Fixes data invariant format problems

The tests do not pass on machines that have different
formatting than English language. The error happens since
the results are written in different than expected format.

Fixes #74

Author: veikkoeeva

src/Microsoft.ML.Core/Environment/TlcEnvironment.cs

@@ -7,6 +7,7 @@
 using System;
 using System.Collections.Concurrent;
 using System.Collections.Generic;
+using System.Globalization;
 using System.IO;
 using System.Linq;
 using System.Threading;
@@ -212,7 +213,7 @@ public void GetAndPrintAllProgress(ProgressReporting.ProgressTracker progressTra
                                 PrintOperationStop(_out, ev);
                                 break;
                             case ProgressReporting.ProgressEvent.EventKind.Progress:
-                                _out.Write("[{0}] ", ev.Index);
+                                _out.Write(string.Format(CultureInfo.InvariantCulture, "[{0}] ", ev.Index));
                                 PrintProgressLine(_out, ev);
                                 break;
                         }
@@ -225,7 +226,7 @@ public void GetAndPrintAllProgress(ProgressReporting.ProgressTracker progressTra
 
                     if (PrintDot())
                     {
-                        // We need to print an extended status line. At this point, every event should be 
+                        // We need to print an extended status line. At this point, every event should be
                         // a non-checkpoint progress event.
                         bool needPrepend = entries.Count > 1;
                         foreach (var ev in entries)
@@ -236,7 +237,7 @@ public void GetAndPrintAllProgress(ProgressReporting.ProgressTracker progressTra
                             {
                                 EnsureNewLine();
                                 WriteAndReturnLinePrefix(MessageSensitivity.None, _out);
-                                _out.Write("[{0}] ", ev.Index);
+                                _out.Write(string.Format(CultureInfo.InvariantCulture, "[{0}] ", ev.Index));
                             }
                             else
                             {
@@ -252,24 +253,24 @@ public void GetAndPrintAllProgress(ProgressReporting.ProgressTracker progressTra
 
             private static void PrintOperationStart(TextWriter writer, ProgressReporting.ProgressEvent ev)
             {
-                writer.WriteLine("[{0}] '{1}' started.", ev.Index, ev.Name);
+                writer.WriteLine(string.Format(CultureInfo.InvariantCulture, "[{0}] '{1}' started.", ev.Index, ev.Name));
             }
 
             private static void PrintOperationStop(TextWriter writer, ProgressReporting.ProgressEvent ev)
             {
-                writer.WriteLine("[{0}] '{1}' finished in {2}.", ev.Index, ev.Name, ev.EventTime - ev.StartTime);
+                writer.WriteLine(string.Format(CultureInfo.InvariantCulture, "[{0}] '{1}' finished in {2}.", ev.Index, ev.Name, ev.EventTime - ev.StartTime));
             }
 
             private void PrintProgressLine(TextWriter writer, ProgressReporting.ProgressEvent ev)
             {
                 // Elapsed time.
                 var elapsed = ev.EventTime - ev.StartTime;
                 if (elapsed.TotalMinutes < 1)
-                    writer.Write("(00:{0:00.00})", elapsed.TotalSeconds);
+                    writer.Write(string.Format(CultureInfo.InvariantCulture, "(00:{0:00.00})", elapsed.TotalSeconds));
                 else if (elapsed.TotalHours < 1)
-                    writer.Write("({0:00}:{1:00.0})", elapsed.Minutes, elapsed.TotalSeconds - 60 * elapsed.Minutes);
+                    writer.Write(string.Format(CultureInfo.InvariantCulture, "({0:00}:{1:00.0})", elapsed.Minutes, elapsed.TotalSeconds - 60 * elapsed.Minutes));
                 else
-                    writer.Write("({0:00}:{1:00}:{2:00})", elapsed.Hours, elapsed.Minutes, elapsed.Seconds);
+                    writer.Write(string.Format(CultureInfo.InvariantCulture, "({0:00}:{1:00}:{2:00})", elapsed.Hours, elapsed.Minutes, elapsed.Seconds));
 
                 // Progress units.
                 bool first = true;
@@ -281,7 +282,7 @@ private void PrintProgressLine(TextWriter writer, ProgressReporting.ProgressEven
                     first = false;
                     writer.Write("{0}", ev.ProgressEntry.Progress[i]);
                     if (ev.ProgressEntry.ProgressLim[i] != null)
-                        writer.Write("/{0}", ev.ProgressEntry.ProgressLim[i].Value);
+                        writer.Write("/{0}", ev.ProgressEntry.ProgressLim[i].Value.ToString(CultureInfo.InvariantCulture));
                     writer.Write(" {0}", ev.ProgressEntry.Header.UnitNames[i]);
                 }
 
@@ -291,7 +292,7 @@ private void PrintProgressLine(TextWriter writer, ProgressReporting.ProgressEven
                     if (ev.ProgressEntry.Metrics[i] == null)
                         continue;
                     // REVIEW: print metrics prettier.
-                    writer.Write("\t{0}: {1}", ev.ProgressEntry.Header.MetricNames[i], ev.ProgressEntry.Metrics[i].Value);
+                    writer.Write("\t{0}: {1}", ev.ProgressEntry.Header.MetricNames[i], ev.ProgressEntry.Metrics[i].Value.ToString(CultureInfo.InvariantCulture));
                 }
 
                 writer.WriteLine();
@@ -306,7 +307,7 @@ private void EnsureNewLine(bool isError = false)
                     return;
 
                 // If _err and _out is the same writer, we need to print new line as well.
-                // If _out and _err writes to Console.Out and Console.Error respectively, 
+                // If _out and _err writes to Console.Out and Console.Error respectively,
                 // in the general user scenario they ends up with writing to the same underlying stream,.
                 // so write a new line to the stream anyways.
                 if (isError && _err != _out && (_out != Console.Out || _err != Console.Error))

src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs

@@ -383,7 +383,7 @@ public static IDataView AddKeyColumn<TSrc>(IHostEnvironment env, IDataView input
 
         /// <summary>
         /// This method takes an array of data views and a specified input vector column, and adds a new output column to each of the data views.
-        /// First, we find the union set of the slot names in the different data views. Next we define a new vector column for each 
+        /// First, we find the union set of the slot names in the different data views. Next we define a new vector column for each
         /// data view, indexed by the union of the slot names. For each data view, every slot value is the value in the slot corresponding
         /// to its slot name in the original column. If a reconciled slot name does not exist in an input column, the value in the output
         /// column is def.
@@ -530,7 +530,7 @@ private static int[][] MapKeys(ISchema[] schemas, string columnName, bool isVec,
 
         /// <summary>
         /// This method takes an array of data views and a specified input key column, and adds a new output column to each of the data views.
-        /// First, we find the union set of the key values in the different data views. Next we define a new key column for each 
+        /// First, we find the union set of the key values in the different data views. Next we define a new key column for each
         /// data view, with the union of the key values as the new key values. For each data view, the value in the output column is the value
         /// corresponding to the key value in the original column.
         /// </summary>
@@ -801,8 +801,8 @@ public static string GetPerFoldResults(IHostEnvironment env, IDataView fold, out
         }
 
         // This method returns a string representation of a set of metrics. If there are stratification columns, it looks for columns named
-        // StratCol and StratVal, and outputs the metrics in the rows with NA in the StratCol column. If weighted is true, it looks 
-        // for a DvBool column named "IsWeighted" and outputs the metrics in the rows with a value of true in that column. 
+        // StratCol and StratVal, and outputs the metrics in the rows with NA in the StratCol column. If weighted is true, it looks
+        // for a DvBool column named "IsWeighted" and outputs the metrics in the rows with a value of true in that column.
         // If nonAveragedCols is non-null, it computes the average and standard deviation over all the relevant rows and populates
         // nonAveragedCols with columns that are either hidden, or are not of a type that we can display (i.e., either a numeric column,
         // or a known length vector of doubles).
@@ -926,8 +926,8 @@ private static string GetMetricsAsString(IHostEnvironment env, IDataView data, b
                 if (average)
                 {
                     Contracts.AssertValue(sumSqMetrics);
-                    sb.AppendLine(string.Format(" ({0:N4})", numResults == 1 ? 0 :
-                        Math.Sqrt(sumSqMetrics[i] / numResults - avgMetrics[i] * avgMetrics[i])));
+                    sb.AppendFormat(CultureInfo.InvariantCulture, " ({0:N4})", numResults == 1 ? 0 :
+                        Math.Sqrt(sumSqMetrics[i] / numResults - avgMetrics[i] * avgMetrics[i])).AppendLine();
                 }
                 else
                     sb.AppendLine();
@@ -1026,7 +1026,7 @@ private static List<string> GetMetricNames(IChannel ch, ISchema schema, IRow row
             Contracts.Assert(Utils.Size(vBufferGetters) == schema.ColumnCount);
 
             // Get the names of the metrics. For R8 valued columns the metric name is the column name. For R8 vector valued columns
-            // the names of the metrics are the column name, followed by the slot name if it exists, or "Label_i" if it doesn't. 
+            // the names of the metrics are the column name, followed by the slot name if it exists, or "Label_i" if it doesn't.
             VBuffer<DvText> names = default(VBuffer<DvText>);
             int metricCount = 0;
             var metricNames = new List<string>();
@@ -1121,7 +1121,7 @@ private static string GetConfusionTableAsString(double[][] confusionTable, doubl
                 var numFalseNeg = confusionTable[0][1];
                 var numTrueNeg = confusionTable[1][1];
                 var numFalsePos = confusionTable[1][0];
-                sb.AppendFormat("{0}TEST {1} RATIO:\t{2:N4} ({3:F1}/({3:F1}+{4:F1}))", prefix, positiveCaps,
+                sb.AppendFormat(CultureInfo.InvariantCulture, "{0}TEST {1} RATIO:\t{2:N4} ({3:F1}/({3:F1}+{4:F1}))", prefix, positiveCaps,
                     1.0 * (numTruePos + numFalseNeg) / (numTruePos + numTrueNeg + numFalseNeg + numFalsePos),
                     numTruePos + numFalseNeg, numFalsePos + numTrueNeg);
             }
@@ -1154,9 +1154,9 @@ private static string GetConfusionTableAsString(double[][] confusionTable, doubl
             {
                 sb.AppendFormat(rowLabelFormat, i, predictedLabelNames[i]);
                 for (int j = 0; j < numLabels; j++)
-                    sb.AppendFormat(format2, confusionTable[i][j]);
+                    sb.AppendFormat(CultureInfo.InvariantCulture, format2, confusionTable[i][j]);
                 Double recall = rowSums[i] > 0 ? confusionTable[i][i] / rowSums[i] : 0;
-                sb.AppendFormat(" {0,5:F4}", recall);
+                sb.AppendFormat(CultureInfo.InvariantCulture, " {0,5:F4}", recall);
                 sb.AppendLine();
             }
             sb.AppendFormat("          {0}||", pad);
@@ -1168,7 +1168,7 @@ private static string GetConfusionTableAsString(double[][] confusionTable, doubl
             for (int i = 0; i < numLabels; i++)
             {
                 Double precision = columnSums[i] > 0 ? confusionTable[i][i] / columnSums[i] : 0;
-                sb.AppendFormat(format, precision);
+                sb.AppendFormat(CultureInfo.InvariantCulture, format, precision);
             }
             sb.AppendLine();
             return sb.ToString();

src/Microsoft.ML.Data/Utilities/TimerScope.cs

@@ -3,6 +3,7 @@
 // See the LICENSE file in the project root for more information.
 
 using System;
+using System.Globalization;
 using Microsoft.ML.Runtime;
 using Microsoft.ML.Runtime.Data;
 
@@ -46,7 +47,7 @@ public void Dispose()
 
             // REVIEW: This is \n\n is to prevent changes across bunch of baseline files.
             // Ideally we should change our comparison method to ignore empty lines.
-            _ch.Info("{0}\t Time elapsed(s): {1}\n\n", DateTime.Now, elapsedSeconds);
+            _ch.Info("{0}\t Time elapsed(s): {1}\n\n", DateTime.Now.ToString(CultureInfo.InvariantCulture), elapsedSeconds.ToString(CultureInfo.InvariantCulture));
 
             using (var pipe = _host.StartPipe<TelemetryMessage>("TelemetryPipe"))
             {

src/Microsoft.ML.FastTree/Training/EnsembleCompression/LassoBasedEnsembleCompressor.cs

@@ -4,6 +4,7 @@
 
 using System;
 using System.Collections.Generic;
+using System.Globalization;
 
 namespace Microsoft.ML.Runtime.FastTree.Internal
 {

src/Microsoft.ML.FastTree/Training/Test.cs

@@ -4,6 +4,7 @@
 
 using System;
 using System.Collections.Generic;
+using System.Globalization;
 using System.Linq;
 using System.Threading;
 using System.Threading.Tasks;
@@ -191,7 +192,7 @@ public virtual string FormatInfoString()
             var sb = new System.Text.StringBuilder();
             foreach (var r in ComputeTests())
             {
-                sb.AppendFormat("{0}.{1}={2}\n", ScoreTracker.DatasetName, r.LossFunctionName, r.FinalValue);
+                sb.AppendFormat(CultureInfo.InvariantCulture, "{0}.{1}={2}\n", ScoreTracker.DatasetName, r.LossFunctionName, r.FinalValue);
             }
             return sb.ToString();
         }
@@ -377,7 +378,7 @@ public override string FormatInfoString()
             {
                 if (i > 1)
                     sb.Append("\t");
-                sb.AppendFormat("@{0}:{1:00.00}", i++, 100.0 * t.FinalValue);
+                sb.AppendFormat(CultureInfo.InvariantCulture, "@{0}:{1:00.00}", i++, 100.0 * t.FinalValue);
             }
             sb.AppendLine();
             return sb.ToString();
@@ -512,7 +513,7 @@ public override string FormatInfoString()
             {
                 if (i > 1)
                     sb.Append("\t");
-                sb.AppendFormat("{0}:{1:00.00}", t.LossFunctionName, t.FinalValue);
+                sb.AppendFormat(CultureInfo.InvariantCulture, "{0}:{1:00.00}", t.LossFunctionName, t.FinalValue);
                 i++;
             }
             sb.AppendLine();

src/Microsoft.ML.FastTree/TreeEnsemble/Ensemble.cs

@@ -4,6 +4,7 @@
 
 using System;
 using System.Collections.Generic;
+using System.Globalization;
 using System.IO;
 using System.Linq;
 using System.Text;
@@ -128,13 +129,13 @@ public string ToTreeEnsembleIni(FeaturesToContentMap fmap,
 
             numNodes += evaluatorCounter;
 
-            sb.AppendFormat("[TreeEnsemble]\nInputs={0}\nEvaluators={1}\n", featureToID.Count, evaluatorCounter + 1);
+            sb.AppendFormat(CultureInfo.InvariantCulture, "[TreeEnsemble]\nInputs={0}\nEvaluators={1}\n", featureToID.Count, evaluatorCounter + 1);
 
             sb.Append(sbInput);
             sb.Append(sbEvaluator);
 
             // Append the final aggregator
-            sb.AppendFormat("\n[Evaluator:{0}]\nEvaluatorType=Aggregator\nNumNodes={1}\nNodes=", evaluatorCounter + 1, numNodes);
+            sb.AppendFormat(CultureInfo.InvariantCulture, "\n[Evaluator:{0}]\nEvaluatorType=Aggregator\nNumNodes={1}\nNodes=", evaluatorCounter + 1, numNodes);
 
             // Nodes
             if (_firstInputInitializationContent != null)
@@ -163,7 +164,7 @@ public string ToTreeEnsembleIni(FeaturesToContentMap fmap,
             {
                 if (_firstInputInitializationContent != null)
                     sb.Append("\t");
-                sb.AppendFormat("{0}", _trees[0].Weight);
+                sb.AppendFormat(CultureInfo.InvariantCulture, "{0}", _trees[0].Weight);
             }
 
             for (int w = 1; w < NumTrees; ++w)
@@ -172,7 +173,7 @@ public string ToTreeEnsembleIni(FeaturesToContentMap fmap,
                 {
                     sb.Append("\t");
                 }
-                sb.Append(_trees[w].Weight);
+                sb.Append(_trees[w].Weight.ToString(CultureInfo.InvariantCulture));
             }
 
             sb.AppendFormat("\nBias={0}", Bias);
@@ -193,15 +194,15 @@ public string ToTreeEnsembleIni(FeaturesToContentMap fmap,
 
         protected int AppendComments(StringBuilder sb, string trainingParams)
         {
-            sb.AppendFormat("\n\n[Comments]\nC:0=Regression Tree Ensemble\nC:1=Generated using FastTree\nC:2=Created on {0}\n", DateTime.Now);
+            sb.AppendFormat("\n\n[Comments]\nC:0=Regression Tree Ensemble\nC:1=Generated using FastTree\nC:2=Created on {0}\n", DateTime.Now.ToString(CultureInfo.InvariantCulture));
 
             string[] trainingParamsList = trainingParams.Split(new char[] { '\n' });
             int i = 0;
             for (; i < trainingParamsList.Length; ++i)
             {
                 if (trainingParamsList[i].Length > 0)
                 {
-                    sb.AppendFormat("C:{0}=PARAM:{1}\n", i + 3, trainingParamsList[i]);
+                    sb.AppendFormat(CultureInfo.InvariantCulture, "C:{0}=PARAM:{1}\n", i + 3, trainingParamsList[i]);
                 }
             }
             return i + 3;
@@ -328,15 +329,15 @@ public string ToGainSummary(FeaturesToContentMap fmap, Dictionary<int, int> feat
             foreach (var pair in sortedByGain)
             {
                 int outputInputId = featureToID.ContainsKey(pair.Key) ? featureToID[pair.Key] : 0;
-                output.Append(string.Format("C:{0}=FG:I{1}:{2}:{3}\n", startingCommentNumber++, outputInputId,
-                    fmap.GetName(pair.Key), Math.Pow(pair.Value, power) / normalizingFactor));
+                output.AppendFormat(CultureInfo.InvariantCulture, "C:{0}=FG:I{1}:{2}:{3}\n", startingCommentNumber++, outputInputId,
+                    fmap.GetName(pair.Key), Math.Pow(pair.Value, power) / normalizingFactor);
             }
             return output.ToString();
         }
 
         /// <summary>
         /// Returns a vector of feature contributions for a given example.
-        /// <paramref name="builder"/> is used as a buffer to accumulate the contributions across trees. 
+        /// <paramref name="builder"/> is used as a buffer to accumulate the contributions across trees.
         /// If <paramref name="builder"/> is null, it will be created, otherwise it will be reused.
         /// </summary>
         internal void GetFeatureContributions(ref VBuffer<float> features, ref VBuffer<float> contribs, ref BufferBuilder<float> builder)