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Added slot names support for OnnxTransformer #4857

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Feb 19, 2020
Merged

Added slot names support for OnnxTransformer #4857

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eef7621
Added slot names support for OnnxTransformer
harishsk Feb 19, 2020
e2fbac4
Updated baselines for failing tests
harishsk Feb 19, 2020
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34 changes: 33 additions & 1 deletion src/Microsoft.ML.OnnxConverter/SaveOnnxCommand.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -2,8 +2,10 @@
// The .NET Foundation licenses this file to you under the MIT license.
// See the LICENSE file in the project root for more information.

using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using Google.Protobuf;
using Microsoft.ML;
using Microsoft.ML.Command;
Expand Down Expand Up @@ -188,7 +190,9 @@ internal static ModelProto ConvertTransformListToOnnxModel(OnnxContextImpl ctx,
if (outputData.Schema[i].IsHidden)
continue;

var idataviewColumnName = outputData.Schema[i].Name;
var column = outputData.Schema[i];

var idataviewColumnName = column.Name;

// Since the last IDataView also contains columns of the initial IDataView, last IDataView's columns found in
// _inputToDrop should be removed too.
Expand All @@ -204,11 +208,39 @@ internal static ModelProto ConvertTransformListToOnnxModel(OnnxContextImpl ctx,
var trueVariableName = ctx.AddIntermediateVariable(null, idataviewColumnName + ".output", true);
ctx.CreateNode("Identity", variableName, trueVariableName, ctx.GetNodeName("Identity"), "");
ctx.AddOutputVariable(outputData.Schema[i].Type, trueVariableName);

if (column.HasSlotNames())
AddSlotNames(ctx, column);
}

// Add metadata graph outputs

return ctx.MakeModel();
}

private static void AddSlotNames(OnnxContextImpl ctx, DataViewSchema.Column column)
{
VBuffer<ReadOnlyMemory<char>> slotNames = default;
column.GetSlotNames(ref slotNames);
IEnumerable<string> slotNamesAsStrings = slotNames.DenseValues().Select(name => name.ToString());

string opType = "LabelEncoder";
string labelEncoderInputName = $"mlnet.{column.Name}.unusedInput";
string labelEncoderOutputName = $"mlnet.{column.Name}.unusedOutput";
string labelEncoderNodeName = $"mlnet.{column.Name}.SlotNames";

string[] oneVals = new string[] { "one" };
long[] dims = new long[] { 1, 1 };
var one = ctx.AddInitializer(oneVals, dims, labelEncoderNodeName);

var labelEncoderOutput = ctx.AddIntermediateVariable(NumberDataViewType.Int64, labelEncoderOutputName, true);
var node = ctx.CreateNode(opType, one, labelEncoderOutput, labelEncoderNodeName);
node.AddAttribute("keys_strings", slotNamesAsStrings);
node.AddAttribute("values_int64s", Enumerable.Range(0, slotNames.Length).Select(x => (long)x));
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@yaeldekel yaeldekel Feb 20, 2020 •
edited by harishsk
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values_int64s [](start = 31, length = 13)

Why do we need this? #Resolved

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These are unused. But are specified only to satisfy ORT.

In reply to: 381867237 [](ancestors = 381867237)


ctx.AddOutputVariable(NumberDataViewType.Int64, labelEncoderOutput);
}

private void Run(IChannel ch)
{
ILegacyDataLoader loader = null;
Expand Down
32 changes: 31 additions & 1 deletion src/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@
using Microsoft.ML.OnnxRuntime;
using Microsoft.ML.Runtime;
using Microsoft.ML.Transforms.Onnx;
using static Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper;
using OnnxShape = System.Collections.Generic.List<int>;

[assembly: LoadableClass(OnnxTransformer.Summary, typeof(IDataTransform), typeof(OnnxTransformer),
Expand Down Expand Up @@ -416,11 +417,40 @@ protected override DataViewSchema.DetachedColumn[] GetOutputColumnsCore()
{
var onnxOutputName = _parent.Outputs[i];
var columnName = onnxOutputName.EndsWith(stdSuffix) ? onnxOutputName.Replace(stdSuffix, "") : onnxOutputName;
info[i] = new DataViewSchema.DetachedColumn(columnName, _parent.OutputTypes[i], null);

var builder = new DataViewSchema.Annotations.Builder();
AddSlotNames(columnName, builder);

info[i] = new DataViewSchema.DetachedColumn(columnName, _parent.OutputTypes[i], builder.ToAnnotations());
}
return info;
}

private void AddSlotNames(string columnName, DataViewSchema.Annotations.Builder builder)
{
var graph = _parent.Model.Graph;
var nodes = graph.Node;

var slotNamesNodeName = $"mlnet.{columnName}.SlotNames";
var slotsNode = nodes.FirstOrDefault(node => node.Name == slotNamesNodeName);
var slotsAttr = slotsNode?.Attribute.FirstOrDefault(attr => attr.Name == "keys_strings");
if (slotsAttr == null)
return;

int count = slotsAttr.Strings.Count();
ValueGetter<VBuffer<ReadOnlyMemory<char>>> getter = (ref VBuffer<ReadOnlyMemory<char>> dst) =>
{
var dstEditor = VBufferEditor.Create(ref dst, count);
for (int i = 0; i < count; i++)
{
dstEditor.Values[i] = slotsAttr.Strings[i].ToString(Encoding.UTF8).AsMemory();
}
dst = dstEditor.Commit();
};

builder.AddSlotNames(count, getter);
}

private protected override Func<int, bool> GetDependenciesCore(Func<int, bool> activeOutput)
{
return col => Enumerable.Range(0, _parent.Outputs.Length).Any(i => activeOutput(i)) && _inputColIndices.Any(i => i == col);
Expand Down
9 changes: 9 additions & 0 deletions src/Microsoft.ML.OnnxTransformer/OnnxUtils.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@
using Microsoft.ML.OnnxRuntime;
using Microsoft.ML.OnnxRuntime.Tensors;
using Microsoft.ML.Runtime;
using static Microsoft.ML.Model.OnnxConverter.OnnxCSharpToProtoWrapper;
using OnnxShape = System.Collections.Generic.List<int>;

namespace Microsoft.ML.Transforms.Onnx
Expand Down Expand Up @@ -157,6 +158,8 @@ public OnnxVariableInfo(string name, OnnxShape shape, Type typeInOnnxRuntime, Da
/// </summary>
internal OnnxModelInfo ModelInfo { get; }

internal GraphProto Graph { get; }

/// <summary>
/// Constructs OnnxModel object from file.
/// </summary>
Expand Down Expand Up @@ -217,6 +220,8 @@ public OnnxModel(string modelFile, int? gpuDeviceId = null, bool fallbackToCpu =

// Create a view to the used ONNX model from ONNXRuntime's perspective.
ModelInfo = new OnnxModelInfo(inputInfos, outputInfos, overrideableInitializers);

Graph = model.Graph;
}

private List<OnnxVariableInfo> GetOnnxVariablesFromMetadata(IReadOnlyDictionary<string, NodeMetadata> nodeMetadata,
Expand All @@ -233,6 +238,10 @@ private List<OnnxVariableInfo> GetOnnxVariablesFromMetadata(IReadOnlyDictionary<
var dataViewType = typePool[name];
var caster = casterPool?[name];

if (name.StartsWith("mlnet.") &&
(name.EndsWith(".unusedInput") || name.EndsWith(".unusedOutput")))
continue;

OnnxVariableInfo info = null;
if (shapeDictionary != null && shapeDictionary.ContainsKey(name))
{
Expand Down
3 changes: 0 additions & 3 deletions src/Microsoft.ML.Transforms/Text/NgramTransform.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -770,9 +770,6 @@ public void SaveAsOnnx(OnnxContext ctx)

private void SaveAsOnnxCore(OnnxContext ctx, int iinfo, string srcVariableName, string dstVariableName)
{
VBuffer<ReadOnlyMemory<char>> slotNames = default;
GetSlotNames(iinfo, 0, ref slotNames);

var transformInfo = _parent._transformInfos[iinfo];

// TfIdfVectorizer accepts strings, int32 and int64 tensors.
Expand Down
154 changes: 152 additions & 2 deletions test/BaselineOutput/Common/Onnx/BinaryClassification/BreastCancer/OneHotBagPipeline.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -324,8 +324,8 @@
{
"name": "target_weights",
"floats": [
0.50476193,
-0.97911227
0.504761934,
-0.979112267
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@yaeldekel yaeldekel Feb 20, 2020 •
edited by harishsk
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How come these changed? #Resolved

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Not sure. But I see this occurring off and on that the baselines numbers change when we run them locally. I am ignoring them because the change is in the 7th decimal place

In reply to: 381858622 [](ancestors = 381858622)

],
"type": "FLOATS"
}
Expand Down Expand Up @@ -428,6 +428,51 @@
"name": "Identity1",
"opType": "Identity"
},
{
"input": [
"mlnet.F2.SlotNames"
],
"output": [
"mlnet.F2.unusedOutput"
],
"name": "mlnet.F2.SlotNames",
"opType": "LabelEncoder",
"attribute": [
{
"name": "keys_strings",
"strings": [
"NA==",
"MQ==",
"OA==",
"MTA=",
"Mg==",
"Mw==",
"Nw==",
"NQ==",
"Ng==",
"OQ=="
],
"type": "STRINGS"
},
{
"name": "values_int64s",
"ints": [
"0",
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8",
"9"
],
"type": "INTS"
}
],
"domain": "ai.onnx.ml"
},
{
"input": [
"Features"
Expand All @@ -438,6 +483,53 @@
"name": "Identity2",
"opType": "Identity"
},
{
"input": [
"mlnet.Features.SlotNames"
],
"output": [
"mlnet.Features.unusedOutput"
],
"name": "mlnet.Features.SlotNames",
"opType": "LabelEncoder",
"attribute": [
{
"name": "keys_strings",
"strings": [
"RjE=",
"RjIuNA==",
"RjIuMQ==",
"RjIuOA==",
"RjIuMTA=",
"RjIuMg==",
"RjIuMw==",
"RjIuNw==",
"RjIuNQ==",
"RjIuNg==",
"RjIuOQ=="
],
"type": "STRINGS"
},
{
"name": "values_int64s",
"ints": [
"0",
"1",
"2",
"3",
"4",
"5",
"6",
"7",
"8",
"9",
"10"
],
"type": "INTS"
}
],
"domain": "ai.onnx.ml"
},
{
"input": [
"PredictedLabel"
Expand Down Expand Up @@ -484,6 +576,28 @@
0
],
"name": "Offset"
},
{
"dims": [
"1",
"1"
],
"dataType": 8,
"stringData": [
"b25l"
],
"name": "mlnet.F2.SlotNames"
},
{
"dims": [
"1",
"1"
],
"dataType": 8,
"stringData": [
"b25l"
],
"name": "mlnet.Features.SlotNames"
}
],
"input": [
Expand Down Expand Up @@ -597,6 +711,24 @@
}
}
},
{
"name": "mlnet.F2.unusedOutput",
"type": {
"tensorType": {
"elemType": 7,
"shape": {
"dim": [
{
"dimValue": "-1"
},
{
"dimValue": "1"
}
]
}
}
}
},
{
"name": "Features.output",
"type": {
Expand All @@ -615,6 +747,24 @@
}
}
},
{
"name": "mlnet.Features.unusedOutput",
"type": {
"tensorType": {
"elemType": 7,
"shape": {
"dim": [
{
"dimValue": "-1"
},
{
"dimValue": "1"
}
]
}
}
}
},
{
"name": "PredictedLabel.output",
"type": {
Expand Down
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