = multiclassExperimentResult.BestRun;
bestPipeline = bestMulticlassIteration.Pipeline;
bestModel = bestMulticlassIteration.Model;
ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiclassExperimentResult.RunDetails.Count());
ConsolePrinter.PrintIterationSummary(multiclassExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
break;
}
}
Expand DownExpand Up@@ -278,5 +280,51 @@ private void ConsumeAutoMLSDKLogs(MLContext context)
}
};
}

private void SafeExecute(Func<ExperimentResult<BinaryClassificationMetrics>> p, out Exception ex, out ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult, FixedDurationBar pbar)
{
try
{
binaryExperimentResult = p.Invoke();
ex = null;
}
catch (Exception e)
{
ex = e;
binaryExperimentResult = null;
return;
}
}

private void SafeExecute(Func<ExperimentResult<RegressionMetrics>> p, out Exception ex, out ExperimentResult<RegressionMetrics> regressionExperimentResult, FixedDurationBar pbar)
{
try
{
regressionExperimentResult = p.Invoke();
ex = null;
}
catch (Exception e)
{
ex = e;
regressionExperimentResult = null;
return;
}
}

private void SafeExecute(Func<ExperimentResult<MulticlassClassificationMetrics>> p, out Exception ex, out ExperimentResult<MulticlassClassificationMetrics> multiClassExperimentResult, FixedDurationBar pbar)
{
try
{
multiClassExperimentResult = p.Invoke();
ex = null;
}
catch (Exception e)
{
ex = e;
multiClassExperimentResult = null;
pbar.Dispose(); // or ((ManualResetEvent)pbar.CompletedHandle).Set();
return;
}
}
}
}
1 change: 1 addition & 0 deletions src/mlnet/ProgressBar/ProgressBar.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -356,6 +356,7 @@ public void Dispose()
_timer?.Dispose();
_timer = null;
foreach (var c in this.Children) c.Dispose();
OnDone();
}
}
}
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 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
[AutoML] Fix error handling in CLI. #3618

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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privacy statement. We’ll occasionally send you account related emails.

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Sign in
to your account

 Merged

srsaggam
merged 2 commits into

from

Apr 29, 2019
 Merged


[AutoML] Fix error handling in CLI. #3618
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a5008a8

fix error handling


srsaggam Apr 29, 2019
c40cf93

renaming variables


srsaggam Apr 29, 2019

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76 changes: 62 additions & 14 deletions
src/mlnet/CodeGenerator/CodeGenerationHelper.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,21 +3,17 @@
// See the LICENSE file in the project root for more information.

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.IO;
using System.Linq;
using System.Runtime.ExceptionServices;
using System.Threading;
using System.Threading.Tasks;
using Microsoft.ML.AutoML;
using Microsoft.ML.CLI.CodeGenerator.CSharp;
using Microsoft.ML.CLI.Data;
using Microsoft.ML.CLI.ShellProgressBar;
using Microsoft.ML.CLI.Utilities;
using Microsoft.ML.Data;
using NLog;
using NLog.Targets;

namespace Microsoft.ML.CLI.CodeGenerator
{
Expand DownExpand Up@@ -81,7 +77,7 @@ public void GenerateCode()
 // i.e there is no common class/interface to handle all three tasks together.

 ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiclassExperimentResult = default;
 ExperimentResult<RegressionMetrics> regressionExperimentResult = default;
 if (verboseLevel > LogLevel.Trace)
 {
Expand DownExpand Up@@ -111,20 +107,22 @@ public void GenerateCode()

 if (verboseLevel > LogLevel.Trace && !Console.IsOutputRedirected)
 {
 Exception ex = null;
 using (var pbar = new FixedDurationBar(wait, "", options))
 {
 pbar.Message = Strings.WaitingForFirstIteration;
 Thread t = default;
 switch (taskKind)
 {
 // TODO: It may be a good idea to convert the below Threads to Tasks or get rid of this progress bar all together and use an existing one in opensource.
 case TaskKind.BinaryClassification:
 t = new Thread(() => binaryExperimentResult = automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar), out ex, out binaryExperimentResult, pbar));
 break;
 case TaskKind.Regression:
 t = new Thread(() => regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar), out ex, out regressionExperimentResult, pbar));
 break;
 case TaskKind.MulticlassClassification:
 t = new Thread(() => multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar), out ex, out multiclassExperimentResult, pbar));
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand All@@ -147,6 +145,10 @@ public void GenerateCode()
 pbar.Message = originalMessage;
 }
 }
 if (ex != null)
 {
 throw ex;
 }
 }
 }
 else
Expand All@@ -160,7 +162,7 @@ public void GenerateCode()
 regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric);
 break;
 case TaskKind.MulticlassClassification:
multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
multiclassExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand DownExpand Up@@ -204,11 +206,11 @@ public void GenerateCode()
 ConsolePrinter.PrintIterationSummary(regressionExperimentResult.RunDetails, new RegressionExperimentSettings().OptimizingMetric, 5);
 break;
 case TaskKind.MulticlassClassification:
 var bestMultiIteration = multiExperimentResult.BestRun;
 bestPipeline = bestMultiIteration.Pipeline;
 bestModel = bestMultiIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 var bestMulticlassIteration = multiclassExperimentResult.BestRun;
 bestPipeline = bestMulticlassIteration.Pipeline;
 bestModel = bestMulticlassIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiclassExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiclassExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 break;
 }
 }
Expand DownExpand Up@@ -278,5 +280,51 @@ private void ConsumeAutoMLSDKLogs(MLContext context)
 }
 };
 }

 private void SafeExecute(Func<ExperimentResult<BinaryClassificationMetrics>> p, out Exception ex, out ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 binaryExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 binaryExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<RegressionMetrics>> p, out Exception ex, out ExperimentResult<RegressionMetrics> regressionExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 regressionExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 regressionExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<MulticlassClassificationMetrics>> p, out Exception ex, out ExperimentResult<MulticlassClassificationMetrics> multiClassExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 multiClassExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 multiClassExperimentResult = null;
 pbar.Dispose(); // or ((ManualResetEvent)pbar.CompletedHandle).Set();
 return;
 }
 }
 }
}

1 change: 1 addition & 0 deletions
src/mlnet/ProgressBar/ProgressBar.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -356,6 +356,7 @@ public void Dispose()
 _timer?.Dispose();
 _timer = null;
 foreach (var c in this.Children) c.Dispose();
 OnDone();
 }
 }
}

, '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
[AutoML] Fix error handling in CLI. #3618

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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By clicking “Sign up for GitHub”, you agree to our terms of service and
privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

srsaggam
merged 2 commits into

from

Apr 29, 2019
 Merged


[AutoML] Fix error handling in CLI. #3618
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a5008a8

fix error handling


srsaggam Apr 29, 2019
c40cf93

renaming variables


srsaggam Apr 29, 2019

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76 changes: 62 additions & 14 deletions
src/mlnet/CodeGenerator/CodeGenerationHelper.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,21 +3,17 @@
// See the LICENSE file in the project root for more information.

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.IO;
using System.Linq;
using System.Runtime.ExceptionServices;
using System.Threading;
using System.Threading.Tasks;
using Microsoft.ML.AutoML;
using Microsoft.ML.CLI.CodeGenerator.CSharp;
using Microsoft.ML.CLI.Data;
using Microsoft.ML.CLI.ShellProgressBar;
using Microsoft.ML.CLI.Utilities;
using Microsoft.ML.Data;
using NLog;
using NLog.Targets;

namespace Microsoft.ML.CLI.CodeGenerator
{
Expand DownExpand Up@@ -81,7 +77,7 @@ public void GenerateCode()
 // i.e there is no common class/interface to handle all three tasks together.

 ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiclassExperimentResult = default;
 ExperimentResult<RegressionMetrics> regressionExperimentResult = default;
 if (verboseLevel > LogLevel.Trace)
 {
Expand DownExpand Up@@ -111,20 +107,22 @@ public void GenerateCode()

 if (verboseLevel > LogLevel.Trace && !Console.IsOutputRedirected)
 {
 Exception ex = null;
 using (var pbar = new FixedDurationBar(wait, "", options))
 {
 pbar.Message = Strings.WaitingForFirstIteration;
 Thread t = default;
 switch (taskKind)
 {
 // TODO: It may be a good idea to convert the below Threads to Tasks or get rid of this progress bar all together and use an existing one in opensource.
 case TaskKind.BinaryClassification:
 t = new Thread(() => binaryExperimentResult = automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar), out ex, out binaryExperimentResult, pbar));
 break;
 case TaskKind.Regression:
 t = new Thread(() => regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar), out ex, out regressionExperimentResult, pbar));
 break;
 case TaskKind.MulticlassClassification:
 t = new Thread(() => multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar), out ex, out multiclassExperimentResult, pbar));
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand All@@ -147,6 +145,10 @@ public void GenerateCode()
 pbar.Message = originalMessage;
 }
 }
 if (ex != null)
 {
 throw ex;
 }
 }
 }
 else
Expand All@@ -160,7 +162,7 @@ public void GenerateCode()
 regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric);
 break;
 case TaskKind.MulticlassClassification:
multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
multiclassExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand DownExpand Up@@ -204,11 +206,11 @@ public void GenerateCode()
 ConsolePrinter.PrintIterationSummary(regressionExperimentResult.RunDetails, new RegressionExperimentSettings().OptimizingMetric, 5);
 break;
 case TaskKind.MulticlassClassification:
 var bestMultiIteration = multiExperimentResult.BestRun;
 bestPipeline = bestMultiIteration.Pipeline;
 bestModel = bestMultiIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 var bestMulticlassIteration = multiclassExperimentResult.BestRun;
 bestPipeline = bestMulticlassIteration.Pipeline;
 bestModel = bestMulticlassIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiclassExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiclassExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 break;
 }
 }
Expand DownExpand Up@@ -278,5 +280,51 @@ private void ConsumeAutoMLSDKLogs(MLContext context)
 }
 };
 }

 private void SafeExecute(Func<ExperimentResult<BinaryClassificationMetrics>> p, out Exception ex, out ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 binaryExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 binaryExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<RegressionMetrics>> p, out Exception ex, out ExperimentResult<RegressionMetrics> regressionExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 regressionExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 regressionExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<MulticlassClassificationMetrics>> p, out Exception ex, out ExperimentResult<MulticlassClassificationMetrics> multiClassExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 multiClassExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 multiClassExperimentResult = null;
 pbar.Dispose(); // or ((ManualResetEvent)pbar.CompletedHandle).Set();
 return;
 }
 }
 }
}

1 change: 1 addition & 0 deletions
src/mlnet/ProgressBar/ProgressBar.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -356,6 +356,7 @@ public void Dispose()
 _timer?.Dispose();
 _timer = null;
 foreach (var c in this.Children) c.Dispose();
 OnDone();
 }
 }
}

, '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 > 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('^' + ".*" + '

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[AutoML] Fix error handling in CLI. #3618

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srsaggam
merged 2 commits into

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Apr 29, 2019
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[AutoML] Fix error handling in CLI. #3618
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a5008a8

fix error handling


srsaggam Apr 29, 2019
c40cf93

renaming variables


srsaggam Apr 29, 2019

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76 changes: 62 additions & 14 deletions
src/mlnet/CodeGenerator/CodeGenerationHelper.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,21 +3,17 @@
// See the LICENSE file in the project root for more information.

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.IO;
using System.Linq;
using System.Runtime.ExceptionServices;
using System.Threading;
using System.Threading.Tasks;
using Microsoft.ML.AutoML;
using Microsoft.ML.CLI.CodeGenerator.CSharp;
using Microsoft.ML.CLI.Data;
using Microsoft.ML.CLI.ShellProgressBar;
using Microsoft.ML.CLI.Utilities;
using Microsoft.ML.Data;
using NLog;
using NLog.Targets;

namespace Microsoft.ML.CLI.CodeGenerator
{
Expand DownExpand Up@@ -81,7 +77,7 @@ public void GenerateCode()
 // i.e there is no common class/interface to handle all three tasks together.

 ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiclassExperimentResult = default;
 ExperimentResult<RegressionMetrics> regressionExperimentResult = default;
 if (verboseLevel > LogLevel.Trace)
 {
Expand DownExpand Up@@ -111,20 +107,22 @@ public void GenerateCode()

 if (verboseLevel > LogLevel.Trace && !Console.IsOutputRedirected)
 {
 Exception ex = null;
 using (var pbar = new FixedDurationBar(wait, "", options))
 {
 pbar.Message = Strings.WaitingForFirstIteration;
 Thread t = default;
 switch (taskKind)
 {
 // TODO: It may be a good idea to convert the below Threads to Tasks or get rid of this progress bar all together and use an existing one in opensource.
 case TaskKind.BinaryClassification:
 t = new Thread(() => binaryExperimentResult = automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar), out ex, out binaryExperimentResult, pbar));
 break;
 case TaskKind.Regression:
 t = new Thread(() => regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar), out ex, out regressionExperimentResult, pbar));
 break;
 case TaskKind.MulticlassClassification:
 t = new Thread(() => multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar), out ex, out multiclassExperimentResult, pbar));
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand All@@ -147,6 +145,10 @@ public void GenerateCode()
 pbar.Message = originalMessage;
 }
 }
 if (ex != null)
 {
 throw ex;
 }
 }
 }
 else
Expand All@@ -160,7 +162,7 @@ public void GenerateCode()
 regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric);
 break;
 case TaskKind.MulticlassClassification:
multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
multiclassExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand DownExpand Up@@ -204,11 +206,11 @@ public void GenerateCode()
 ConsolePrinter.PrintIterationSummary(regressionExperimentResult.RunDetails, new RegressionExperimentSettings().OptimizingMetric, 5);
 break;
 case TaskKind.MulticlassClassification:
 var bestMultiIteration = multiExperimentResult.BestRun;
 bestPipeline = bestMultiIteration.Pipeline;
 bestModel = bestMultiIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 var bestMulticlassIteration = multiclassExperimentResult.BestRun;
 bestPipeline = bestMulticlassIteration.Pipeline;
 bestModel = bestMulticlassIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiclassExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiclassExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 break;
 }
 }
Expand DownExpand Up@@ -278,5 +280,51 @@ private void ConsumeAutoMLSDKLogs(MLContext context)
 }
 };
 }

 private void SafeExecute(Func<ExperimentResult<BinaryClassificationMetrics>> p, out Exception ex, out ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 binaryExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 binaryExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<RegressionMetrics>> p, out Exception ex, out ExperimentResult<RegressionMetrics> regressionExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 regressionExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 regressionExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<MulticlassClassificationMetrics>> p, out Exception ex, out ExperimentResult<MulticlassClassificationMetrics> multiClassExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 multiClassExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 multiClassExperimentResult = null;
 pbar.Dispose(); // or ((ManualResetEvent)pbar.CompletedHandle).Set();
 return;
 }
 }
 }
}

1 change: 1 addition & 0 deletions
src/mlnet/ProgressBar/ProgressBar.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -356,6 +356,7 @@ public void Dispose()
 _timer?.Dispose();
 _timer = null;
 foreach (var c in this.Children) c.Dispose();
 OnDone();
 }
 }
}

, '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
[AutoML] Fix error handling in CLI. #3618

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 Merged

srsaggam
merged 2 commits into

from

Apr 29, 2019
 Merged


[AutoML] Fix error handling in CLI. #3618
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a5008a8

fix error handling


srsaggam Apr 29, 2019
c40cf93

renaming variables


srsaggam Apr 29, 2019

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76 changes: 62 additions & 14 deletions
src/mlnet/CodeGenerator/CodeGenerationHelper.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,21 +3,17 @@
// See the LICENSE file in the project root for more information.

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.IO;
using System.Linq;
using System.Runtime.ExceptionServices;
using System.Threading;
using System.Threading.Tasks;
using Microsoft.ML.AutoML;
using Microsoft.ML.CLI.CodeGenerator.CSharp;
using Microsoft.ML.CLI.Data;
using Microsoft.ML.CLI.ShellProgressBar;
using Microsoft.ML.CLI.Utilities;
using Microsoft.ML.Data;
using NLog;
using NLog.Targets;

namespace Microsoft.ML.CLI.CodeGenerator
{
Expand DownExpand Up@@ -81,7 +77,7 @@ public void GenerateCode()
 // i.e there is no common class/interface to handle all three tasks together.

 ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiclassExperimentResult = default;
 ExperimentResult<RegressionMetrics> regressionExperimentResult = default;
 if (verboseLevel > LogLevel.Trace)
 {
Expand DownExpand Up@@ -111,20 +107,22 @@ public void GenerateCode()

 if (verboseLevel > LogLevel.Trace && !Console.IsOutputRedirected)
 {
 Exception ex = null;
 using (var pbar = new FixedDurationBar(wait, "", options))
 {
 pbar.Message = Strings.WaitingForFirstIteration;
 Thread t = default;
 switch (taskKind)
 {
 // TODO: It may be a good idea to convert the below Threads to Tasks or get rid of this progress bar all together and use an existing one in opensource.
 case TaskKind.BinaryClassification:
 t = new Thread(() => binaryExperimentResult = automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar), out ex, out binaryExperimentResult, pbar));
 break;
 case TaskKind.Regression:
 t = new Thread(() => regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar), out ex, out regressionExperimentResult, pbar));
 break;
 case TaskKind.MulticlassClassification:
 t = new Thread(() => multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar), out ex, out multiclassExperimentResult, pbar));
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand All@@ -147,6 +145,10 @@ public void GenerateCode()
 pbar.Message = originalMessage;
 }
 }
 if (ex != null)
 {
 throw ex;
 }
 }
 }
 else
Expand All@@ -160,7 +162,7 @@ public void GenerateCode()
 regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric);
 break;
 case TaskKind.MulticlassClassification:
multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
multiclassExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand DownExpand Up@@ -204,11 +206,11 @@ public void GenerateCode()
 ConsolePrinter.PrintIterationSummary(regressionExperimentResult.RunDetails, new RegressionExperimentSettings().OptimizingMetric, 5);
 break;
 case TaskKind.MulticlassClassification:
 var bestMultiIteration = multiExperimentResult.BestRun;
 bestPipeline = bestMultiIteration.Pipeline;
 bestModel = bestMultiIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 var bestMulticlassIteration = multiclassExperimentResult.BestRun;
 bestPipeline = bestMulticlassIteration.Pipeline;
 bestModel = bestMulticlassIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiclassExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiclassExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 break;
 }
 }
Expand DownExpand Up@@ -278,5 +280,51 @@ private void ConsumeAutoMLSDKLogs(MLContext context)
 }
 };
 }

 private void SafeExecute(Func<ExperimentResult<BinaryClassificationMetrics>> p, out Exception ex, out ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 binaryExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 binaryExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<RegressionMetrics>> p, out Exception ex, out ExperimentResult<RegressionMetrics> regressionExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 regressionExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 regressionExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<MulticlassClassificationMetrics>> p, out Exception ex, out ExperimentResult<MulticlassClassificationMetrics> multiClassExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 multiClassExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 multiClassExperimentResult = null;
 pbar.Dispose(); // or ((ManualResetEvent)pbar.CompletedHandle).Set();
 return;
 }
 }
 }
}

1 change: 1 addition & 0 deletions
src/mlnet/ProgressBar/ProgressBar.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -356,6 +356,7 @@ public void Dispose()
 _timer?.Dispose();
 _timer = null;
 foreach (var c in this.Children) c.Dispose();
 OnDone();
 }
 }
}

, '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
[AutoML] Fix error handling in CLI. #3618

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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privacy statement. We’ll occasionally send you account related emails.

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 Merged

srsaggam
merged 2 commits into

from

Apr 29, 2019
 Merged


[AutoML] Fix error handling in CLI. #3618
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a5008a8

fix error handling


srsaggam Apr 29, 2019
c40cf93

renaming variables


srsaggam Apr 29, 2019

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76 changes: 62 additions & 14 deletions
src/mlnet/CodeGenerator/CodeGenerationHelper.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,21 +3,17 @@
// See the LICENSE file in the project root for more information.

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.IO;
using System.Linq;
using System.Runtime.ExceptionServices;
using System.Threading;
using System.Threading.Tasks;
using Microsoft.ML.AutoML;
using Microsoft.ML.CLI.CodeGenerator.CSharp;
using Microsoft.ML.CLI.Data;
using Microsoft.ML.CLI.ShellProgressBar;
using Microsoft.ML.CLI.Utilities;
using Microsoft.ML.Data;
using NLog;
using NLog.Targets;

namespace Microsoft.ML.CLI.CodeGenerator
{
Expand DownExpand Up@@ -81,7 +77,7 @@ public void GenerateCode()
 // i.e there is no common class/interface to handle all three tasks together.

 ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiclassExperimentResult = default;
 ExperimentResult<RegressionMetrics> regressionExperimentResult = default;
 if (verboseLevel > LogLevel.Trace)
 {
Expand DownExpand Up@@ -111,20 +107,22 @@ public void GenerateCode()

 if (verboseLevel > LogLevel.Trace && !Console.IsOutputRedirected)
 {
 Exception ex = null;
 using (var pbar = new FixedDurationBar(wait, "", options))
 {
 pbar.Message = Strings.WaitingForFirstIteration;
 Thread t = default;
 switch (taskKind)
 {
 // TODO: It may be a good idea to convert the below Threads to Tasks or get rid of this progress bar all together and use an existing one in opensource.
 case TaskKind.BinaryClassification:
 t = new Thread(() => binaryExperimentResult = automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar), out ex, out binaryExperimentResult, pbar));
 break;
 case TaskKind.Regression:
 t = new Thread(() => regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar), out ex, out regressionExperimentResult, pbar));
 break;
 case TaskKind.MulticlassClassification:
 t = new Thread(() => multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar), out ex, out multiclassExperimentResult, pbar));
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand All@@ -147,6 +145,10 @@ public void GenerateCode()
 pbar.Message = originalMessage;
 }
 }
 if (ex != null)
 {
 throw ex;
 }
 }
 }
 else
Expand All@@ -160,7 +162,7 @@ public void GenerateCode()
 regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric);
 break;
 case TaskKind.MulticlassClassification:
multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
multiclassExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand DownExpand Up@@ -204,11 +206,11 @@ public void GenerateCode()
 ConsolePrinter.PrintIterationSummary(regressionExperimentResult.RunDetails, new RegressionExperimentSettings().OptimizingMetric, 5);
 break;
 case TaskKind.MulticlassClassification:
 var bestMultiIteration = multiExperimentResult.BestRun;
 bestPipeline = bestMultiIteration.Pipeline;
 bestModel = bestMultiIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 var bestMulticlassIteration = multiclassExperimentResult.BestRun;
 bestPipeline = bestMulticlassIteration.Pipeline;
 bestModel = bestMulticlassIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiclassExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiclassExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 break;
 }
 }
Expand DownExpand Up@@ -278,5 +280,51 @@ private void ConsumeAutoMLSDKLogs(MLContext context)
 }
 };
 }

 private void SafeExecute(Func<ExperimentResult<BinaryClassificationMetrics>> p, out Exception ex, out ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 binaryExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 binaryExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<RegressionMetrics>> p, out Exception ex, out ExperimentResult<RegressionMetrics> regressionExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 regressionExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 regressionExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<MulticlassClassificationMetrics>> p, out Exception ex, out ExperimentResult<MulticlassClassificationMetrics> multiClassExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 multiClassExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 multiClassExperimentResult = null;
 pbar.Dispose(); // or ((ManualResetEvent)pbar.CompletedHandle).Set();
 return;
 }
 }
 }
}

1 change: 1 addition & 0 deletions
src/mlnet/ProgressBar/ProgressBar.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -356,6 +356,7 @@ public void Dispose()
 _timer?.Dispose();
 _timer = null;
 foreach (var c in this.Children) c.Dispose();
 OnDone();
 }
 }
}

, '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('^' + ".*" + '

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[AutoML] Fix error handling in CLI. #3618

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 Merged

srsaggam
merged 2 commits into

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Apr 29, 2019
 Merged


[AutoML] Fix error handling in CLI. #3618
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a5008a8

fix error handling


srsaggam Apr 29, 2019
c40cf93

renaming variables


srsaggam Apr 29, 2019

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76 changes: 62 additions & 14 deletions
src/mlnet/CodeGenerator/CodeGenerationHelper.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,21 +3,17 @@
// See the LICENSE file in the project root for more information.

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.IO;
using System.Linq;
using System.Runtime.ExceptionServices;
using System.Threading;
using System.Threading.Tasks;
using Microsoft.ML.AutoML;
using Microsoft.ML.CLI.CodeGenerator.CSharp;
using Microsoft.ML.CLI.Data;
using Microsoft.ML.CLI.ShellProgressBar;
using Microsoft.ML.CLI.Utilities;
using Microsoft.ML.Data;
using NLog;
using NLog.Targets;

namespace Microsoft.ML.CLI.CodeGenerator
{
Expand DownExpand Up@@ -81,7 +77,7 @@ public void GenerateCode()
 // i.e there is no common class/interface to handle all three tasks together.

 ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiclassExperimentResult = default;
 ExperimentResult<RegressionMetrics> regressionExperimentResult = default;
 if (verboseLevel > LogLevel.Trace)
 {
Expand DownExpand Up@@ -111,20 +107,22 @@ public void GenerateCode()

 if (verboseLevel > LogLevel.Trace && !Console.IsOutputRedirected)
 {
 Exception ex = null;
 using (var pbar = new FixedDurationBar(wait, "", options))
 {
 pbar.Message = Strings.WaitingForFirstIteration;
 Thread t = default;
 switch (taskKind)
 {
 // TODO: It may be a good idea to convert the below Threads to Tasks or get rid of this progress bar all together and use an existing one in opensource.
 case TaskKind.BinaryClassification:
 t = new Thread(() => binaryExperimentResult = automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar), out ex, out binaryExperimentResult, pbar));
 break;
 case TaskKind.Regression:
 t = new Thread(() => regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar), out ex, out regressionExperimentResult, pbar));
 break;
 case TaskKind.MulticlassClassification:
 t = new Thread(() => multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar), out ex, out multiclassExperimentResult, pbar));
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand All@@ -147,6 +145,10 @@ public void GenerateCode()
 pbar.Message = originalMessage;
 }
 }
 if (ex != null)
 {
 throw ex;
 }
 }
 }
 else
Expand All@@ -160,7 +162,7 @@ public void GenerateCode()
 regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric);
 break;
 case TaskKind.MulticlassClassification:
multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
multiclassExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand DownExpand Up@@ -204,11 +206,11 @@ public void GenerateCode()
 ConsolePrinter.PrintIterationSummary(regressionExperimentResult.RunDetails, new RegressionExperimentSettings().OptimizingMetric, 5);
 break;
 case TaskKind.MulticlassClassification:
 var bestMultiIteration = multiExperimentResult.BestRun;
 bestPipeline = bestMultiIteration.Pipeline;
 bestModel = bestMultiIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 var bestMulticlassIteration = multiclassExperimentResult.BestRun;
 bestPipeline = bestMulticlassIteration.Pipeline;
 bestModel = bestMulticlassIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiclassExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiclassExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 break;
 }
 }
Expand DownExpand Up@@ -278,5 +280,51 @@ private void ConsumeAutoMLSDKLogs(MLContext context)
 }
 };
 }

 private void SafeExecute(Func<ExperimentResult<BinaryClassificationMetrics>> p, out Exception ex, out ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 binaryExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 binaryExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<RegressionMetrics>> p, out Exception ex, out ExperimentResult<RegressionMetrics> regressionExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 regressionExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 regressionExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<MulticlassClassificationMetrics>> p, out Exception ex, out ExperimentResult<MulticlassClassificationMetrics> multiClassExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 multiClassExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 multiClassExperimentResult = null;
 pbar.Dispose(); // or ((ManualResetEvent)pbar.CompletedHandle).Set();
 return;
 }
 }
 }
}

1 change: 1 addition & 0 deletions
src/mlnet/ProgressBar/ProgressBar.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -356,6 +356,7 @@ public void Dispose()
 _timer?.Dispose();
 _timer = null;
 foreach (var c in this.Children) c.Dispose();
 OnDone();
 }
 }
}

, '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); }
})();
})();

Skip to content
[AutoML] Fix error handling in CLI. #3618

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
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 Merged

srsaggam
merged 2 commits into

from

Apr 29, 2019
 Merged


[AutoML] Fix error handling in CLI. #3618
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a5008a8

fix error handling


srsaggam Apr 29, 2019
c40cf93

renaming variables


srsaggam Apr 29, 2019

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76 changes: 62 additions & 14 deletions
src/mlnet/CodeGenerator/CodeGenerationHelper.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,21 +3,17 @@
// See the LICENSE file in the project root for more information.

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.IO;
using System.Linq;
using System.Runtime.ExceptionServices;
using System.Threading;
using System.Threading.Tasks;
using Microsoft.ML.AutoML;
using Microsoft.ML.CLI.CodeGenerator.CSharp;
using Microsoft.ML.CLI.Data;
using Microsoft.ML.CLI.ShellProgressBar;
using Microsoft.ML.CLI.Utilities;
using Microsoft.ML.Data;
using NLog;
using NLog.Targets;

namespace Microsoft.ML.CLI.CodeGenerator
{
Expand DownExpand Up@@ -81,7 +77,7 @@ public void GenerateCode()
 // i.e there is no common class/interface to handle all three tasks together.

 ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiExperimentResult = default;
 ExperimentResult<MulticlassClassificationMetrics> multiclassExperimentResult = default;
 ExperimentResult<RegressionMetrics> regressionExperimentResult = default;
 if (verboseLevel > LogLevel.Trace)
 {
Expand DownExpand Up@@ -111,20 +107,22 @@ public void GenerateCode()

 if (verboseLevel > LogLevel.Trace && !Console.IsOutputRedirected)
 {
 Exception ex = null;
 using (var pbar = new FixedDurationBar(wait, "", options))
 {
 pbar.Message = Strings.WaitingForFirstIteration;
 Thread t = default;
 switch (taskKind)
 {
 // TODO: It may be a good idea to convert the below Threads to Tasks or get rid of this progress bar all together and use an existing one in opensource.
 case TaskKind.BinaryClassification:
 t = new Thread(() => binaryExperimentResult = automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreBinaryClassificationModels(context, trainData, validationData, columnInformation, new BinaryExperimentSettings().OptimizingMetric, pbar), out ex, out binaryExperimentResult, pbar));
 break;
 case TaskKind.Regression:
 t = new Thread(() => regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric, pbar), out ex, out regressionExperimentResult, pbar));
 break;
 case TaskKind.MulticlassClassification:
 t = new Thread(() => multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar));
 t = new Thread(() => SafeExecute(() => automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric, pbar), out ex, out multiclassExperimentResult, pbar));
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand All@@ -147,6 +145,10 @@ public void GenerateCode()
 pbar.Message = originalMessage;
 }
 }
 if (ex != null)
 {
 throw ex;
 }
 }
 }
 else
Expand All@@ -160,7 +162,7 @@ public void GenerateCode()
 regressionExperimentResult = automlEngine.ExploreRegressionModels(context, trainData, validationData, columnInformation, new RegressionExperimentSettings().OptimizingMetric);
 break;
 case TaskKind.MulticlassClassification:
multiExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
multiclassExperimentResult = automlEngine.ExploreMultiClassificationModels(context, trainData, validationData, columnInformation, new MulticlassExperimentSettings().OptimizingMetric);
 break;
 default:
 logger.Log(LogLevel.Error, Strings.UnsupportedMlTask);
Expand DownExpand Up@@ -204,11 +206,11 @@ public void GenerateCode()
 ConsolePrinter.PrintIterationSummary(regressionExperimentResult.RunDetails, new RegressionExperimentSettings().OptimizingMetric, 5);
 break;
 case TaskKind.MulticlassClassification:
 var bestMultiIteration = multiExperimentResult.BestRun;
 bestPipeline = bestMultiIteration.Pipeline;
 bestModel = bestMultiIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 var bestMulticlassIteration = multiclassExperimentResult.BestRun;
 bestPipeline = bestMulticlassIteration.Pipeline;
 bestModel = bestMulticlassIteration.Model;
 ConsolePrinter.ExperimentResultsHeader(LogLevel.Info, settings.MlTask, settings.Dataset.Name, columnInformation.LabelColumnName, elapsedTime.ToString("F2"), multiclassExperimentResult.RunDetails.Count());
 ConsolePrinter.PrintIterationSummary(multiclassExperimentResult.RunDetails, new MulticlassExperimentSettings().OptimizingMetric, 5);
 break;
 }
 }
Expand DownExpand Up@@ -278,5 +280,51 @@ private void ConsumeAutoMLSDKLogs(MLContext context)
 }
 };
 }

 private void SafeExecute(Func<ExperimentResult<BinaryClassificationMetrics>> p, out Exception ex, out ExperimentResult<BinaryClassificationMetrics> binaryExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 binaryExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 binaryExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<RegressionMetrics>> p, out Exception ex, out ExperimentResult<RegressionMetrics> regressionExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 regressionExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 regressionExperimentResult = null;
 return;
 }
 }

 private void SafeExecute(Func<ExperimentResult<MulticlassClassificationMetrics>> p, out Exception ex, out ExperimentResult<MulticlassClassificationMetrics> multiClassExperimentResult, FixedDurationBar pbar)
 {
 try
 {
 multiClassExperimentResult = p.Invoke();
 ex = null;
 }
 catch (Exception e)
 {
 ex = e;
 multiClassExperimentResult = null;
 pbar.Dispose(); // or ((ManualResetEvent)pbar.CompletedHandle).Set();
 return;
 }
 }
 }
}

1 change: 1 addition & 0 deletions
src/mlnet/ProgressBar/ProgressBar.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -356,6 +356,7 @@ public void Dispose()
 _timer?.Dispose();
 _timer = null;
 foreach (var c in this.Children) c.Dispose();
 OnDone();
 }
 }
}