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Merged
merged 10 commits into from
May 8, 2020
Merged

Adding vector tests for KeyToValue and ValueToKey #5090

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fcfec4b
adding vector test for key2val
kere-nel May 4, 2020
31bc4b9
fix for key2value
kere-nel May 5, 2020
5655100
adding value2key test
kere-nel May 5, 2020
540ba50
keytovector fix
kere-nel May 5, 2020
2fadb21
adding test
kere-nel May 5, 2020
5d95f58
format changes
kere-nel May 5, 2020
4724582
adding baselines
kere-nel May 6, 2020
4497038
fixing unknown value mapping
kere-nel May 6, 2020
ebea3a0
updating baselines
kere-nel May 6, 2020
14bae44
adding new line
kere-nel May 7, 2020
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7 changes: 4 additions & 3 deletions src/Microsoft.ML.Data/Transforms/KeyToValue.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -505,19 +505,20 @@ public override bool SaveOnnx(OnnxContext ctx, string srcVariableName, string ds
// Onnx expects the input keys to be int64s. But the input data can come from an ML.NET node that
// may output a uint32. So cast it here to ensure that the data is treated correctly
opType = "Cast";
var castNodeOutput = ctx.AddIntermediateVariable(NumberDataViewType.Int64, "CastNodeOutput");
var srcShape = (int)ctx.RetrieveShapeOrNull(srcVariableName)[1];
var castNodeOutput = ctx.AddIntermediateVariable(new VectorDataViewType(NumberDataViewType.Int64, srcShape), "CastNodeOutput");
var castNode = ctx.CreateNode(opType, srcVariableName, castNodeOutput, ctx.GetNodeName(opType), "");
var t = InternalDataKindExtensions.ToInternalDataKind(DataKind.Int64).ToType();
castNode.AddAttribute("to", t);

var labelEncoderOutput = dstVariableName;
var labelEncoderInput = srcVariableName;
if (TypeOutput == NumberDataViewType.Double || TypeOutput == BooleanDataViewType.Instance)
labelEncoderOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "CastNodeOutput");
labelEncoderOutput = ctx.AddIntermediateVariable(new VectorDataViewType(NumberDataViewType.Single, srcShape), "CastNodeOutput");
else if (TypeOutput == NumberDataViewType.Int64 || TypeOutput == NumberDataViewType.UInt16 ||
TypeOutput == NumberDataViewType.Int32 || TypeOutput == NumberDataViewType.Int16 ||
TypeOutput == NumberDataViewType.UInt64 || TypeOutput == NumberDataViewType.UInt32)
labelEncoderOutput = ctx.AddIntermediateVariable(TextDataViewType.Instance, "CastNodeOutput");
labelEncoderOutput = ctx.AddIntermediateVariable(new VectorDataViewType(TextDataViewType.Instance, srcShape), "CastNodeOutput");

opType = "LabelEncoder";
var node = ctx.CreateNode(opType, castNodeOutput, labelEncoderOutput, ctx.GetNodeName(opType));
Expand Down
24 changes: 14 additions & 10 deletions src/Microsoft.ML.Data/Transforms/KeyToVector.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -689,27 +689,31 @@ private JToken SaveAsPfaCore(BoundPfaContext ctx, int iinfo, ColInfo info, JToke

private void SaveAsOnnxCore(OnnxContext ctx, int iinfo, ColInfo info, string srcVariableName, string dstVariableName)
{
var shape = ctx.RetrieveShapeOrNull(srcVariableName);
// Make sure that shape must present for calculating the reduction axes. The shape here is generally not null
// because inputs and outputs of a transform are declared with shapes.
Contracts.CheckValue(shape, nameof(shape));
var dim = info.TypeSrc.GetValueCount();

string opType = "Cast";
var castOutput = ctx.AddIntermediateVariable(NumberDataViewType.Int64, opType);
var castOutput = ctx.AddIntermediateVariable(new VectorDataViewType(NumberDataViewType.Int64, dim), opType);
var castNode = ctx.CreateNode(opType, srcVariableName, castOutput, ctx.GetNodeName(opType), "");
castNode.AddAttribute("to", typeof(long));

opType = "OneHotEncoder";
var isOutputCountVector = _parent._columns[iinfo].OutputCountVector;
var categoryRange = info.TypeSrc.GetItemType().GetKeyCountAsInt32(Host);
var encodedVariableName = ctx.AddIntermediateVariable(new VectorDataViewType(NumberDataViewType.Single, 1, categoryRange), "encoded");
var typeShape = new VectorDataViewType(NumberDataViewType.Single, dim, categoryRange);

var encodedVariableName = (isOutputCountVector && info.TypeSrc is VectorDataViewType) ?
ctx.AddIntermediateVariable(typeShape, "encoded") : dstVariableName;
var node = ctx.CreateNode(opType, castOutput, encodedVariableName, ctx.GetNodeName(opType));
node.AddAttribute("cats_int64s", Enumerable.Range(1, categoryRange).Select(x => (long)x));
node.AddAttribute("zeros", true);

// OneHotEncoder adds one additional dimension, so we remove it below
opType = "Squeeze";
var reduceNode = ctx.CreateNode(opType, encodedVariableName, dstVariableName, ctx.GetNodeName(opType), "");
reduceNode.AddAttribute("axes", new long[] { shape.Count - 1 });
if (_parent._columns[iinfo].OutputCountVector && info.TypeSrc is VectorDataViewType)
{
opType = "ReduceSum";
var reduceNode = ctx.CreateNode(opType, encodedVariableName, dstVariableName, ctx.GetNodeName(opType), "");
reduceNode.AddAttribute("axes", new long[] { 1 });
reduceNode.AddAttribute("keepdims", 0);
}
}
}
}
Expand Down
14 changes: 10 additions & 4 deletions src/Microsoft.ML.Data/Transforms/ValueToKeyMappingTransformer.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -787,7 +787,8 @@ private IEnumerable<T> GetTermsAndIds<T>(int iinfo, out long[] termIds)
private void CastInputToString<T>(OnnxContext ctx, out OnnxNode node, out long[] termIds, string srcVariableName, int iinfo,
string opType, string labelEncoderOutput)
{
var castOutput = ctx.AddIntermediateVariable(TextDataViewType.Instance, "castOutput");
var srcShape = ctx.RetrieveShapeOrNull(srcVariableName);
var castOutput = ctx.AddIntermediateVariable(new VectorDataViewType(TextDataViewType.Instance, (int)srcShape[1]), "castOutput");
var castNode = ctx.CreateNode("Cast", srcVariableName, castOutput, ctx.GetNodeName("Cast"), "");
var t = InternalDataKindExtensions.ToInternalDataKind(DataKind.String).ToType();
castNode.AddAttribute("to", t);
Expand All @@ -799,21 +800,23 @@ private void CastInputToString<T>(OnnxContext ctx, out OnnxNode node, out long[]
private void CastInputToFloat<T>(OnnxContext ctx, out OnnxNode node, out long[] termIds, string srcVariableName, int iinfo,
string opType, string labelEncoderOutput)
{
var castOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "castOutput");
var srcShape = ctx.RetrieveShapeOrNull(srcVariableName);
var castOutput = ctx.AddIntermediateVariable(new VectorDataViewType(NumberDataViewType.Single, (int)srcShape[1]), "castOutput");
var castNode = ctx.CreateNode("Cast", srcVariableName, castOutput, ctx.GetNodeName("Cast"), "");
var t = InternalDataKindExtensions.ToInternalDataKind(DataKind.Single).ToType();
castNode.AddAttribute("to", t);
node = ctx.CreateNode(opType, castOutput, labelEncoderOutput, ctx.GetNodeName(opType));
var terms = GetTermsAndIds<T>(iinfo, out termIds);
node.AddAttribute("keys_floats", terms.Select(item => Convert.ToSingle(item)));
}

private bool SaveAsOnnxCore(OnnxContext ctx, int iinfo, ColInfo info, string srcVariableName, string dstVariableName)
{
OnnxNode node;
long[] termIds;
string opType = "LabelEncoder";
OnnxNode castNode;
var labelEncoderOutput = ctx.AddIntermediateVariable(NumberDataViewType.Int64, "LabelEncoderOutput");
var labelEncoderOutput = ctx.AddIntermediateVariable(new VectorDataViewType(NumberDataViewType.Int64, _types[iinfo].GetValueCount()), "LabelEncoderOutput");

var type = info.TypeSrc.GetItemType();
if (type.Equals(TextDataViewType.Instance))
Expand Down Expand Up @@ -876,7 +879,10 @@ private bool SaveAsOnnxCore(OnnxContext ctx, int iinfo, ColInfo info, string src
return false;
}

node.AddAttribute("default_int64", -1);
//Unknown keys should map to 0
node.AddAttribute("default_int64", 0);
node.AddAttribute("default_string", "0");
node.AddAttribute("default_float", 0f);
node.AddAttribute("values_int64s", termIds);

// Onnx outputs an Int64, but ML.NET outputs a keytype. So cast it here
Expand Down
52 changes: 10 additions & 42 deletions ...Output/Common/Onnx/BinaryClassification/BreastCancer/ExcludeVariablesInOnnxConversion.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -33,9 +33,17 @@
},
{
"name": "default_int64",
"i": "-1",
"type": "INT"
},
{
"name": "default_string",
"s": "MA==",
"type": "STRING"
},
{
"name": "default_float",
"type": "FLOAT"
},
{
"name": "values_int64s",
"ints": [
Expand Down Expand Up @@ -94,7 +102,7 @@
"Cast"
],
"output": [
"encoded"
"F21"
],
"name": "OneHotEncoder",
"opType": "OneHotEncoder",
Expand Down Expand Up @@ -123,25 +131,6 @@
],
"domain": "ai.onnx.ml"
},
{
"input": [
"encoded"
],
"output": [
"F21"
],
"name": "Squeeze",
"opType": "Squeeze",
"attribute": [
{
"name": "axes",
"ints": [
"1"
],
"type": "INTS"
}
]
},
{
"input": [
"F21"
Expand Down Expand Up @@ -673,27 +662,6 @@
}
}
},
{
"name": "encoded",
"type": {
"tensorType": {
"elemType": 1,
"shape": {
"dim": [
{
"dimValue": "-1"
},
{
"dimValue": "1"
},
{
"dimValue": "10"
}
]
}
}
}
},
{
"name": "F22",
"type": {
Expand Down
52 changes: 10 additions & 42 deletions test/BaselineOutput/Common/Onnx/BinaryClassification/BreastCancer/ModelWithLessIO.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -32,9 +32,17 @@
},
{
"name": "default_int64",
"i": "-1",
"type": "INT"
},
{
"name": "default_string",
"s": "MA==",
"type": "STRING"
},
{
"name": "default_float",
"type": "FLOAT"
},
{
"name": "values_int64s",
"ints": [
Expand Down Expand Up @@ -92,7 +100,7 @@
"Cast"
],
"output": [
"encoded"
"F21"
],
"name": "OneHotEncoder",
"opType": "OneHotEncoder",
Expand Down Expand Up @@ -120,25 +128,6 @@
],
"domain": "ai.onnx.ml"
},
{
"input": [
"encoded"
],
"output": [
"F21"
],
"name": "Squeeze",
"opType": "Squeeze",
"attribute": [
{
"name": "axes",
"ints": [
"1"
],
"type": "INTS"
}
]
},
{
"input": [
"F1",
Expand Down Expand Up @@ -1022,27 +1011,6 @@
}
}
},
{
"name": "encoded",
"type": {
"tensorType": {
"elemType": 1,
"shape": {
"dim": [
{
"dimValue": "-1"
},
{
"dimValue": "1"
},
{
"dimValue": "9"
}
]
}
}
}
},
{
"name": "VectorFeaturizerOutput",
"type": {
Expand Down
10 changes: 9 additions & 1 deletion ...sClassification/BreastCancer/MultiClassificationLogisticRegressionSaveModelToOnnxTest.txt
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Expand Up @@ -99,9 +99,17 @@
},
{
"name": "default_int64",
"i": "-1",
"type": "INT"
},
{
"name": "default_string",
"s": "MA==",
"type": "STRING"
},
{
"name": "default_float",
"type": "FLOAT"
},
{
"name": "values_int64s",
"ints": [
Expand Down
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