Added Benchmark performance tests for wikidetoxData #820

Anipik · 2018-09-05T00:31:12Z

This PR adds BenchMark tests for AveragePreceptron and LightGBM classifier on wikiDetox Dataset.

Anipik · 2018-09-05T03:22:43Z

@dotnet-bot test MachineLearning-CI

eerhardt · 2018-09-05T15:19:19Z

test/Microsoft.ML.Benchmarks/Program.cs

@@ -29,7 +29,7 @@ static void Main(string[] args)

        private static IConfig CreateCustomConfig() 
            => DefaultConfig.Instance
-                .With(Job.Default
+                .With(Job.VeryLongRun


Do we really want to change this? /cc @adamsitnik

+1

In reply to: 215314542 [](ancestors = 215314542)

I think that we should not change it.

What the current setting is : 1 warmup iteration, up to 20 workload iterations in 1 process
What LongRun is : up to 30 warmup iterations, up to 500 workload iterations repeated in 4 dedicated processes

What's the effect of having warm-up iterations?

Are we running in the same process, or another? The normal user has a single run, so I think only the first warm-up iteration is representative. For instance, the WordEmbedding transform only spends time loading the model the first time; this time is significant (seconds to minutes). I'm not sure if the static loading of the word embedding models will be torn-down in the current tests.

Static dictionary which keeps the word embedding models:

machinelearning/src/Microsoft.ML.Transforms/Text/WordEmbeddingsTransform.cs

Line 84 in b727d10

private static Dictionary<string, WeakReference<Model>> _vocab = new Dictionary<string, WeakReference<Model>>();

If we run benchmarks in concurrency, we'll hit the loader lock, which will cause only one model to load per process in parallel:

machinelearning/src/Microsoft.ML.Transforms/Text/WordEmbeddingsTransform.cs

Line 80 in b727d10

private static object _embeddingsLock = new object();

Can we check, for the WordEmbedding transforms benchmark, if the model is reloaded from disk for iteration (it should be)?

we should be able to verify from the time of warmup iterations. There shouldn't be large difference between both the cases

@justinormont every benchmark is executed in a dedicated process. We have 1 warmup iteration to exclude the cost of Jitting from the final result.

However, if in the real life scenarios this code is executed only once it makes sense to have a custom config for it, which is going to spawn new process n times and every process is going to run the benchmark exactly once. This is possible with BenchmarkDotNet.

@justinormont could you say something more about typical scenarios? (how many times train and predict are executed)

@davidwrighton this could be also interesting from the Runtime perspective, especially with tiered jitting enabled (cc @kouvel)

There isn't just one type of user. What's being tested here is a batch scoring scenario where the user has a pre-trained model and they want to score a dataset against the model. This benchmark is meant to cover the speed of this scoring process (it doesn't return a useful accuracy metric as there is data leakage from running in a Train-Train (mostly same dataset used for both training and the final eval). The user in this benchmark likely is expected to have a cold-start.

Todo: see if the subsequent iterations also load the Word Embedding file (or we won't be including its load-time in the benchmark).

Future pull requests: We should expand the user scenarios tested. And increase the datasets so we don't overfit our perf improvements to only the few represented datasets.

eerhardt · 2018-09-05T15:20:10Z

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

+            Maml.MainAll(cmd);
+        }
+
+        [GlobalSetup]


(nit) typically "setup" methods are towards the top of the class file. It makes for easier reading to see the stuff that will run first at the top.

eerhardt · 2018-09-05T15:21:27Z

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

+            string outDir = Path.Combine(currentAssemblyLocation.Directory.FullName, "TestOutput");
+
+            s_output_Wiki = Path.Combine(outDir, @"BenchmarkDefForMLNET\WikiDetox\00-baseline,_Bigram+Trichar\");
+            Directory.CreateDirectory(s_output_Wiki);


Do we really need to save an output model? Is it required? What are we going to do with it?

Oh, I see we use it in WikiDox_Test. It seems like that test is dependent on Preceptron_CV running first. I'm not sure that is a good idea - to have one benchmark depend on another benchmark.

In reply to: 215315428 [](ancestors = 215315428)

@eerhardt is right, benchmark should not rely on the side effects of any other benchmarks. What if the user provides a filter to run only one of them?

@Anipik you can use Target property of the [GlobalSetup] an example:

[GlobalSetup(Targets = new string[] { nameof(Preceptron_CV), nameof(LightGBM_CV) }] public void Setup_Preceptron_LightGBM() { } [GlobalSetup(Target = nameof(WikiDox_Test))] public void Setup_WikiDox() { Setup_Preceptron_LightGBM(); Preceptron_CV(); }

It seems like that test is dependent on Preceptron_CV running first.

We can put one of the trained model on azure and pull that for this benchmark ?

We can provide a trained model, but this assumes the model will be static. It's likely that the model itself will change in time. For instance, the default tokenizer should be changed, or we may change the workings of the TextTransform.

What we could do is create the model once (not repeatedly) before the test runs for the first time. Then we use it.

What we could do is create the model once (not repeatedly) before the test runs for the first time. Then we use it.

we can do that in the global setup for that test

sfilipi · 2018-09-05T15:30:37Z

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

+        [GlobalSetup]
+        public void Setup()
+        {
+            s_dataPath_Wiki = Program.GetInvariantCultureDataPath("wikiDetoxAnnotated160kRows.tsv");


wikiDetoxAnnotated160kRows.tsv [](start = 67, length = 30)

There is a way to define datasets in the tests: look at machinelearning/test/Microsoft.ML.TestFramework/Datasets.cs.

Might make sense to add this one to the list.

sfilipi · 2018-09-05T15:31:24Z

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

+        {
+            string modelPath = Path.Combine(s_output_Wiki, @"0.model.fold000.zip");
+            string cmd = @"Test data=" + s_dataPath_Wiki + " in=" + modelPath;
+            Maml.MainAll(cmd);


Maml.MainAll(cmd); [](start = 12, length = 18)

don't know much about benchmark tests: do we need to track the time the run starts-ends or the framework does it for us? #Resolved

[Benchmark] attribute automatically does that for you. At the end of the run it gives you all the statistics like mean, median, memory used

adamsitnik · 2018-09-05T15:40:00Z

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

+        }
+
+        [Benchmark]
+        public void WikiDox_Test()


nit: remove "_Test" from the benchmark name. The names should be short and meaningful.

actually test here refers to the "Test" and "CV" commads given to Maml.MainAll api

@Anipik I am sorry, I did not know. Very often people call benchmarks "Test" and later on it's hard to identify them.

Np :). i will try to rename it more properly and avoid "test" keyword

eerhardt · 2018-09-05T17:07:00Z

build.proj

@@ -79,6 +79,10 @@
    <TestFile Include="$(MSBuildThisFileDirectory)/test/data/external/winequality-white.csv"
      Url="https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv"
      DestinationFile="$(MSBuildThisFileDirectory)test/data/external/winequality-white.csv" />
+
+    <TestFile Include="$(MSBuildThisFileDirectory)/test/data/external/wikiDetoxAnnotated160kRows.tsv"


We shouldn't be downloading this file unless we need to run perf tests. It is a rather large file to download. So we should probably put this behind a Condition.

adamsitnik · 2018-09-06T15:55:37Z

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

+{
+    internal class EmptyWriter : TextWriter
+    {
+        private static EmptyWriter _instance = null;


nit: this could be simpified to internal static readonly EmptyWriter Instance = new EmptyWriter()

it would be nice to add a comment with explanation why do we need that

sfilipi

revoking review

danmoseley · 2018-09-06T22:43:15Z

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

+        }
+
+        [GlobalSetup(Target = nameof(wikiDetox))]
+        public void Setup_wikiDetox()


Wiki should always have a capital W in type and method names, ideally

danmoseley · 2018-09-06T22:43:36Z

test/Microsoft.ML.Benchmarks/Microsoft.ML.Benchmarks.csproj

    <ProjectReference Include="..\..\src\Microsoft.ML.KMeansClustering\Microsoft.ML.KMeansClustering.csproj" />
    <ProjectReference Include="..\..\src\Microsoft.ML.StandardLearners\Microsoft.ML.StandardLearners.csproj" />
+    <ProjectReference Include="..\..\src\Microsoft.ML.LightGBM\Microsoft.ML.LightGBM.csproj" />


Good to keep sorted

(A good habit -- it leads to fewer merge conflicts..)

eerhardt · 2018-09-06T23:47:46Z

build.proj

@@ -33,8 +33,8 @@
      RestoreProjects;
      BuildRedist;
      BuildNative;
-      $(TraversalBuildDependsOn);


Is this change necessary?

If we dont do this, then we have to build the Microsoft.ML.Benchmark project again before running

dotnet run will build the project again so its safe to revert it

eerhardt · 2018-09-06T23:48:41Z

test/Microsoft.ML.TestFramework/Datasets.cs

+        public static TestDataset WikiDetox = new TestDataset
+        {
+            name = "WikiDetox",
+            trainFilename = "Input/WikiDetoxAnnotated160kRows.tsv",


Should this be "external/WikiDetoxAnnotated160kRows.tsv"?

We are doing a similar thing for all the other files in the benchmark project https://github.com/dotnet/machinelearning/pull/820/files/d2fe71419e148aebd916626889caccb7fd25d845#diff-ea979ea573e3bccc8a3837b5e09743ffL28

The difference here is that these Datasets are used throughout the tests, not just in the benchmark tests.

I see you are mapping ..\data\external to Input\ in the Benchmarks.csproj. However, other tests try to read these files from underneath $RepoRoot/test/data, and there is no "Input" folder in that directory. Since this class holds common datasets used throughout the tests, I don't think it makes sense to have this "Input" directory in this file name in the common code. If some other test tried using this dataset, it wouldn't work.

test/Microsoft.ML.Benchmarks/Microsoft.ML.Benchmarks.csproj

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

Anipik · 2018-09-07T17:01:31Z

Benchmarks Result

BenchmarkDotNet=v0.11.1, OS=Windows 10.0.17134.228 (1803/April2018Update/Redstone4)
Intel Xeon CPU E5-1650 v4 3.60GHz, 1 CPU, 12 logical and 6 physical cores
.NET Core SDK=2.1.400
  [Host]     : .NET Core 2.1.2 (CoreCLR 4.6.26628.05, CoreFX 4.6.26629.01), 64bit RyuJIT
  Job-HIDSQF : .NET Core 2.1.2 (CoreCLR 4.6.26628.05, CoreFX 4.6.26629.01), 64bit RyuJIT

Toolchain=netcoreapp2.1  MaxIterationCount=20  WarmupCount=1

Method	Mean	Error	StdDev	Extra Metric	Gen 0	Gen 1	Gen 2	Allocated
Preceptron_CV	73.816 s	0.7231 s	0.6764 s	-	4496000.0000	1374000.0000	114000.0000	794.59 KB
LightGBM_CV	795.648 s	11.7280 s	10.9704 s	-	7767000.0000	2064000.0000	112000.0000	780.41 KB
WikiDetox	5.313 s	0.0253 s	0.0224 s	-	175000.0000	34000.0000	8000.0000	240651.7 KB

danmoseley · 2018-09-07T17:16:10Z

@sfilipi the running time of LightGBM_CV is much too large (with ~15 iterations it will take well over an hour). Is it possible to reduce the input size or otherwise improve the running time while still having a representative scenario?

Similar question for Preceptron_CV, although 73 sec is doable, it would certainly be easier to get accurate numbers if it was smaller so we coudl do more iterations. Would, say, a smaller input make it run faster while remaining representative?

WikiDetox runtime looks great.

Anipik · 2018-09-07T17:19:42Z

BigramAndTrigramBenchmark.Preceptron_CV
Mean = 73.8162 s, StdErr = 0.1746 s (0.24%); N = 15, StdDev = 0.6764 s
Min = 72.2857 s, Q1 = 73.5126 s, Median = 73.7712 s, Q3 = 74.4294 s, Max = 74.7860 s
IQR = 0.9168 s, LowerFence = 72.1373 s, UpperFence = 75.8047 s
ConfidenceInterval = [73.0931 s; 74.5393 s] (CI 99.9%), Margin = 0.7231 s (0.98% of Mean)
Skewness = -0.56, Kurtosis = 2.55, MValue = 2
-------------------- Histogram --------------------
[72.046 s ; 75.026 s) | @@@@@@@@@@@@@@@
---------------------------------------------------

BigramAndTrigramBenchmark.LightGBM_CV:

Mean = 795.6485 s, StdErr = 2.8325 s (0.36%); N = 15, StdDev = 10.9704 s
Min = 780.4932 s, Q1 = 785.8133 s, Median = 793.5253 s, Q3 = 800.2203 s, Max = 818.2505 s
IQR = 14.4070 s, LowerFence = 764.2029 s, UpperFence = 821.8307 s
ConfidenceInterval = [783.9205 s; 807.3764 s] (CI 99.9%), Margin = 11.7280 s (1.47% of Mean)
Skewness = 0.47, Kurtosis = 2.12, MValue = 2
-------------------- Histogram --------------------
[776.601 s ; 804.842 s) | @@@@@@@@@@@@
[804.842 s ; 822.143 s) | @@@
---------------------------------------------------

BigramAndTrigramBenchmark.WikiDetox: 
Mean = 5.3131 s, StdErr = 0.0060 s (0.11%); N = 14, StdDev = 0.0224 s
Min = 5.2615 s, Q1 = 5.3019 s, Median = 5.3078 s, Q3 = 5.3292 s, Max = 5.3533 s
IQR = 0.0272 s, LowerFence = 5.2611 s, UpperFence = 5.3700 s
ConfidenceInterval = [5.2879 s; 5.3384 s] (CI 99.9%), Margin = 0.0253 s (0.48% of Mean)
Skewness = -0.31, Kurtosis = 2.98, MValue = 2
-------------------- Histogram --------------------
[5.253 s ; 5.361 s) | @@@@@@@@@@@@@@
--------------------------------------------------


Here @ in histogram referes to each iteration

eerhardt · 2018-09-07T17:43:12Z

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

@@ -32,7 +32,7 @@ public void Setup_Preceptron_LightGBM()

            if (!File.Exists(s_dataPath_Wiki))
            {
-                throw new FileNotFoundException(s_dataPath_Wiki);
+                throw new FileNotFoundException($"Could not find {s_dataPath_Wiki} Please ensure you have run 'build.cmd -- /t:DownloadExternalTestFiles /p:IncludeBenchmarkData' from the root");


Needs to be /p:IncludeBenchmarkData=true, right?

eerhardt · 2018-09-07T17:45:21Z

test/Microsoft.ML.TestFramework/Datasets.cs

@@ -163,8 +163,8 @@ public static class TestDatasets
        public static TestDataset WikiDetox = new TestDataset
        {
            name = "WikiDetox",
-            trainFilename = "Input/WikiDetoxAnnotated160kRows.tsv",
-            testFilename = "Input/WikiDetoxAnnotated160kRows.tsv"
+            trainFilename = "external/WikiDetoxAnnotated160kRows.tsv",


I believe the casing here is different than what we use in the build.proj.

Here it is:
WikiDetoxAnnotated160kRows.tsv
In build.proj it is:
wikiDetoxAnnotated160kRows.tsv

When running on a case sensitive file system (i.e. Linux), they need to be the same.

eerhardt · 2018-09-07T17:47:45Z

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

+        private static string s_dataPath_Wiki;
+        private static string s_modelPath_Wiki;
+
+        [GlobalSetup(Targets = new string[] { nameof(Preceptron_CV), nameof(LightGBM_CV) })]


This setup needs to run for all the tests, right? It initializes the s_dataPath_Wiki variable, which appears to be needed even in the WikiDetox benchmark.

@eerhardt only one globalSetup can be applied to one target

side note: please do remember that BenchmarkDotNet runs all these benchmarks in dedicated processes, so if BenchmarkA has SetupMethodA and it initializes a static field, another benchmark from the same class won't have the static field initialized and the setup needs to initialize it as well

This is why when I was doing a cleanup I made all of the static fields instance fields. So good practice is to avoid using static for fields to avoid confusion.

build.proj

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

eerhardt

justinormont · 2018-09-10T18:21:27Z

test/Microsoft.ML.Benchmarks/BigramAndTrigramBenchMark.cs

+        }
+
+        [Benchmark]
+        public void Preceptron_CV()


Can we name these benchmarks so the output shows a more useful name? Or is there another way to have a more useful name [instead of nameof()]?

Currently, "Perceptron_CV" doesn't well describe this benchmark.
Perhaps: "Wiki Detox using CV Bigrams+Trichargram with AveragedPerceptron"

How does this format sound: [mode]_[task]_[dataset]_[featurization]_[learner]

Mode is one of: CV / TrainTest / Test / etc
Task is one of: MulticlassClassification / Regression / BinaryClassification / Ranking / AnomalyDetection / Clustering / MultiOutputRegression / etc

So our benchmark names would then be:

CV_Multiclass_WikiDetox_BigramsAndTrichar_OVAAveragedPerceptron

CV_Multiclass_WikiDetox_BigramsAndTrichar_LightGBMMulticlass

CV_Multiclass_WikiDetox_WordEmbeddings_OVAAveragedPerceptron

CV_Multiclass_WikiDetox_WordEmbeddings_SDCAMC

Test_Multiclass_WikiDetox_BigramsAndTrichar_OVAAveragedPerceptron (this could better convey that we are specifically benchmarking the bulk scoring speed, whereas the above benchmarks mainly training speeds)

We'll need a naming convention as we expand to additional datasets and pipelines.

justinormont · 2018-09-10T18:42:41Z

@danmosemsft for your questions about speed: #820 (comment)

@sfilipi the running time of LightGBM_CV is much too large (with ~15 iterations it will take well over an hour). Is it possible to reduce the input size or otherwise improve the running time while still having a representative scenario?

Similar question for Preceptron_CV, although 73 sec is doable, it would certainly be easier to get accurate numbers if it was smaller so we coudl do more iterations. Would, say, a smaller input make it run faster while remaining representative?

WikiDetox runtime looks great.

These benchmarks are created to be representative of customer tasks. The names are currently a bit odd, the Preceptron_CV & LightGBM_CV are model training benchmarks, while WikiDetox is a scoring speed benchmark. Since the last one (currently named WikiDetox) is only scoring, it's fast. Specifically, I would NOT truncate the datasets, or they would no longer be representative.

The longer term solution, I think, is greatly increasing the number of datasets/pipelines represented. Statistical significance should be obtained across many datasets; currently we are getting statistical significance of the runtimes by re-running the same test many times. While this creates a representative number for this dataset and pipeline, it over-focuses on this dataset/pipeline and will overfit our perf improvements to improve a small number of datasets/pipelines.

We should strive to make overall improvements across many datasets (and tasks). Some datasets will get slower, but on aggregate-metrics we will see gains.

justinormont

Looks good, but I'd fix these before pushing into the repo:

Re-enable the required Wiki Detox dataset file in the CDN:
Added Benchmark performance tests for wikidetoxData #820 (comment)
Less confusing names for the benchmarks:
Added Benchmark performance tests for wikidetoxData #820 (comment)
Better error message if the dataset is missing:
Added Benchmark performance tests for wikidetoxData #820 (comment) (nice to have)

Anipik · 2018-09-10T22:48:05Z

Better error message if the dataset is missing:
#820 (comment) (nice to have)

@justinormont what else information do you want me to add here ? Currently we throw this
throw new FileNotFoundException($"Could not find {_dataPath_Wiki} Please ensure you have run 'build.cmd -- /t:DownloadExternalTestFiles /p:IncludeBenchmarkData=true' from the root");

justinormont

LGTM

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Anipik mentioned this pull request Sep 10, 2018

WordEmbedding Tests added plus added dimension check for the first row #880

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Anipik added 7 commits September 10, 2018 21:39

added some performance tests

8a09798

added word embeding performancetests

8904a31

Build Failure Corrected

3e76854

feedback addressed

abf22a7

Casing, static fields removed and excpetion corrected

78ff767

s_ removed

80e6585

Names changed

d540422

justinormont merged commit f0f04ef into dotnet:master Sep 11, 2018

This was referenced Sep 12, 2018

Perf benchmarks for optimization #711

Closed

Added numeric ranking Performance Tests #888

Merged

Anipik deleted the BenchMark branch October 10, 2018 18:23

ghost locked as resolved and limited conversation to collaborators Mar 29, 2022

Added Benchmark performance tests for wikidetoxData #820

Added Benchmark performance tests for wikidetoxData #820

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