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Merged
ganik merged 6 commits into from
Sep 6, 2019
Merged

Implement ONNX conversion for TypeConverting transform #4155

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bfe2435
Implement ONNX conversion for TypeConverting transform
ganik Aug 29, 2019
e12e12e
Changed ICanSaveOnnx to ISaveAsOnnx and removed experimental flag.
harishsk Aug 30, 2019
860900b
Addded test for onnx type conversion and fixed related bugs
harishsk Aug 31, 2019
d184d3d
Fixed baseline versions of failing onnx tests
harishsk Sep 1, 2019
260ab5d
Fixed baseline for another test
harishsk Sep 1, 2019
94a9447
Replaced hardcoded column names
harishsk Sep 4, 2019
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1 change: 1 addition & 0 deletions src/Microsoft.ML.Data/Model/Onnx/OnnxNode.cs
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Expand Up @@ -29,5 +29,6 @@ internal abstract class OnnxNode
public abstract void AddAttribute(string argName, string[] value);
public abstract void AddAttribute(string argName, IEnumerable<string> value);
public abstract void AddAttribute(string argName, IEnumerable<bool> value);
public abstract void AddAttribute(string argName, Type t);
}
}
19 changes: 7 additions & 12 deletions src/Microsoft.ML.Data/Transforms/TypeConverting.cs
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Expand Up @@ -381,13 +381,13 @@ internal static bool GetNewType(IExceptionContext ectx, DataViewType srcType, In
return true;
}

private sealed class Mapper : OneToOneMapperBase, ICanSaveOnnx
private sealed class Mapper : OneToOneMapperBase, ISaveAsOnnx
{
private readonly TypeConvertingTransformer _parent;
private readonly DataViewType[] _types;
private readonly int[] _srcCols;

public bool CanSaveOnnx(OnnxContext ctx) => ctx.GetOnnxVersion() == OnnxVersion.Experimental;
public bool CanSaveOnnx(OnnxContext ctx) => true;

public Mapper(TypeConvertingTransformer parent, DataViewSchema inputSchema)
: base(parent.Host.Register(nameof(Mapper)), parent, inputSchema)
Expand Down Expand Up @@ -497,22 +497,17 @@ public void SaveAsOnnx(OnnxContext ctx)

private bool SaveAsOnnxCore(OnnxContext ctx, int iinfo, string srcVariableName, string dstVariableName)
{
var opType = "CSharp";
var node = ctx.CreateNode(opType, srcVariableName, dstVariableName, ctx.GetNodeName(opType));
node.AddAttribute("type", LoaderSignature);
node.AddAttribute("to", (byte)_parent._columns[iinfo].OutputKind);
if (_parent._columns[iinfo].OutputKeyCount != null)
{
var key = (KeyDataViewType)_types[iinfo].GetItemType();
node.AddAttribute("max", key.Count);
}
var opType = "Cast";
var node = ctx.CreateNode(opType, srcVariableName, dstVariableName, ctx.GetNodeName(opType), "");
var t = _parent._columns[iinfo].OutputKind.ToInternalDataKind().ToType();
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@ganik ganik Aug 29, 2019 •
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var t [](start = 16, length = 6)

Need to handle key type #Resolved

node.AddAttribute("to", t);
return true;
}
}
}

/// <summary>
/// Estimator for <see cref="KeyToVectorMappingTransformer"/>. Converts the underlying input column type to a new type.
/// Estimator for <see cref="TypeConvertingTransformer"/>. Converts the underlying input column type to a new type.
/// The input and output column types need to be compatible.
/// <see cref="PrimitiveDataViewType"/>
/// </summary>
Expand Down
8 changes: 7 additions & 1 deletion src/Microsoft.ML.KMeansClustering/KMeansModelParameters.cs
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Expand Up @@ -351,11 +351,17 @@ bool ISingleCanSaveOnnx.SaveAsOnnx(OnnxContext ctx, string[] outputNames, string
var addNodeY = ctx.CreateNode("Add", new[] { nameZ, nameC2 }, new[] { nameY }, ctx.GetNodeName("Add"), "");

// Compute the most-matched cluster index, L
var nameL = outputNames[0];
var nameL = "ArgMinInt64";
var predictNodeL = ctx.CreateNode("ArgMin", nameY, nameL, ctx.GetNodeName("ArgMin"), "");
predictNodeL.AddAttribute("axis", 1);
predictNodeL.AddAttribute("keepdims", 1);

// ArgMin outputs an Int64. But ML.NET's KMeans trainer outputs a UINT32.
// Cast the output here to UInt32 to make them compatible
var predictedNode = ctx.CreateNode("Cast", nameL, outputNames[0], ctx.GetNodeName("Cast"), "");
var t = InternalDataKindExtensions.ToInternalDataKind(DataKind.UInt32).ToType();
predictedNode.AddAttribute("to", t);

return true;
}
}
Expand Down
2 changes: 2 additions & 0 deletions src/Microsoft.ML.OnnxConverter/OnnxNodeImpl.cs
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Expand Up @@ -43,5 +43,7 @@ public override void AddAttribute(string argName, string value)
=> OnnxUtils.NodeAddAttributes(_node, argName, value);
public override void AddAttribute(string argName, bool value)
=> OnnxUtils.NodeAddAttributes(_node, argName, value);
public override void AddAttribute(string argName, Type value)
=> OnnxUtils.NodeAddAttributes(_node, argName, value);
}
}
79 changes: 48 additions & 31 deletions src/Microsoft.ML.OnnxConverter/OnnxUtils.cs
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Expand Up @@ -70,6 +70,14 @@ private static AttributeProto MakeAttribute(string key)
return attribute;
}

private static AttributeProto MakeAttribute(string key, TensorProto.Types.DataType value)
{
AttributeProto attribute = MakeAttribute(key);
attribute.Type = AttributeProto.Types.AttributeType.Int;
attribute.I = (int)value;
return attribute;
}

private static AttributeProto MakeAttribute(string key, double value)
{
AttributeProto attribute = MakeAttribute(key);
Expand Down Expand Up @@ -211,6 +219,45 @@ public static void NodeAddAttributes(NodeProto node, string argName, IEnumerable

public static void NodeAddAttributes(NodeProto node, string argName, bool value)
=> node.Attribute.Add(MakeAttribute(argName, value));
public static void NodeAddAttributes(NodeProto node, string argName, Type value)
=> node.Attribute.Add(MakeAttribute(argName, ConvertToTensorProtoType(value)));

private static TensorProto.Types.DataType ConvertToTensorProtoType(Type rawType)
{
var dataType = TensorProto.Types.DataType.Undefined;

if (rawType == typeof(bool))
dataType = TensorProto.Types.DataType.Float;
else if (rawType == typeof(ReadOnlyMemory<char>))
dataType = TensorProto.Types.DataType.String;
else if (rawType == typeof(sbyte))
dataType = TensorProto.Types.DataType.Int8;
else if (rawType == typeof(byte))
dataType = TensorProto.Types.DataType.Uint8;
else if (rawType == typeof(short))
dataType = TensorProto.Types.DataType.Int16;
else if (rawType == typeof(ushort))
dataType = TensorProto.Types.DataType.Uint16;
else if (rawType == typeof(int))
dataType = TensorProto.Types.DataType.Int32;
else if (rawType == typeof(uint))
dataType = TensorProto.Types.DataType.Uint32;
else if (rawType == typeof(long))
dataType = TensorProto.Types.DataType.Int64;
else if (rawType == typeof(ulong))
dataType = TensorProto.Types.DataType.Uint64;
else if (rawType == typeof(float))
dataType = TensorProto.Types.DataType.Float;
else if (rawType == typeof(double))
dataType = TensorProto.Types.DataType.Double;
else
{
string msg = "Unsupported type: " + rawType.ToString();
Contracts.Check(false, msg);
}

return dataType;
}

private static ByteString StringToByteString(ReadOnlyMemory<char> str) => ByteString.CopyFrom(Encoding.UTF8.GetBytes(str.ToString()));
private static IEnumerable<ByteString> StringToByteString(IEnumerable<ReadOnlyMemory<char>> str)
Expand Down Expand Up @@ -295,42 +342,12 @@ public static ModelArgs GetModelArgs(DataViewType type, string colName,
Contracts.CheckValue(type, nameof(type));
Contracts.CheckNonEmpty(colName, nameof(colName));

TensorProto.Types.DataType dataType = TensorProto.Types.DataType.Undefined;
Type rawType;
if (type is VectorDataViewType vectorType)
rawType = vectorType.ItemType.RawType;
else
rawType = type.RawType;

if (rawType == typeof(bool))
dataType = TensorProto.Types.DataType.Float;
else if (rawType == typeof(ReadOnlyMemory<char>))
dataType = TensorProto.Types.DataType.String;
else if (rawType == typeof(sbyte))
dataType = TensorProto.Types.DataType.Int8;
else if (rawType == typeof(byte))
dataType = TensorProto.Types.DataType.Uint8;
else if (rawType == typeof(short))
dataType = TensorProto.Types.DataType.Int16;
else if (rawType == typeof(ushort))
dataType = TensorProto.Types.DataType.Uint16;
else if (rawType == typeof(int))
dataType = TensorProto.Types.DataType.Int32;
else if (rawType == typeof(uint))
dataType = TensorProto.Types.DataType.Int64;
else if (rawType == typeof(long))
dataType = TensorProto.Types.DataType.Int64;
else if (rawType == typeof(ulong))
dataType = TensorProto.Types.DataType.Uint64;
else if (rawType == typeof(float))
dataType = TensorProto.Types.DataType.Float;
else if (rawType == typeof(double))
dataType = TensorProto.Types.DataType.Double;
else
{
string msg = "Unsupported type: " + type.ToString();
Contracts.Check(false, msg);
}
var dataType = ConvertToTensorProtoType(rawType);

string name = colName;
List<long> dimsLocal = null;
Expand Down
2 changes: 1 addition & 1 deletion ...Output/Common/Onnx/BinaryClassification/BreastCancer/ExcludeVariablesInOnnxConversion.txt
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Expand Up @@ -515,7 +515,7 @@
"name": "F20",
"type": {
"tensorType": {
"elemType": "INT64",
"elemType": "UINT32",
"shape": {
"dim": [
{
Expand Down
2 changes: 1 addition & 1 deletion test/BaselineOutput/Common/Onnx/BinaryClassification/BreastCancer/ModelWithLessIO.txt
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Expand Up @@ -842,7 +842,7 @@
"name": "F20",
"type": {
"tensorType": {
"elemType": "INT64",
"elemType": "UINT32",
"shape": {
"dim": [
{
Expand Down
2 changes: 1 addition & 1 deletion test/BaselineOutput/Common/Onnx/BinaryClassification/BreastCancer/OneHotBagPipeline.txt
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Expand Up @@ -598,7 +598,7 @@
"name": "F20",
"type": {
"tensorType": {
"elemType": "INT64",
"elemType": "UINT32",
"shape": {
"dim": [
{
Expand Down
21 changes: 19 additions & 2 deletions test/BaselineOutput/Common/Onnx/Cluster/BreastCancer/Kmeans.txt
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Expand Up @@ -109,7 +109,7 @@
"Score"
],
"output": [
"PredictedLabel"
"ArgMinInt64"
],
"name": "ArgMin",
"opType": "ArgMin",
Expand All @@ -126,6 +126,23 @@
}
]
},
{
"input": [
"ArgMinInt64"
],
"output": [
"PredictedLabel"
],
"name": "Cast",
"opType": "Cast",
"attribute": [
{
"name": "to",
"i": "12",
"type": "INT"
}
]
},
{
"input": [
"Features0"
Expand Down Expand Up @@ -272,7 +289,7 @@
"name": "PredictedLabel0",
"type": {
"tensorType": {
"elemType": "INT64",
"elemType": "UINT32",
"shape": {
"dim": [
{
Expand Down
6 changes: 3 additions & 3 deletions ...sClassification/BreastCancer/MultiClassificationLogisticRegressionSaveModelToOnnxTest.txt
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Expand Up @@ -312,7 +312,7 @@
"name": "Label1",
"type": {
"tensorType": {
"elemType": "INT64",
"elemType": "UINT32",
"shape": {
"dim": [
{
Expand Down Expand Up @@ -348,7 +348,7 @@
"name": "PredictedLabel0",
"type": {
"tensorType": {
"elemType": "INT64",
"elemType": "UINT32",
"shape": {
"dim": [
{
Expand Down Expand Up @@ -404,7 +404,7 @@
"name": "Label0",
"type": {
"tensorType": {
"elemType": "INT64",
"elemType": "UINT32",
"shape": {
"dim": [
{
Expand Down
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