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Merged
ganik merged 3 commits into from
Aug 20, 2019
Merged

Load TransformerChain model file in ModelFileUtils #4110

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3edc0fe
Load TransformerChain model file in ModelFileUtils
najeeb-kazmi Aug 13, 2019
710a295
Add test
najeeb-kazmi Aug 14, 2019
fa7001d
PR feedback
najeeb-kazmi Aug 14, 2019
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2 changes: 1 addition & 1 deletion src/Microsoft.ML.Data/Model/ModelOperationsCatalog.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@ namespace Microsoft.ML
/// </summary>
public sealed class ModelOperationsCatalog : IInternalCatalog
{
private const string SchemaEntryName = "Schema";
internal const string SchemaEntryName = "Schema";

IHostEnvironment IInternalCatalog.Environment => _env;
private readonly IHostEnvironment _env;
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11 changes: 11 additions & 0 deletions src/Microsoft.ML.Data/Utilities/ModelFileUtils.cs
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Expand Up @@ -25,6 +25,8 @@ internal static class ModelFileUtils
{
public const string DirPredictor = "Predictor";
public const string DirDataLoaderModel = "DataLoaderModel";
public const string DirTransformerChain = TransformerChain.LoaderSignature;
public const string SchemaEntryName = ModelOperationsCatalog.SchemaEntryName;
// ResultsProcessor needs access to this constant.
public const string DirTrainingInfo = "TrainingInfo";

Expand Down Expand Up @@ -64,6 +66,15 @@ public static IDataView LoadPipeline(IHostEnvironment env, RepositoryReader rep,
Contracts.CheckValue(env, nameof(env));
env.CheckValue(rep, nameof(rep));
env.CheckValue(files, nameof(files));

var entry = rep.OpenEntryOrNull(SchemaEntryName);
if (entry != null)
{
var loader = new BinaryLoader(env, new BinaryLoader.Arguments(), entry.Stream);
ModelLoadContext.LoadModel<ITransformer, SignatureLoadModel>(env, out var transformerChain, rep, DirTransformerChain);
return transformerChain.Transform(loader);
}

using (var ent = rep.OpenEntry(DirDataLoaderModel, ModelLoadContext.ModelStreamName))
{
ILegacyDataLoader loader;
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94 changes: 94 additions & 0 deletions test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs
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Expand Up @@ -612,6 +612,100 @@ public void EntryPointExecGraphCommand()
cmd.Run();
}

[Fact]
public void ScoreTransformerChainModel()
{
var dataPath = GetDataPath("wikipedia-detox-250-line-data.tsv");
var modelPath = DeleteOutputPath("model.zip");
var outputDataPath = DeleteOutputPath("scored.idv");

var mlContext = new MLContext();

var data = new TextLoader(mlContext,
new TextLoader.Options()
{
AllowQuoting = true,
Separator = "\t",
HasHeader = true,
Columns = new[]
{
new TextLoader.Column("Label", DataKind.Boolean, 0),
new TextLoader.Column("SentimentText", DataKind.String, 1)
}
}).Load(dataPath);

var pipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
.Append(mlContext.BinaryClassification.Trainers.AveragedPerceptron());

var model = pipeline.Fit(data);

mlContext.Model.Save(model, data.Schema, modelPath);

string inputGraph = string.Format(@"
{{
'Inputs': {{
'file': '{0}',
'transform_model': '{1}'
}},
'Nodes': [
{{
'Name': 'Data.CustomTextLoader',
'Inputs': {{
'CustomSchema': 'col=Sentiment:I8:0 col=SentimentText:TX:1 quote+ header=+ sep=tab',
'InputFile': '$file'
}},
'Outputs': {{
'Data': '$data'
}}
}},
{{
'Name': 'Transforms.DatasetTransformScorer',
'Inputs': {{
'Data': '$data',
'TransformModel': '$transform_model'
}},
'Outputs': {{
'ScoredData': '$scoredVectorData'
}}
}},
{{
'Inputs': {{
'Data': '$scoredVectorData'
}},
'Name': 'Transforms.ScoreColumnSelector',
'Outputs': {{
'OutputData': '$scoreColumnsOnlyData'
}}
}},
{{
'Inputs': {{
'Data': '$scoreColumnsOnlyData',
'PredictedLabelColumn': 'PredictedLabel'
}},
'Name': 'Transforms.PredictedLabelColumnOriginalValueConverter',
'Outputs': {{
'OutputData': '$output_data'
}}
}}
],
'Outputs': {{
'output_data': '{2}'
}}
}}", EscapePath(dataPath), EscapePath(modelPath), EscapePath(outputDataPath));

var jsonPath = DeleteOutputPath("graph.json");
File.WriteAllLines(jsonPath, new[] { inputGraph });

var args = new ExecuteGraphCommand.Arguments() { GraphPath = jsonPath };
var cmd = new ExecuteGraphCommand(Env, args);
cmd.Run();

var loadedData = mlContext.Data.LoadFromBinary(outputDataPath);

Assert.NotNull(loadedData.Schema.GetColumnOrNull("PredictedLabel"));
Assert.NotNull(loadedData.Schema.GetColumnOrNull("Score"));
}

//[Fact]
//public void EntryPointArrayOfVariables()
//{
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