1 override of CreateNode
Microsoft.ML.OnnxConverter (1)
OnnxContextImpl.cs (1)
155public override OnnxNode CreateNode(string opType, IEnumerable<string> inputs,
74 references to CreateNode
Microsoft.ML.Data (18)
Model\Onnx\OnnxContext.cs (2)
113/// Convenience alternative to <see cref="CreateNode(string, IEnumerable{string}, IEnumerable{string}, string, string)"/> 124=> CreateNode(opType, new[] { input }, new[] { output }, name, domain);
Model\Onnx\OnnxNode.cs (1)
12/// <see cref="OnnxContext.CreateNode(string, IEnumerable{string}, IEnumerable{string}, string, string)"/>.
Prediction\Calibrator.cs (7)
1308var node = ctx.CreateNode(opType, new[] { outputNames[0], minVar }, new[] { subNodeOutput }, ctx.GetNodeName(opType), ""); 1313node = ctx.CreateNode(opType, new[] { subNodeOutput, binSizeVar }, new[] { divNodeOutput }, ctx.GetNodeName(opType), ""); 1325node = ctx.CreateNode(opType, new[] { castOutput, zeroVar, numBinsMinusOneVar }, new[] { binIndexOutput }, ctx.GetNodeName(opType), ""); 1329node = ctx.CreateNode(opType, new[] { binProbabilitiesVar, binIndexOutput }, new[] { outputNames[1] }, ctx.GetNodeName(opType), ""); 1806var node = ctx.CreateNode(opType, new[] { scoreProbablityColumnNames[0], slopVar }, new[] { mulNodeOutput }, ctx.GetNodeName(opType), ""); 1811node = ctx.CreateNode(opType, new[] { mulNodeOutput, betaVar }, new[] { linearOutput }, ctx.GetNodeName(opType), ""); 1814node = ctx.CreateNode(opType, new[] { linearOutput },
Scorers\BinaryClassifierScorer.cs (1)
213ctx.CreateNode(opType, new[] { binarizerOutput, one }, new[] { addOutput }, ctx.GetNodeName(opType), "");
Transforms\ColumnConcatenatingTransformer.cs (1)
940var node = ctx.CreateNode(opType, inputList.Select(t => t.Key),
Transforms\Hashing.cs (5)
1385ctx.CreateNode(optType2, new[] { castOutput, zero }, new[] { isGreaterThanZeroOutputBool }, ctx.GetNodeName(optType2), ""); 1422var shiftNode = ctx.CreateNode(opType, new[] { murmurOutput, shiftValue }, new[] { bitShiftOutput }, ctx.GetNodeName(opType), ""); 1427shiftNode = ctx.CreateNode(opType, new[] { bitShiftOutput, shiftValue }, new[] { bitShiftOutput2 }, ctx.GetNodeName(opType), ""); 1440ctx.CreateNode(opType, new[] { castOutput, one }, new[] { addOutput }, ctx.GetNodeName(opType), ""); 1446ctx.CreateNode(opType, new[] { isGreaterThanZeroOutput, addOutput }, new[] { mulOutput }, ctx.GetNodeName(opType), "");
Transforms\SlotsDroppingTransformer.cs (1)
908var node = ctx.CreateNode(opType, new[] { srcVariableName, slotsVar }, new[] { dstVariableName }, ctx.GetNodeName(opType), "");
Microsoft.ML.FastTree (3)
FastTree.cs (1)
3108var node = ctx.CreateNode(opType, new[] { featureColumn }, new[] { scoreVarName }, ctx.GetNodeName(opType));
FastTreeTweedie.cs (1)
544ctx.CreateNode(opType, new[] { fastTreeOutput }, outputNames, ctx.GetNodeName(opType), "");
RandomForestRegression.cs (1)
228ctx.CreateNode(opType, new[] { fastTreeOutput, numTrees }, outputNames, ctx.GetNodeName(opType), "");
Microsoft.ML.KMeansClustering (3)
KMeansModelParameters.cs (3)
346var gemmNodeXC2 = ctx.CreateNode("Gemm", new[] { nameX, nameC, zeroName }, new[] { nameXC2 }, ctx.GetNodeName("Gemm"), ""); 352var addNodeZ = ctx.CreateNode("Add", new[] { nameX2, nameXC2 }, new[] { nameZ }, ctx.GetNodeName("Add"), ""); 356var addNodeY = ctx.CreateNode("Add", new[] { nameZ, nameC2 }, new[] { nameY }, ctx.GetNodeName("Add"), "");
Microsoft.ML.Mkl.Components (2)
VectorWhitening.cs (2)
664var node = ctx.CreateNode(opType, new[] { modelName, srcVariableName, zeroValueName }, new[] { gemmOutput }, ctx.GetNodeName(opType), ""); 668ctx.CreateNode(opType, new[] { gemmOutput }, new[] { dstVariableName }, ctx.GetNodeName(opType), "");
Microsoft.ML.PCA (1)
PcaTransformer.cs (1)
670var gemmNode = ctx.CreateNode(opType, new[] { transposeOutput, pcaMatrix, zeroMeanNode }, new[] { dstVariableName }, ctx.GetNodeName(opType), "");
Microsoft.ML.StandardTrainers (31)
Standard\LinearModelParameters.cs (2)
146var node = ctx.CreateNode(opType, new[] { featureColumn }, new[] { scoreVarName }, ctx.GetNodeName(opType)); 744ctx.CreateNode(opType, new[] { linearRegressorOutput }, outputs, ctx.GetNodeName(opType), "");
Standard\LogisticRegression\MulticlassLogisticRegression.cs (1)
991var node = ctx.CreateNode(opType, new[] { featureColumn }, new[] { classifierLabelOutput, outputs[1] }, ctx.GetNodeName(opType));
Standard\MulticlassClassification\MulticlassNaiveBayesTrainer.cs (16)
457ctx.CreateNode(opType, new[] { featureColumn, zero }, new[] { greaterOutput }, ctx.GetNodeName(opType), ""); 467ctx.CreateNode(opType, new[] { castOutput, oneInt }, new[] { isFeaturePresent }, ctx.GetNodeName(opType), "com.microsoft"); 472ctx.CreateNode(opType, new[] { labelHistogram, trainingCount }, new[] { divOutput }, ctx.GetNodeName(opType), ""); 481ctx.CreateNode(opType, new[] { featureHistogramName, one }, new[] { sumOutput }, ctx.GetNodeName(opType), ""); 493ctx.CreateNode(opType, new[] { labelHistogramTrans, featureHistogramName }, new[] { absentFeatureCount }, ctx.GetNodeName(opType), ""); 497ctx.CreateNode(opType, new[] { labelHistogramTrans, labelCount }, new[] { sumOutput }, ctx.GetNodeName(opType), ""); 505ctx.CreateNode(opType, new[] { absentFeatureCount, one }, new[] { sumOutput }, ctx.GetNodeName(opType), ""); 513ctx.CreateNode(opType, new[] { logOutput1, logOutput2 }, new[] { logProb }, ctx.GetNodeName(opType), ""); 517ctx.CreateNode(opType, new[] { logOutput3, logOutput2 }, new[] { absentFeatureLogProb }, ctx.GetNodeName(opType), ""); 521node = ctx.CreateNode(opType, new[] { logProb }, new[] { logProbReduceSum }, ctx.GetNodeName(opType), ""); 527node = ctx.CreateNode(opType, new[] { absentFeatureLogProb }, new[] { absentFeatureLogProbReduceSum }, ctx.GetNodeName(opType), ""); 538ctx.CreateNode(opType, new[] { castOutput, absentFeatureLogProbReduceSum }, new[] { subOutput }, ctx.GetNodeName(opType), ""); 542ctx.CreateNode(opType, new[] { subOutput, logProbReduceSum, logOutput }, new[] { sumOutput }, ctx.GetNodeName(opType), ""); 550node = ctx.CreateNode(opType, new[] { sumOutput }, new[] { scoreIndex }, ctx.GetNodeName(opType), ""); 563ctx.CreateNode(opType, new[] { castOutput, one }, new[] { sumOutput }, ctx.GetNodeName(opType), ""); 580ctx.CreateNode(opType, new[] { logOutput, isFeaturePresent }, new[] { output }, ctx.GetNodeName(opType), "");
Standard\MulticlassClassification\OneVersusAllTrainer.cs (9)
563var clipNode = ctx.CreateNode(opType, new[] { clipInput, zeroVar }, new[] { outputs[i] }, ctx.GetNodeName(opType), ""); 585var addNode = ctx.CreateNode(opType, new[] { argMaxOutput, one }, new[] { addOutput }, ctx.GetNodeName(opType), ""); 670var concatNode = ctx.CreateNode(opType, probabilityOutputs, new[] { concatOutput }, ctx.GetNodeName(opType), ""); 803ctx.CreateNode(opType, probabilityOutputs, new[] { sumOutput }, ctx.GetNodeName(opType), ""); 823ctx.CreateNode(opType, new[] { sumOutput, castIsZeroSumToFloat }, 831ctx.CreateNode(opType, new[] { probabilityOutputs[i], sumOutputNonZero }, new[] { divOutputs[i] }, ctx.GetNodeName(opType), ""); 837var concatNode = ctx.CreateNode(opType, divOutputs, new[] { concatOutput }, ctx.GetNodeName(opType), ""); 926var concatNode = ctx.CreateNode(opType, probabilityOutputs, new[] { concatOutput }, ctx.GetNodeName(opType), ""); 942var divNode = ctx.CreateNode(opType, new[] { expOutput, sumOutput }, new[] { divOutput }, ctx.GetNodeName(opType), "");
Standard\Simple\SimpleTrainers.cs (3)
418ctx.CreateNode(opType, new[] { labelColumn, labelColumn }, new[] { xorOutput }, ctx.GetNodeName(opType), ""); 431ctx.CreateNode(opType, new[] { castOutput, prob }, new[] { probVarName }, ctx.GetNodeName(opType), ""); 434ctx.CreateNode(opType, new[] { castOutput, score }, new[] { scoreVarName }, ctx.GetNodeName(opType), "");
Microsoft.ML.Transforms (16)
GcnTransform.cs (7)
657var subtractNode = ctx.CreateNode(opType, new[] { srcVariableName, meanOfInput }, new[] { inputMinusMean }, ctx.GetNodeName(opType), ""); 671var l1Node = ctx.CreateNode(opType, new[] { inputMinusMean, sumOfAbsOfInput }, new[] { dstVariableName }, ctx.GetNodeName(opType), ""); 678var squareNode = ctx.CreateNode(opType, new[] { inputMinusMean, two }, new[] { squareOfInput }, ctx.GetNodeName(opType), ""); 690var l2Node = ctx.CreateNode(opType, new[] { inputMinusMean, squareRoot }, new[] { dstVariableName }, ctx.GetNodeName(opType), ""); 700var lMaxNode = ctx.CreateNode(opType, new[] { inputMinusMean, maxOfInput }, new[] { dstVariableName }, ctx.GetNodeName(opType), ""); 708var squareOfInputMinusMeanNode = ctx.CreateNode(opType, new[] { inputMinusMean, two }, new[] { squareOfInputMinusMean }, ctx.GetNodeName(opType), ""); 721var lStdDevNode = ctx.CreateNode(opType, new[] { input, stdDev }, new[] { dstVariableName }, ctx.GetNodeName(opType), "");
Text\WordEmbeddingsExtractor.cs (8)
452var nodeA = ctx.CreateNode("Equal", new[] { nameY, nameF }, new[] { nameA }, ctx.GetNodeName("Equal"), ""); 477var nodePMin = ctx.CreateNode("Add", new[] { nameY, nameVMin }, new[] { namePMin }, ctx.GetNodeName("Add"), ""); 480var nodePMax = ctx.CreateNode("Add", new[] { nameY, nameVMax }, new[] { namePMax }, ctx.GetNodeName("Add"), ""); 484var nodeGMin = ctx.CreateNode("Gather", new[] { nameD, namePMin }, new[] { nameGMin }, ctx.GetNodeName("Gather"), ""); 487var nodeGMax = ctx.CreateNode("Gather", new[] { nameD, namePMax }, new[] { nameGMax }, ctx.GetNodeName("Gather"), ""); 502var nodeW = ctx.CreateNode("Gather", new[] { nameD, nameY }, new[] { nameW }, ctx.GetNodeName("Gather"), ""); 535var nodeE = ctx.CreateNode("Div", new[] { nameK, nameT }, new[] { nameE }, ctx.GetNodeName("Div"), ""); 539var nodeP = ctx.CreateNode("Concat", new[] { nameJ, nameE, nameL }, new[] { nameP }, ctx.GetNodeName("Concat"), "");
Text\WordTokenizing.cs (1)
421var reshapeNode = ctx.CreateNode(opType, new[] { intermediateVar, shape }, new[] { reshapeOutput }, ctx.GetNodeName(opType), "");