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migrate to private ML.NET nuget for latest bug fixes (dotnet#131)
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‎NuGet.Config‎

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<configuration>
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<packageSources>
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<add key="nuget.org" value="https://api.nuget.org/v3/index.json" protocolVersion="3" />
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<add key="DotNetMyGet" value="https://dotnet.myget.org/F/dotnet-core/api/v3/index.json" protocolVersion="3" />
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</packageSources>
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</configuration>

‎src/Microsoft.ML.Auto/API/BinaryClassificationExperiment.cs‎

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using System.Collections.Generic;
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using System.Linq;
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using Microsoft.Data.DataView;
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using Microsoft.ML.Core.Data;
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using Microsoft.ML.Data;
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namespace Microsoft.ML.Auto

‎src/Microsoft.ML.Auto/API/MulticlassClassificationExperiment.cs‎

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using System.Collections.Generic;
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using System.Linq;
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using Microsoft.Data.DataView;
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using Microsoft.ML.Core.Data;
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using Microsoft.ML.Data;
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namespace Microsoft.ML.Auto

‎src/Microsoft.ML.Auto/API/Pipeline.cs‎

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// See the LICENSE file in the project root for more information.
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using System.Collections.Generic;
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using Microsoft.ML.Core.Data;
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namespace Microsoft.ML.Auto
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{

‎src/Microsoft.ML.Auto/API/RegressionExperiment.cs‎

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using System.Collections.Generic;
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using System.Linq;
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using Microsoft.Data.DataView;
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using Microsoft.ML.Core.Data;
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using Microsoft.ML.Data;
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namespace Microsoft.ML.Auto

‎src/Microsoft.ML.Auto/API/RunResult.cs‎

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using System;
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using System.Linq;
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using Microsoft.ML.Core.Data;
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namespace Microsoft.ML.Auto
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{

‎src/Microsoft.ML.Auto/AutoMlUtils.cs‎

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@@ -23,11 +23,6 @@ public static void Assert(bool boolVal, string message = null)
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}
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}
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public static IDataView Take(this IDataView data, MLContext context, int count)
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{
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return TakeFilter.Create(context, data, count);
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}
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public static IDataView DropLastColumn(this IDataView data, MLContext context)
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{
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return context.Transforms.DropColumns(data.Schema[data.Schema.Count - 1].Name).Fit(data).Transform(data);
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MLContext context, IDataView trainData)
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{
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IDataView validationData;
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(trainData, validationData) = catalog.TrainTestSplit(trainData);
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var splitData = catalog.TrainTestSplit(trainData);
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trainData = splitData.TrainSet;
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validationData = splitData.TestSet;
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trainData = trainData.DropLastColumn(context);
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validationData = validationData.DropLastColumn(context);
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return (trainData, validationData);
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}
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public static IDataView Skip(this IDataView data, MLContext context, int count)
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{
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return SkipFilter.Create(context, data, count);
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}
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public static (string, ColumnType, ColumnPurpose, ColumnDimensions)[] GetColumnInfoTuples(MLContext context,
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public static (string, DataViewType, ColumnPurpose, ColumnDimensions)[] GetColumnInfoTuples(MLContext context,
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IDataView data, ColumnInformation columnInfo)
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{
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var purposes = PurposeInference.InferPurposes(context, data, columnInfo);
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var colDimensions = DatasetDimensionsApi.CalcColumnDimensions(context, data, purposes);
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var cols = new (string, ColumnType, ColumnPurpose, ColumnDimensions)[data.Schema.Count];
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var cols = new (string, DataViewType, ColumnPurpose, ColumnDimensions)[data.Schema.Count];
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for (var i = 0; i < cols.Length; i++)
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{
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var schemaCol = data.Schema[i];

‎src/Microsoft.ML.Auto/ColumnInference/ColumnInferenceApi.cs‎

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@@ -52,7 +52,7 @@ public static ColumnInferenceResults InferColumns(MLContext context, string path
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var loaderColumns = ColumnTypeInference.GenerateLoaderColumns(typeInference.Columns);
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var typedLoaderArgs = new TextLoader.Arguments
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{
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Column = loaderColumns,
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Columns = loaderColumns,
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Separators = new[] { splitInference.Separator.Value },
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AllowSparse = splitInference.AllowSparse,
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AllowQuoting = splitInference.AllowQuote,
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var textLoaderArgs = new TextLoader.Arguments()
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{
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Column = columnResults.ToArray(),
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Columns = columnResults.ToArray(),
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AllowQuoting = splitInference.AllowQuote,
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AllowSparse = splitInference.AllowSparse,
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Separators = new char[] { splitInference.Separator.Value },

‎src/Microsoft.ML.Auto/ColumnInference/ColumnInformationUtil.cs‎

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@@ -82,7 +82,7 @@ internal static ColumnInformation BuildColumnInfo(IEnumerable<(string name, Colu
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return columnInfo;
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}
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public static ColumnInformation BuildColumnInfo(IEnumerable<(string, ColumnType, ColumnPurpose, ColumnDimensions)> columns)
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public static ColumnInformation BuildColumnInfo(IEnumerable<(string, DataViewType, ColumnPurpose, ColumnDimensions)> columns)
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{
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return BuildColumnInfo(columns.Select(c => (c.Item1, c.Item3)));
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}

‎src/Microsoft.ML.Auto/ColumnInference/ColumnTypeInference.cs‎

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{
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private readonly ReadOnlyMemory<char>[] _data;
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private readonly int _columnId;
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private PrimitiveType _suggestedType;
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private PrimitiveDataViewType _suggestedType;
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private bool? _hasHeader;
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public int ColumnId
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{
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get { return _columnId; }
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}
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public PrimitiveType SuggestedType
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public PrimitiveDataViewType SuggestedType
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{
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get { return _suggestedType; }
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set { _suggestedType = value; }
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{
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public readonly int ColumnIndex;
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public PrimitiveType ItemType;
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public PrimitiveDataViewType ItemType;
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public string SuggestedName;
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101-
public Column(int columnIndex, string suggestedName, PrimitiveType itemType)
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public Column(int columnIndex, string suggestedName, PrimitiveDataViewType itemType)
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{
103103
ColumnIndex = columnIndex;
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SuggestedName = suggestedName;
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continue;
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}
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col.SuggestedType = BoolType.Instance;
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col.SuggestedType = BooleanDataViewType.Instance;
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bool first;
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166166
col.HasHeader = !Conversions.TryParse(in col.RawData[0], out first);
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continue;
186186
}
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188-
col.SuggestedType = NumberType.R4;
188+
col.SuggestedType = NumberDataViewType.Single;
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190190
var headerStr = col.RawData[0].ToString();
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col.HasHeader = !double.TryParse(headerStr, out var doubleVal);
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202202
if (col.SuggestedType != null)
203203
continue;
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205-
col.SuggestedType = TextType.Instance;
205+
col.SuggestedType = TextDataViewType.Instance;
206206
col.HasHeader = IsLookLikeHeader(col.RawData[0]);
207207
}
208208
}
@@ -258,14 +258,14 @@ private static InferenceResult InferTextFileColumnTypesCore(MLContext context, I
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// read the file as the specified number of text columns
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var textLoaderArgs = new TextLoader.Arguments
260260
{
261-
Column = new[] { new TextLoader.Column("C", DataKind.TX, 0, args.ColumnCount - 1) },
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Columns = new[] { new TextLoader.Column("C", DataKind.TX, 0, args.ColumnCount - 1) },
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Separators = new[] { args.Separator },
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AllowSparse = args.AllowSparse,
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AllowQuoting = args.AllowQuote,
265265
};
266266
var textLoader = new TextLoader(context, textLoaderArgs);
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var idv = textLoader.Read(fileSource);
268-
idv = idv.Take(context, args.MaxRowsToRead);
268+
idv = context.Data.TakeRows(idv, args.MaxRowsToRead);
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// read all the data into memory.
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// list items are rows of the dataset.
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// if label column has all Boolean values, set its type as Boolean
362362
if (labelColumn.HasAllBooleanValues())
363363
{
364-
labelColumn.SuggestedType = BoolType.Instance;
364+
labelColumn.SuggestedType = BooleanDataViewType.Instance;
365365
}
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367367
var outCols = cols.Select(x => new Column(x.ColumnId, x.Name, x.SuggestedType)).ToArray();

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