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Fixes to onnx export for text related transforms #4891

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Merged
ganik merged 1 commit into from
Feb 26, 2020
Merged

Fixes to onnx export for text related transforms #4891

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9 changes: 3 additions & 6 deletions ...Microsoft.ML.StandardTrainers/Standard/LogisticRegression/MulticlassLogisticRegression.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -1009,12 +1009,9 @@ private bool SaveAsOnnxCore(OnnxContext ctx, string[] outputs, string featureCol
var t = InternalDataKindExtensions.ToInternalDataKind(DataKind.UInt32).ToType();
castNode.AddAttribute("to", t);

// The predictedLabel is a scalar. But the onnx output of ML.NET output expects a [1x1] tensor for output. So reshape it here
opType = "Reshape";
long[] shape = { 1, 1 };
long[] shapeDim = { 2 };
var shapeVar = ctx.AddInitializer(shape, shapeDim, "ShapeVar");
var reshapeNode = ctx.CreateNode(opType, new[] { castNodeOutput, shapeVar }, new[] { predictedLabelUint32 }, ctx.GetNodeName(opType), "");
opType = "Unsqueeze";
var unsqueezeNode = ctx.CreateNode(opType, castNodeOutput, predictedLabelUint32, ctx.GetNodeName(opType), "");
unsqueezeNode.AddAttribute("axes", new long[] { 0 });

return true;
}
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4 changes: 2 additions & 2 deletions src/Microsoft.ML.Transforms/Text/TextNormalizing.cs
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Expand Up @@ -238,7 +238,7 @@ private void SaveAsOnnxCore(OnnxContext ctx, string srcVariableName, string dstV
var opType = "Squeeze";
var squeezeOutput = ctx.AddIntermediateVariable(null, "SqueezeOutput", true);
var node = ctx.CreateNode(opType, srcVariableName, squeezeOutput, ctx.GetNodeName(opType), "");
node.AddAttribute("axes", new long[] { 0 });
node.AddAttribute("axes", new long[] { 1 });

opType = "StringNormalizer";
var normalizerOutput = ctx.AddIntermediateVariable(null, "NormalizerOutput", true);
Expand All @@ -249,7 +249,7 @@ private void SaveAsOnnxCore(OnnxContext ctx, string srcVariableName, string dstV

opType = "Unsqueeze";
node = ctx.CreateNode(opType, normalizerOutput, dstVariableName, ctx.GetNodeName(opType), "");
node.AddAttribute("axes", new long[] { 0 });
node.AddAttribute("axes", new long[] { 1 });
}
protected override DataViewSchema.DetachedColumn[] GetOutputColumnsCore()
{
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26 changes: 19 additions & 7 deletions src/Microsoft.ML.Transforms/Text/TokenizingByCharacters.cs
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Expand Up @@ -190,6 +190,7 @@ private sealed class Mapper : OneToOneMapperBase, ISaveAsOnnx
private readonly DataViewType _type;
private readonly TokenizingByCharactersTransformer _parent;
private readonly bool[] _isSourceVector;
private readonly int[] _sourceVectorLength;
// Constructed and cached the first time it is needed.
private volatile string _keyValuesStr;
private volatile int[] _keyValuesBoundaries;
Expand All @@ -201,8 +202,13 @@ public Mapper(TokenizingByCharactersTransformer parent, DataViewSchema inputSche
var keyType = new KeyDataViewType(typeof(ushort), CharsCount);
_type = new VectorDataViewType(keyType);
_isSourceVector = new bool[_parent.ColumnPairs.Length];
_sourceVectorLength = new int[_parent.ColumnPairs.Length];
for (int i = 0; i < _isSourceVector.Length; i++)
_isSourceVector[i] = inputSchema[_parent.ColumnPairs[i].inputColumnName].Type is VectorDataViewType;
{
var type = inputSchema[_parent.ColumnPairs[i].inputColumnName].Type;
_isSourceVector[i] = type is VectorDataViewType;
_sourceVectorLength[i] = type.GetValueCount();
}
}

public bool CanSaveOnnx(OnnxContext ctx) => true;
Expand All @@ -219,27 +225,33 @@ public void SaveAsOnnx(OnnxContext ctx)
string outputColumnName = _parent.ColumnPairs[iinfo].outputColumnName;
string srcVariableName = ctx.GetVariableName(inputColumnName);
string dstVariableName = ctx.AddIntermediateVariable(_type, outputColumnName, true);
SaveAsOnnxCore(ctx, srcVariableName, dstVariableName);
SaveAsOnnxCore(ctx, iinfo, srcVariableName, dstVariableName);
}
}

private void SaveAsOnnxCore(OnnxContext ctx, string srcVariableName, string dstVariableName)
private void SaveAsOnnxCore(OnnxContext ctx, int iinfo, string srcVariableName, string dstVariableName)
{
string opType = "Tokenizer";
string tokenizerOutput = ctx.AddIntermediateVariable(null, "TokenizerOutput", true);
DataViewType dataViewType;
if (_isSourceVector[iinfo])
dataViewType = new VectorDataViewType(TextDataViewType.Instance, _sourceVectorLength[iinfo]);
else
dataViewType = TextDataViewType.Instance;

string tokenizerOutput = ctx.AddIntermediateVariable(dataViewType, "TokenizerOutput", true);
var node = ctx.CreateNode(opType, srcVariableName, tokenizerOutput, ctx.GetNodeName(opType), "com.microsoft");
node.AddAttribute("mark", _parent._useMarkerChars);
node.AddAttribute("mincharnum", 1);
node.AddAttribute("pad_value", "");
node.AddAttribute("separators", new string[] { "" });

opType = "Squeeze";
var squeezeOutput = ctx.AddIntermediateVariable(null, "SqueezeOutput", true);
var squeezeOutput = ctx.AddIntermediateVariable(dataViewType, "SqueezeOutput");
node = ctx.CreateNode(opType, tokenizerOutput, squeezeOutput, ctx.GetNodeName(opType), "");
node.AddAttribute("axes", new long[] { 0 });
node.AddAttribute("axes", new long[] { 1 });

opType = "LabelEncoder";
var labelEncoderOutput = ctx.AddIntermediateVariable(null, "LabelEncoderOutput", true);
var labelEncoderOutput = ctx.AddIntermediateVariable(NumberDataViewType.Int64, "LabelEncoderOutput");
node = ctx.CreateNode(opType, squeezeOutput, labelEncoderOutput, ctx.GetNodeName(opType));

IEnumerable<string> charStrings = Enumerable.Range(0, 65535).Select(x => ((char)x).ToString());
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4 changes: 2 additions & 2 deletions src/Microsoft.ML.Transforms/Text/WordTokenizing.cs
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Expand Up @@ -416,9 +416,9 @@ public void SaveAsOnnx(OnnxContext ctx)
tokenizerNode.AddAttribute("separators", separators);

opType = "Squeeze";
var squeezeOutput = ctx.AddIntermediateVariable(_type, column.Name, true);
var squeezeOutput = ctx.AddIntermediateVariable(_type, column.Name);
var squeezeNode = ctx.CreateNode(opType, intermediateVar, squeezeOutput, ctx.GetNodeName(opType), "");
squeezeNode.AddAttribute("axes", new long[] { 0 });
squeezeNode.AddAttribute("axes", new long[] { 1 });
}
}
}
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27 changes: 12 additions & 15 deletions ...sClassification/BreastCancer/MultiClassificationLogisticRegressionSaveModelToOnnxTest.txt
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Expand Up @@ -274,14 +274,22 @@
},
{
"input": [
"CastNodeOutput",
"ShapeVar"
"CastNodeOutput"
],
"output": [
"PredictedLabel"
],
"name": "Reshape",
"opType": "Reshape"
"name": "Unsqueeze",
"opType": "Unsqueeze",
"attribute": [
{
"name": "axes",
"ints": [
"0"
],
"type": "INTS"
}
]
},
{
"input": [
Expand Down Expand Up @@ -371,17 +379,6 @@
],
"name": "model",
"initializer": [
{
"dims": [
"2"
],
"dataType": 7,
"int64Data": [
"1",
"1"
],
"name": "ShapeVar"
},
{
"dims": [
"1",
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