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Added IsotonicCalibrator ONNX Export Support #5298

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0d7217b
Work on IsotonicCalibrator ONNX Export Support
mstfbl Jul 10, 2020
a6aad6a
Merge remote-tracking branch 'upstream/master' into addIsotonicCalibr…
mstfbl Jul 13, 2020
1467b2f
Addressed comment and added unit test
mstfbl Jul 13, 2020
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188 changes: 187 additions & 1 deletion src/Microsoft.ML.Data/Prediction/Calibrator.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -1924,7 +1924,7 @@ public override ICalibrator CreateCalibrator(IChannel ch)
/// <item><description><see cref="Values"/>[n], if x &gt; <see cref="Maxes"/>[n]</description></item>
///</list>
/// </remarks>
public sealed class IsotonicCalibrator : ICalibrator, ICanSaveInBinaryFormat
public sealed class IsotonicCalibrator : ICalibrator, ICanSaveInBinaryFormat, ISingleCanSaveOnnx
{
internal const string LoaderSignature = "PAVCaliExec";
internal const string RegistrationName = "PAVCalibrator";
Expand Down Expand Up @@ -1958,6 +1958,11 @@ private static VersionInfo GetVersionInfo()
/// Values of PAV intervals.
/// </summary>
public readonly ImmutableArray<float> Values;
/// <summary>
/// Bool required by the interface ISingleCanSaveOnnx, returns true if
/// and only if calibrator can be exported in ONNX.
/// </summary>
bool ICanSaveOnnx.CanSaveOnnx(OnnxContext ctx) => true;

/// <summary>
/// Initializes a new instance of <see cref="IsotonicCalibrator"/>.
Expand Down Expand Up @@ -2115,6 +2120,187 @@ private float FindValue(float score)
float t = (score - Maxes[pos - 1]) / (Mins[pos] - Maxes[pos - 1]);
return Values[pos - 1] + t * (Values[pos] - Values[pos - 1]);
}

bool ISingleCanSaveOnnx.SaveAsOnnx(OnnxContext ctx, string[] outputNames, string featureColumn)
{
_host.CheckValue(ctx, nameof(ctx));
_host.CheckValue(outputNames, nameof(outputNames));
_host.Check(Utils.Size(outputNames) == 2);

const int minimumOpSetVersion = 9;
ctx.CheckOpSetVersion(minimumOpSetVersion, "IsotonicCalibrator");

var minsLengthVar = ctx.AddInitializer(Mins.Length, "MinsLength");
var minsLengthMinusOneVar = ctx.AddInitializer(Mins.Length - 1, "MinsLengthMinusOne");
var maxesLengthVar = ctx.AddInitializer(Maxes.Length, "MaxesLength");
var minToReturnVar = ctx.AddInitializer((float)1e-15, "MinToReturn");
var maxToReturnVar = ctx.AddInitializer((float)(1 - 1e-15), "MaxToReturn");
var minsVar = ctx.AddInitializer(Mins, new long[] { Mins.Length, 1 }, "Mins");
var maxesVar = ctx.AddInitializer(Maxes, new long[] { Maxes.Length, 1 }, "Maxes");
var valuesVar = ctx.AddInitializer(Values, new long[] { Values.Length, 1 }, "Values");
var minsZeroVar = ctx.AddInitializer(Mins[0], "MinsZero");
var maxesPMinusOneVar = ctx.AddInitializer(Maxes[Mins.Length - 1], "MaxesPMinusOne");
var zeroVar = ctx.AddInitializer(0, "Zero");
var oneVar = ctx.AddInitializer(1, "One");

//The isotonic regression optimization problem is defined by:
// min(sum(w_i, (y[i] - y_[j])^2))
// subject to y_[i] <= y_[j] whenever X[i] <= X[j] (non-decreasing)
// and min(y_) = y_min, max(y_) = y_max
// where:
// *y[i] are inputs(real numbers)
// *y_[i] are fitted
// *X specifies the order.If X is non-decreasing then y_ is non-decreasing.
// *w[i] are optional strictly positive weights(default to 1.0)

// Goal: Given output, calculate prob

// --- STEP 1: implement if-then-else logic for (p = Mins.Length): ------------------------------------
// If p == 0, Return 0
// If score < Mins[0], Return prob = Values[0]
// If score > Maxes[p-1], Return prob = Values[p-1]
// Else, continue

// Get Values[0]
string opType = "GatherElements";
var valuesZeroOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "valuesZeroOutput");
OnnxNode node = ctx.CreateNode(opType, new[] { valuesVar, zeroVar }, new[] { valuesZeroOutput }, ctx.GetNodeName(opType), "");

// Get Values[p-1] = Values[Mins.Length-1]
opType = "GatherElements";
var valuesPMinusOneOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "valuesPMinusOneOutput");
node = ctx.CreateNode(opType, new[] { valuesVar, minsLengthMinusOneVar }, new[] { valuesPMinusOneOutput }, ctx.GetNodeName(opType), "");

opType = "Equal";
var pEqualToZeroOutput = ctx.AddIntermediateVariable(BooleanDataViewType.Instance, "pEqualToZeroOutput");
node = ctx.CreateNode(opType, new[] { minsLengthVar, zeroVar }, new[] { pEqualToZeroOutput }, ctx.GetNodeName(opType), "");

opType = "Less";
var scoreLessThenMinsZeroOutput = ctx.AddIntermediateVariable(BooleanDataViewType.Instance, "scoreLessThenMinsZeroOutput");
node = ctx.CreateNode(opType, new[] { outputNames[0], minsZeroVar }, new[] { scoreLessThenMinsZeroOutput }, ctx.GetNodeName(opType), "");

opType = "Greater";
var scoreGreaterThenMaxesPMinusOneOutput = ctx.AddIntermediateVariable(BooleanDataViewType.Instance, "scoreGreaterThenMaxesPMinusOneOutput");
node = ctx.CreateNode(opType, new[] { outputNames[0], maxesPMinusOneVar }, new[] { scoreGreaterThenMaxesPMinusOneOutput }, ctx.GetNodeName(opType), "");

// Implement if statements
// To-do

// --- STEP 2: calculate pos, which is the index of the given score in the already-sorted Maxes ------------------------------------
// AKA: Find closest element to score in maxes

// scoreRepeatedAsVectorOutput, which has score repeated in all indices, length of vector is same as that of Maxes
// Calculate with mul_broadcast element-wise binary multiplication
// Note: score = outputNames[0]
var shapeOnesAsVector = new long[] { Maxes.Length };
var onesAsVector = new List<float>();
for(int i = 0; i < Maxes.Length; i++)
onesAsVector.Add(1.0f);
var onesAsVectorVar = ctx.AddInitializer(onesAsVector, shapeOnesAsVector, "OnesAsVector");

opType = "Mul";
var scoreRepeatedAsVectorOutput = ctx.AddIntermediateVariable(new VectorDataViewType(NumberDataViewType.Single, 1), "scoreRepeatedAsVectorOutput");
node = ctx.CreateNode(opType, new[] { onesAsVectorVar, outputNames[0] }, new[] { scoreRepeatedAsVectorOutput }, ctx.GetNodeName(opType), "");

// Subtract scoreRepeatedAsVectorOutput from Maxes
opType = "Sub";
var subVectorsOutput = ctx.AddIntermediateVariable(new VectorDataViewType(NumberDataViewType.Single, 1), "scoreAsVectorOutput");
node = ctx.CreateNode(opType, new[] { maxesVar, scoreRepeatedAsVectorOutput }, new[] { subVectorsOutput }, ctx.GetNodeName(opType), "");

// Square values in subVectorsOutput by multiplying it with itself
opType = "Mul";
var squaredVectorOutput = ctx.AddIntermediateVariable(new VectorDataViewType(NumberDataViewType.Single, 1), "squaredVectorOutput");
node = ctx.CreateNode(opType, new[] { subVectorsOutput, subVectorsOutput }, new[] { squaredVectorOutput }, ctx.GetNodeName(opType), "");

// Return index of given score, or if given score doesn't exist, return "logical index"
// of given score, which is the index of the first element greater than the given score.
opType = "ArgMin";
var posOutput = ctx.AddIntermediateVariable(NumberDataViewType.Int64, "posOutput");
node = ctx.CreateNode(opType, new[] { squaredVectorOutput }, new[] { posOutput }, ctx.GetNodeName(opType), "");

// --- STEP 3: if score >= Mins[pos], then prob = Values[pos] ------------------------------------

// Get Mins[pos]
opType = "GatherElements";
var minsPosOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "minsPosOutput");
node = ctx.CreateNode(opType, new[] { minsVar, posOutput }, new[] { minsPosOutput }, ctx.GetNodeName(opType), "");

// Get Values[pos]
opType = "GatherElements";
var valuesPosOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "valuesPosOutput");
node = ctx.CreateNode(opType, new[] { valuesVar, posOutput }, new[] { valuesPosOutput }, ctx.GetNodeName(opType), "");

opType = "GreaterOrEqual";
var scoreGreaterThanEqualToMinsPosOutput = ctx.AddIntermediateVariable(BooleanDataViewType.Instance, "scoreGreaterThanEqualToMinsPosOutput");
node = ctx.CreateNode(opType, new[] { outputNames[0], posOutput }, new[] { scoreGreaterThanEqualToMinsPosOutput }, ctx.GetNodeName(opType), "");

// Implement if statements
// To-do

// --- STEP 4: calculate (score - Maxes[pos - 1]) / (Mins[pos] - Maxes[pos - 1]) ------------------------------------
// score: outputNames[0]

opType = "Sub";
var posMinusOneOutput = ctx.AddIntermediateVariable(NumberDataViewType.Int64, "posMinusOneOutput");
node = ctx.CreateNode(opType, new[] { posOutput, oneVar }, new[] { posMinusOneOutput }, ctx.GetNodeName(opType), "");

opType = "GatherElements";
var maxesPosMinusOneOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "maxesPosMinusOneOutput");
node = ctx.CreateNode(opType, new[] { maxesVar, posMinusOneOutput }, new[] { maxesPosMinusOneOutput }, ctx.GetNodeName(opType), "");

opType = "Sub";
var subNode1Output = ctx.AddIntermediateVariable(NumberDataViewType.Single, "subNodeUpperOutput");
node = ctx.CreateNode(opType, new[] { outputNames[0], maxesPosMinusOneOutput }, new[] { subNode1Output }, ctx.GetNodeName(opType), "");

opType = "Sub";
var subNode2Output = ctx.AddIntermediateVariable(NumberDataViewType.Single, "subNodeLowerOutput");
node = ctx.CreateNode(opType, new[] { minsPosOutput, maxesPosMinusOneOutput }, new[] { subNode2Output }, ctx.GetNodeName(opType), "");

opType = "Div";
var tNodeOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "divNodeOutput");
node = ctx.CreateNode(opType, new[] { subNode1Output, subNode2Output }, new[] { tNodeOutput }, ctx.GetNodeName(opType), "");

// --- STEP 5: calculate and return prob = Values[pos - 1] + t * (Values[pos] - Values[pos - 1]); ------------------------------------

opType = "GatherElements";
var valuesPosMinusOneOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "valuesPosMinusOneOutput");
node = ctx.CreateNode(opType, new[] { valuesVar, posMinusOneOutput }, new[] { valuesPosMinusOneOutput }, ctx.GetNodeName(opType), "");

opType = "Sub";
var subNode3Output = ctx.AddIntermediateVariable(NumberDataViewType.Single, "subNode3Output");
node = ctx.CreateNode(opType, new[] { valuesPosOutput, valuesPosMinusOneOutput }, new[] { subNode3Output }, ctx.GetNodeName(opType), "");

opType = "Mul";
var mulNodeOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "mulNodeOutput");
node = ctx.CreateNode(opType, new[] { tNodeOutput, subNode3Output }, new[] { mulNodeOutput }, ctx.GetNodeName(opType), "");

opType = "Add";
var probabilityNodeOutput = ctx.AddIntermediateVariable(NumberDataViewType.Single, "probabilityNodeOutput");
node = ctx.CreateNode(opType, new[] { valuesPosMinusOneOutput, mulNodeOutput }, new[] { probabilityNodeOutput }, ctx.GetNodeName(opType), "");

// --- STEP 6: continue with logic ------------------------------------
// if (prob < MinToReturn)
// return MinToReturn;
// if (prob > MaxToReturn)
// return MaxToReturn;
// return prob

opType = "Less";
var probLessThanMinToReturnOutput = ctx.AddIntermediateVariable(BooleanDataViewType.Instance, "probLessThanMinToReturnOutput");
node = ctx.CreateNode(opType, new[] { probabilityNodeOutput, minToReturnVar }, new[] { probLessThanMinToReturnOutput }, ctx.GetNodeName(opType), "");

opType = "Greater";
var probGreaterThanMaxToReturnOutput = ctx.AddIntermediateVariable(BooleanDataViewType.Instance, "probGreaterThanMaxToReturnOutput");
node = ctx.CreateNode(opType, new[] { probabilityNodeOutput, maxToReturnVar }, new[] { probGreaterThanMaxToReturnOutput }, ctx.GetNodeName(opType), "");

// Implement if statements
// To-do

opType = "Identity";
node = ctx.CreateNode(opType, new[] { probabilityNodeOutput }, new[] { outputNames[1] }, ctx.GetNodeName(opType), "");

return true;
}
}

internal static class Calibrate
Expand Down
7 changes: 7 additions & 0 deletions test/Microsoft.ML.Tests/OnnxConversionTest.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -338,6 +338,13 @@ public void NaiveCalibratorOnnxConversionTest()
ML.BinaryClassification.Calibrators.Naive(scoreColumnName: "ScoreX"));
}

[Fact]
public void IsotonicCalibratorOnnxConversionTest()
{
CommonCalibratorOnnxConversionTest(ML.BinaryClassification.Calibrators.Isotonic(),
ML.BinaryClassification.Calibrators.Naive(scoreColumnName: "ScoreX"));
}

class CalibratorInput
{
public bool Label { get; set; }
Expand Down