Fix Unix path handling in result-processor tests

test/BaselineOutput/Common/AveragedPerceptron/osx-arm64/AveragedPerceptron-TrainTest-breast-cancer.PAVcalibration-rp.txt

@@ -0,0 +1,4 @@
+AveragedPerceptron
+AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.996146	0.97511	0.95122	0.979079	0.988558	0.972973	0.084507	0.909522	0.964948	0.992065	AveragedPerceptron	%Data%	%Data%	%Output%	99	0	0	maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali=PAV dout=%Output% data=%Data% out=%Output% seed=1		
+

test/BaselineOutput/Common/AveragedPerceptron/osx-arm64/AveragedPerceptron-TrainTest-breast-cancer.calibrateRandom-rp.txt

@@ -0,0 +1,4 @@
+AveragedPerceptron
+AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.996146	0.97511	0.95122	0.979079	0.988558	0.972973	0.120617	0.87086	0.964948	0.992065	AveragedPerceptron	%Data%	%Data%	%Output%	99	0	0	maml.exe TrainTest test=%Data% tr=AveragedPerceptron numcali=200 dout=%Output% data=%Data% out=%Output% seed=1		
+

test/BaselineOutput/Common/AveragedPerceptron/osx-arm64/AveragedPerceptron-TrainTest-breast-cancer.nocalibration-rp.txt

@@ -0,0 +1,4 @@
+AveragedPerceptron
+AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.996146	0.97511	0.95122	0.979079	0.988558	0.972973	NaN	0	0.964948	0.992065	AveragedPerceptron	%Data%	%Data%	%Output%	99	0	0	maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali={} dout=%Output% data=%Data% out=%Output% seed=1		
+

test/BaselineOutput/Common/LdSvm/osx-arm64/LDSVM-def-CV-breast-cancer-rp.txt

@@ -0,0 +1,4 @@
+LdSvm
+AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	/iter	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.973077	0.963079	0.94487	0.947619	0.97619	0.968344	0.204103	0.777959	0.945069	0.974864	1000	LdSvm	%Data%		%Output%	99	0	0	maml.exe CV tr=LdSvm{iter=1000} threads=- dout=%Output% data=%Data% seed=1	/iter:1000	
+

test/BaselineOutput/Common/LdSvm/osx-arm64/LDSVM-nob-CV-breast-cancer-rp.txt

@@ -0,0 +1,4 @@
+LdSvm
+AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	/bias	/iter	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.982598	0.914001	0.827025	0.960625	0.976218	0.89237	0.24697	0.734766	0.885366	0.972638	-	1000	LdSvm	%Data%		%Output%	99	0	0	maml.exe CV tr=LdSvm{iter=1000 bias=-} threads=- dout=%Output% data=%Data% seed=1	/bias:-;/iter:1000	
+

test/BaselineOutput/Common/LdSvm/osx-arm64/LDSVM-nob-TrainTest-breast-cancer-rp.txt

@@ -0,0 +1,4 @@
+LdSvm
+AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	/bias	/iter	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.969024	0.951684	0.955752	0.903766	0.949672	0.977477	0.25164	0.730579	0.929032	0.965033	-	1000	LdSvm	%Data%	%Data%	%Output%	99	0	0	maml.exe TrainTest test=%Data% tr=LdSvm{iter=1000 bias=-} dout=%Output% data=%Data% out=%Output% seed=1	/bias:-;/iter:1000	
+

test/BaselineOutput/Common/WeightedEnsemble/osx-arm64/WE-AvgPer-TrainTest-breast-cancer-rp.txt

@@ -0,0 +1,4 @@
+WeightedEnsemble
+AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	/bp	/nm	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.99624	0.973646	0.958506	0.966527	0.9819	0.977477	0.112168	0.879907	0.9625	0.9924	AvgPer	3	WeightedEnsemble	%Data%	%Data%	%Output%	99	0	0	maml.exe TrainTest test=%Data% tr=WeightedEnsemble{bp=AvgPer nm=3 tp=-} dout=%Output% loader=Text{col=Label:BL:0 col=Features:R4:1-9} data=%Data% out=%Output% seed=1	/bp:AvgPer;/nm:3	
+

test/BaselineOutput/Common/WeightedEnsemble/osx-arm64/WE-Hetero-TrainTest-breast-cancer-rp.txt

@@ -0,0 +1,4 @@
+WeightedEnsemble
+AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	/bp	/nm	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.996249	0.97511	0.9625	0.966527	0.981941	0.97973	0.112863	0.879162	0.964509	0.992435	svm,ap	20	WeightedEnsemble	%Data%	%Data%	%Output%	99	0	0	maml.exe TrainTest test=%Data% tr=WeightedEnsemble{bp=svm bp=ap nm=20 tp=-} dout=%Output% loader=Text{col=Label:BL:0 col=Features:R4:1-9} data=%Data% out=%Output% seed=1	/bp:svm,ap;/nm:20	
+

test/BaselineOutput/Common/WeightedEnsembleMulticlass/osx-arm64/WE-Average-TrainTest-iris-rp.txt

@@ -0,0 +1,4 @@
+WeightedEnsembleMulticlass
+Accuracy(micro-avg)	Accuracy(macro-avg)	Log-loss	Log-loss reduction	/oc	/bp	/nm	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.946667	0.946667	0.433342	0.605555	MultiAverage	mlr{t-}	5	WeightedEnsembleMulticlass	%Data%	%Data%	%Output%	99	0	0	maml.exe TrainTest test=%Data% tr=WeightedEnsembleMulticlass{bp=mlr{t-} nm=5 oc=MultiAverage tp=-} dout=%Output% data=%Data% out=%Output% seed=1 xf=Term{col=Label}	/oc:MultiAverage;/bp:mlr{t-};/nm:5	
+

test/BaselineOutput/Common/WeightedEnsembleMulticlass/osx-arm64/WE-Bootstrap-TrainTest-iris-rp.txt

@@ -0,0 +1,4 @@
+WeightedEnsembleMulticlass
+Accuracy(micro-avg)	Accuracy(macro-avg)	Log-loss	Log-loss reduction	/bp	/nm	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
+0.94	0.94	0.435527	0.603567	mlr{t-}	20	WeightedEnsembleMulticlass	%Data%	%Data%	%Output%	99	0	0	maml.exe TrainTest test=%Data% tr=WeightedEnsembleMulticlass{bp=mlr{t-} nm=20 st=BootstrapSelector{} tp=-} dout=%Output% data=%Data% out=%Output% seed=1 xf=Term{col=Label}	/bp:mlr{t-};/nm:20	
+

test/Microsoft.ML.Predictor.Tests/ResultProcessor/TestResultProcessor.cs

@@ -4,6 +4,7 @@
 
 using System.Collections.Generic;
 using System.IO;
+using System.Linq;
 using System.Reflection;
 using Xunit;
 using Xunit.Abstractions;
@@ -22,6 +23,37 @@ public TestResultProcessor(ITestOutputHelper helper) : base(helper)
         {
         }
 
+        [Theory]
+        [InlineData("absolute")]
+        [InlineData("with spaces")]
+        [InlineData("with {braces}")]
+        [InlineData("with {unmatched brace")]
+        public void ResultProcessorWithAbsolutePaths(string directory)
+        {
+            string outputDirectory = Path.Combine(SubDirectory, directory);
+            string[] commands = { "TrainTest", "CV" };
+            string[] inputPaths = new string[commands.Length];
+            for (int i = 0; i < commands.Length; i++)
+            {
+                string name = $"LogisticRegression-norm-{commands[i]}-breast-cancer-out.txt";
+                inputPaths[i] = DeleteOutputPath(outputDirectory, name);
+                File.Copy(GetBaselinePath("LogisticRegression", name), inputPaths[i]);
+            }
+
+            string outputPath = DeleteOutputPath(outputDirectory, "results-rp.txt");
+            RunResultProcessorTest(inputPaths, outputPath, null);
+
+            Assert.True(File.Exists(outputPath));
+            string[] lines = File.ReadAllLines(outputPath).Where(line => !string.IsNullOrWhiteSpace(line)).ToArray();
+            Assert.Equal(4, lines.Length);
+            Assert.Equal("LogisticRegression", lines[0]);
+            Assert.Contains("Accuracy", lines[1]);
+            for (int i = 0; i < inputPaths.Length; i++)
+                Assert.Contains(inputPaths[i], lines[i + 2]);
+
+            Done();
+        }
+
         // Worker method for running the tests
         private void RunTestCore(string name, string fileName, string[] testDataNames, string[] extraArgs = null)
         {

test/Microsoft.ML.TestFramework/BaseTestPredictorsMaml.cs

@@ -5,7 +5,8 @@
 using System.Collections.Generic;
 using System.IO;
 using System.Linq;
-using System.Runtime.InteropServices;
+using System.Text;
+using Microsoft.ML.CommandLine;
 using Microsoft.ML.Runtime;
 using Microsoft.ML.TestFrameworkCommon;
 
@@ -199,19 +200,16 @@ protected void Run(RunContext ctx, int digitsOfPrecision = DigitsOfPrecision, Nu
                 return;
 
             // ResultProcessor output
-            if (RuntimeInformation.IsOSPlatform(OSPlatform.Windows)) // -rp.txt files are not getting generated for Non-Windows Os
-            {
-                string rpName = basePrefix + "-rp.txt";
-                string rpOutPath = DeleteOutputPath(dir, rpName);
+            string rpName = basePrefix + "-rp.txt";
+            string rpOutPath = DeleteOutputPath(dir, rpName);
 
-                string[] rpArgs = null;
-                if (ctx.Command == Cmd.CV && ctx.ExtraArgs != null && ctx.ExtraArgs.Any(arg => arg.Contains("opf+")))
-                    rpArgs = new string[] { "opf+" };
+            string[] rpArgs = null;
+            if (ctx.Command == Cmd.CV && ctx.ExtraArgs != null && ctx.ExtraArgs.Any(arg => arg.Contains("opf+")))
+                rpArgs = new string[] { "opf+" };
 
-                // Run result processor on the console output.
-                RunResultProcessorTest(new string[] { consOutPath.Path }, rpOutPath, rpArgs);
-                CheckEqualityNormalized(dir, rpName, digitsOfPrecision: digitsOfPrecision, parseOption: parseOption);
-            }
+            // Run result processor on the console output.
+            RunResultProcessorTest(new string[] { consOutPath.Path }, rpOutPath, rpArgs);
+            CheckEqualityNormalized(dir, rpName, digitsOfPrecision: digitsOfPrecision, parseOption: parseOption);
 
             // Check the prediction output against its baseline.
             Contracts.Assert(predOutPath != null);
@@ -288,17 +286,22 @@ protected void RunResultProcessorTest(string[] dataFiles, string outPath, string
             File.Delete(outPath);
 
             List<string> args = new List<string>();
+            StringBuilder arg = new StringBuilder();
             for (int i = 0; i < dataFiles.Length; i++)
             {
-                args.Add("\"" + dataFiles[i] + "\"");
+                arg.Clear().Append("in=");
+                CmdQuoter.QuoteValue(dataFiles[i], arg);
+                args.Add(arg.ToString());
             }
-            args.Add("/o");
-            args.Add(outPath);
+            arg.Clear().Append("o=");
+            CmdQuoter.QuoteValue(outPath, arg);
+            args.Add(arg.ToString());
             args.Add("/calledFromUnitTestSuite+");
 
             if (extraArgs != null)
                 args.AddRange(extraArgs);
-            ResultProcessor.Main(Env, args.ToArray());
+            int result = ResultProcessor.Main(Env, args.ToArray());
+            Check(result == 0, "Result processor failed with exit code {0}.", result);
         }
 
         private static string GetNamePrefix(string testType, PredictorAndArgs predictor, TestDataset dataset, string extraTag = "")