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Ivan Matantsev
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Merge branch 'master' into ivanidze/wordembedding
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‎.vsts-dotnet-ci.yml

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resources:
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containers:
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- container: centos7
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image: microsoft/dotnet-buildtools-prereqs:centos-7-b46d863-20180719033416
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phases:
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- template: /build/ci/phase-template.yml
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parameters:
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name: Linux
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buildScript: ./build.sh
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queue:
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container: centos7
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- template: /build/ci/phase-template.yml
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parameters:
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name: Windows_NT
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buildScript: build.cmd
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queue:
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name: Hosted VS2017
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demands:
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- agent.os -equals Windows_NT

‎README.md

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@@ -44,9 +44,9 @@ To build ML.NET from source please visit our [developers guide](docs/project-doc
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| | x64 Debug | x64 Release |
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|:---|----------------:|------------------:|
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|**Linux**|[![x64-debug](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/linux_debug/badge/icon)](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/linux_debug/lastCompletedBuild)|[![x64-release](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/linux_release/badge/icon)](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/linux_release/lastCompletedBuild)|
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|**Linux**|[![x64-debug](https://dotnet.visualstudio.com/public/_apis/build/status/104?branch=master)](https://dotnet.visualstudio.com/DotNet-Public/_build/latest?definitionId=104&branch=master)|[![x64-release](https://dotnet.visualstudio.com/public/_apis/build/status/104?branch=master)](https://dotnet.visualstudio.com/DotNet-Public/_build/latest?definitionId=104&branch=master)|
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|**macOS**|[![x64-debug](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/osx10.13_debug/badge/icon)](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/osx10.13_debug/lastCompletedBuild)|[![x64-release](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/osx10.13_release/badge/icon)](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/osx10.13_release/lastCompletedBuild)|
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|**Windows**|[![x64-debug](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/windows_nt_debug/badge/icon)](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/windows_nt_debug/lastCompletedBuild)|[![x64-release](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/windows_nt_release/badge/icon)](https://ci2.dot.net/job/dotnet_machinelearning/job/master/job/windows_nt_release/lastCompletedBuild)|
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|**Windows**|[![x64-debug](https://dotnet.visualstudio.com/public/_apis/build/status/104?branch=master)](https://dotnet.visualstudio.com/DotNet-Public/_build/latest?definitionId=104&branch=master)|[![x64-release](https://dotnet.visualstudio.com/public/_apis/build/status/104?branch=master)](https://dotnet.visualstudio.com/DotNet-Public/_build/latest?definitionId=104&branch=master)|
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## Contributing
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‎build/ci/phase-template.yml

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parameters:
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name: ''
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buildScript: ''
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queue: {}
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phases:
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- phase: ${{ parameters.name }}
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variables:
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_buildScript: ${{ parameters.buildScript }}
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_phaseName: ${{ parameters.name }}
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queue:
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parallel: 2
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matrix:
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Build_Debug:
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_configuration: Debug
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Build_Release:
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_configuration: Release
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${{ insert }}: ${{ parameters.queue }}
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steps:
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- script: $(_buildScript) -$(_configuration) -runtests
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displayName: Build and Test
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- task: PublishTestResults@2
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displayName: Publish Test Results
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condition: succeededOrFailed()
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inputs:
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testRunner: 'vSTest'
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searchFolder: '$(System.DefaultWorkingDirectory)/bin'
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testResultsFiles: '**/*.trx'
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testRunTitle: Machinelearning_Tests_$(_phaseName)_$(_configuration)_$(Build.BuildNumber)
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configuration: $(_configuration)
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mergeTestResults: true
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- script: $(_buildScript) -buildPackages
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displayName: Build Packages

‎netci.groovy

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@@ -6,46 +6,22 @@ import jobs.generation.Utilities;
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def project = GithubProject
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def branch = GithubBranchName
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9-
['Windows_NT', 'Linux', 'OSX10.13'].each { os ->
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['OSX10.13'].each { os ->
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['Debug', 'Release'].each { config ->
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[true, false].each { isPR ->
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// Calculate job name
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def jobName = os.toLowerCase() + '_' + config.toLowerCase()
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def buildFile = '';
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def machineAffinity = 'latest-or-auto'
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// Calculate the build command
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if (os == 'Windows_NT') {
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buildFile = ".\\build.cmd"
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} else {
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buildFile = "./build.sh"
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}
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def buildCommand = buildFile + " -$config -runtests"
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def packCommand = buildFile + " -buildPackages"
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def newJob = job(Utilities.getFullJobName(project, jobName, isPR)) {
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steps {
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if (os == 'Windows_NT') {
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batchFile(buildCommand)
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batchFile(packCommand)
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}
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else {
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// Shell
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shell(buildCommand)
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shell(packCommand)
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}
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shell("./build.sh -$config -runtests")
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shell("./build.sh -buildPackages")
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}
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}
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42-
def osImageName = os
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if (os == 'Linux') {
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// Trigger a portable Linux build that runs on RHEL7.2
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osImageName = "RHEL7.2"
46-
}
47-
48-
Utilities.setMachineAffinity(newJob, osImageName, machineAffinity)
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Utilities.setMachineAffinity(newJob, os, machineAffinity)
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Utilities.standardJobSetup(newJob, project, isPR, "*/${branch}")
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if (isPR) {

‎src/Microsoft.ML.Data/Prediction/Calibrator.cs

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@@ -1437,13 +1437,13 @@ public bool SaveAsOnnx(OnnxContext ctx, string[] scoreProbablityColumnNames, str
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string opType = "Affine";
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string linearOutput = ctx.AddIntermediateVariable(null, "linearOutput", true);
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var node = ctx.CreateNode(opType, new[] { scoreProbablityColumnNames[0] },
1440-
new[] { linearOutput }, ctx.GetNodeName(opType), "ai.onnx");
1440+
new[] { linearOutput }, ctx.GetNodeName(opType), "");
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node.AddAttribute("alpha", ParamA * -1);
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node.AddAttribute("beta", -0.0000001);
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opType = "Sigmoid";
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node = ctx.CreateNode(opType, new[] { linearOutput },
1446-
new[] { scoreProbablityColumnNames[1] }, ctx.GetNodeName(opType), "ai.onnx");
1446+
new[] { scoreProbablityColumnNames[1] }, ctx.GetNodeName(opType), "");
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return true;
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}

‎src/Microsoft.ML.Data/Transforms/ConcatTransform.cs

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var node = ctx.CreateNode(opType, inputList.Select(t => t.Key),
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new[] { ctx.AddIntermediateVariable(outColType, outName) }, ctx.GetNodeName(opType));
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726-
node.AddAttribute("inputList", inputList.Select(x => x.Key));
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node.AddAttribute("inputdimensions", inputList.Select(x => x.Value));
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}
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}

‎src/Microsoft.ML.Data/Transforms/TermTransform.cs

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@@ -719,7 +719,10 @@ protected override bool SaveAsOnnxCore(OnnxContext ctx, int iinfo, ColInfo info,
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var node = ctx.CreateNode(opType, srcVariableName, dstVariableName, ctx.GetNodeName(opType));
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node.AddAttribute("classes_strings", terms.DenseValues());
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node.AddAttribute("default_int64", -1);
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node.AddAttribute("default_string", DvText.Empty);
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//default_string needs to be an empty string but there is a BUG in Lotus that
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//throws a validation error when default_string is empty. As a work around, set
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//default_string to a space.
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node.AddAttribute("default_string", " ");
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return true;
724727
}
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‎src/Microsoft.ML.Onnx/OnnxUtils.cs

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model.Domain = domain;
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model.ProducerName = producerName;
254254
model.ProducerVersion = producerVersion;
255-
model.IrVersion = (long)UniversalModelFormat.Onnx.Version.IrVersion;
255+
model.IrVersion = (long)Version.IrVersion;
256256
model.ModelVersion = modelVersion;
257257
model.OpsetImport.Add(new OperatorSetIdProto() { Domain = "ai.onnx.ml", Version = 1 });
258-
model.OpsetImport.Add(new OperatorSetIdProto() { Domain = "ai.onnx", Version = 6 });
258+
model.OpsetImport.Add(new OperatorSetIdProto() { Domain = "", Version = 7 });
259259
model.Graph = new GraphProto();
260260
var graph = model.Graph;
261261
graph.Node.Add(nodes);

‎src/Microsoft.ML.StandardLearners/Standard/LinearPredictor.cs

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string opType = "LinearRegressor";
239239
var node = ctx.CreateNode(opType, new[] { featureColumn }, outputs, ctx.GetNodeName(opType));
240240
// Selection of logit or probit output transform. enum {'NONE', 'LOGIT', 'PROBIT}
241-
node.AddAttribute("post_transform", 0);
241+
node.AddAttribute("post_transform", "NONE");
242242
node.AddAttribute("targets", 1);
243243
node.AddAttribute("coefficients", Weight.DenseValues());
244-
node.AddAttribute("intercepts", Bias);
244+
node.AddAttribute("intercepts", new float[] { Bias });
245245
return true;
246246
}
247247

‎src/Microsoft.ML.StandardLearners/Standard/LogisticRegression/MulticlassLogisticRegression.cs

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846846
string opType = "LinearClassifier";
847847
var node = ctx.CreateNode(opType, new[] { featureColumn }, outputs, ctx.GetNodeName(opType));
848-
// Selection of logit or probit output transform. enum {'NONE', 'LOGIT', 'PROBIT}
849-
node.AddAttribute("post_transform", 0);
848+
// Selection of logit or probit output transform. enum {'NONE', 'SOFTMAX', 'LOGISTIC', 'SOFTMAX_ZERO', 'PROBIT}
849+
node.AddAttribute("post_transform", "NONE");
850850
node.AddAttribute("multi_class", true);
851851
node.AddAttribute("coefficients", _weights.SelectMany(w => w.DenseValues()));
852852
node.AddAttribute("intercepts", _biases);
853-
node.AddAttribute("classlabels_strings", _labelNames);
853+
node.AddAttribute("classlabels_ints", Enumerable.Range(0, _numClasses).Select(x => (long)x));
854854
return true;
855855
}
856856

‎src/Microsoft.ML.Transforms/NAReplaceTransform.cs

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632632
node.AddAttribute("replaced_value_float", Single.NaN);
633633

634634
if (!Infos[iinfo].TypeSrc.IsVector)
635-
node.AddAttribute("imputed_value_float", Enumerable.Repeat((float)_repValues[iinfo], 1));
635+
node.AddAttribute("imputed_value_floats", Enumerable.Repeat((float)_repValues[iinfo], 1));
636636
else
637637
{
638638
if (_repIsDefault[iinfo] != null)
639639
node.AddAttribute("imputed_value_floats", (float[])_repValues[iinfo]);
640640
else
641-
node.AddAttribute("imputed_value_float", Enumerable.Repeat((float)_repValues[iinfo], 1));
641+
node.AddAttribute("imputed_value_floats", Enumerable.Repeat((float)_repValues[iinfo], 1));
642642
}
643643

644644
return true;

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