Merge branch '2.5' into plus-plus-check

.github/workflows/ci.yml

@@ -20,7 +20,7 @@ jobs:
         with:
           php-version: ${{ matrix.php-versions }}
           tools: composer, pecl
-          extensions: svm, mbstring, gd, fileinfo
+          extensions: svm, mbstring, gd, fileinfo, swoole
           ini-values: memory_limit=-1
 
       - name: Validate composer.json

benchmarks/Classifiers/OneVsRestBench.php

@@ -2,18 +2,22 @@
 
 namespace Rubix\ML\Benchmarks\Classifiers;
 
+use Rubix\ML\Backends\Backend;
 use Rubix\ML\Classifiers\OneVsRest;
 use Rubix\ML\Datasets\Generators\Blob;
 use Rubix\ML\Classifiers\LogisticRegression;
 use Rubix\ML\NeuralNet\Optimizers\Stochastic;
 use Rubix\ML\Datasets\Generators\Agglomerate;
+use Rubix\ML\Tests\DataProvider\BackendProviderTrait;
 
 /**
  * @Groups({"Classifiers"})
  * @BeforeMethods({"setUp"})
  */
 class OneVsRestBench
 {
+    use BackendProviderTrait;
+
     protected const TRAINING_SIZE = 10000;
 
     protected const TESTING_SIZE = 10000;
@@ -52,9 +56,13 @@ public function setUp() : void
      * @Subject
      * @Iterations(5)
      * @OutputTimeUnit("seconds", precision=3)
+     * @ParamProviders("provideBackends")
+     * @param array{ backend: Backend } $params
      */
-    public function trainPredict() : void
+    public function trainPredict(array $params) : void
     {
+        $this->estimator->setBackend($params['backend']);
+
         $this->estimator->train($this->training);
 
         $this->estimator->predict($this->testing);

benchmarks/Classifiers/RandomForestBench.php

@@ -2,17 +2,21 @@
 
 namespace Rubix\ML\Benchmarks\Classifiers;
 
+use Rubix\ML\Backends\Backend;
 use Rubix\ML\Classifiers\RandomForest;
 use Rubix\ML\Datasets\Generators\Blob;
 use Rubix\ML\Classifiers\ClassificationTree;
 use Rubix\ML\Datasets\Generators\Agglomerate;
+use Rubix\ML\Tests\DataProvider\BackendProviderTrait;
 use Rubix\ML\Transformers\IntervalDiscretizer;
 
 /**
  * @Groups({"Classifiers"})
  */
 class RandomForestBench
 {
+    use BackendProviderTrait;
+
     protected const TRAINING_SIZE = 10000;
 
     protected const TESTING_SIZE = 10000;
@@ -70,9 +74,13 @@ public function setUpCategorical() : void
      * @Iterations(5)
      * @BeforeMethods({"setUpContinuous"})
      * @OutputTimeUnit("seconds", precision=3)
+     * @ParamProviders("provideBackends")
+     * @param array{ backend: Backend } $params
      */
-    public function continuous() : void
+    public function continuous(array $params) : void
     {
+        $this->estimator->setBackend($params['backend']);
+
         $this->estimator->train($this->training);
 
         $this->estimator->predict($this->testing);
@@ -83,9 +91,13 @@ public function continuous() : void
      * @Iterations(5)
      * @BeforeMethods({"setUpCategorical"})
      * @OutputTimeUnit("seconds", precision=3)
+     * @ParamProviders("provideBackends")
+     * @param array{ backend: Backend } $params
      */
-    public function categorical() : void
+    public function categorical(array $params) : void
     {
+        $this->estimator->setBackend($params['backend']);
+
         $this->estimator->train($this->training);
 
         $this->estimator->predict($this->testing);

composer.json

@@ -49,7 +49,8 @@
         "phpstan/extension-installer": "^1.0",
         "phpstan/phpstan": "^1.0",
         "phpstan/phpstan-phpunit": "^1.0",
-        "phpunit/phpunit": "^9.0"
+        "phpunit/phpunit": "^9.0",
+        "swoole/ide-helper": "^5.1"
     },
     "suggest": {
         "ext-tensor": "For fast Matrix/Vector computing",

phpstan.neon

@@ -6,3 +6,4 @@ parameters:
         - 'benchmarks'
     excludePaths:
         - src/Backends/Amp.php
+        - src/Backends/Swoole.php

phpunit.xml

@@ -1,5 +1,18 @@
 <?xml version="1.0" encoding="UTF-8"?>
-<phpunit xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" backupGlobals="false" backupStaticAttributes="false" bootstrap="vendor/autoload.php" colors="true" convertErrorsToExceptions="true" convertNoticesToExceptions="true" convertWarningsToExceptions="true" forceCoversAnnotation="true" processIsolation="false" stopOnFailure="false" xsi:noNamespaceSchemaLocation="https://schema.phpunit.de/9.3/phpunit.xsd">
+<phpunit
+  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+  backupGlobals="false"
+  backupStaticAttributes="false"
+  bootstrap="vendor/autoload.php"
+  colors="true"
+  convertErrorsToExceptions="true"
+  convertNoticesToExceptions="true"
+  convertWarningsToExceptions="true"
+  forceCoversAnnotation="true"
+  processIsolation="true"
+  stopOnFailure="false"
+  xsi:noNamespaceSchemaLocation="https://schema.phpunit.de/9.3/phpunit.xsd"
+>
   <coverage processUncoveredFiles="true">
     <include>
       <directory suffix=".php">src</directory>

src/Backends/Swoole.php

@@ -0,0 +1,173 @@
+<?php
+
+namespace Rubix\ML\Backends;
+
+use Rubix\ML\Backends\Tasks\Task;
+use Rubix\ML\Specifications\ExtensionIsLoaded;
+use Rubix\ML\Specifications\SwooleExtensionIsLoaded;
+use RuntimeException;
+use Swoole\Atomic;
+use Swoole\Process;
+
+use function Swoole\Coroutine\run;
+
+/**
+ * Swoole
+ *
+ * Works both with Swoole and OpenSwoole.
+ *
+ * @category    Machine Learning
+ * @package     Rubix/ML
+ */
+class Swoole implements Backend
+{
+    /**
+     * The queue of tasks to be processed in parallel.
+     */
+    protected array $queue = [];
+
+    private int $cpus;
+
+    private int $hasIgbinary;
+
+    public function __construct()
+    {
+        SwooleExtensionIsLoaded::create()->check();
+
+        $this->cpus = swoole_cpu_num();
+        $this->hasIgbinary = ExtensionIsLoaded::with('igbinary')->passes();
+    }
+
+    /**
+     * Queue up a deferred task for backend processing.
+     *
+     * @internal
+     *
+     * @param Task $task
+     * @param callable(mixed,mixed):void $after
+     * @param mixed $context
+     */
+    public function enqueue(Task $task, ?callable $after = null, $context = null) : void
+    {
+        $this->queue[] = function () use ($task, $after, $context) {
+            $result = $task();
+
+            if ($after) {
+                $after($result, $context);
+            }
+
+            return $result;
+        };
+    }
+
+    /**
+     * Process the queue and return the results.
+     *
+     * @internal
+     *
+     * @return mixed[]
+     */
+    public function process() : array
+    {
+        $results = [];
+
+        $maxMessageLength = new Atomic(0);
+        $workerProcesses = [];
+
+        $currentCpu = 0;
+
+        foreach ($this->queue as $index => $queueItem) {
+            $workerProcess = new Process(
+                function (Process $worker) use ($maxMessageLength, $queueItem) {
+                    $serialized = $this->serialize($queueItem());
+
+                    $serializedLength = strlen($serialized);
+                    $currentMaxSerializedLength = $maxMessageLength->get();
+
+                    if ($serializedLength > $currentMaxSerializedLength) {
+                        $maxMessageLength->set($serializedLength);
+                    }
+
+                    $worker->exportSocket()->send($serialized);
+                },
+                // redirect_stdin_and_stdout
+                false,
+                // pipe_type
+                SOCK_DGRAM,
+                // enable_coroutine
+                true,
+            );
+
+            $workerProcess->setAffinity([$currentCpu]);
+            $workerProcess->setBlocking(false);
+            $workerProcess->start();
+
+            $workerProcesses[$index] = $workerProcess;
+
+            $currentCpu = ($currentCpu + 1) % $this->cpus;
+        }
+
+        run(function () use ($maxMessageLength, &$results, $workerProcesses) {
+            foreach ($workerProcesses as $index => $workerProcess) {
+                $status = $workerProcess->wait();
+
+                if (0 !== $status['code']) {
+                    throw new RuntimeException('Worker process exited with an error');
+                }
+
+                $socket = $workerProcess->exportSocket();
+
+                if ($socket->isClosed()) {
+                    throw new RuntimeException('Coroutine socket is closed');
+                }
+
+                $maxMessageLengthValue = $maxMessageLength->get();
+
+                $receivedData = $socket->recv($maxMessageLengthValue);
+                $unserialized = $this->unserialize($receivedData);
+
+                $results[] = $unserialized;
+            }
+        });
+
+        return $results;
+    }
+
+    /**
+     * Flush the queue
+     */
+    public function flush() : void
+    {
+        $this->queue = [];
+    }
+
+    private function serialize(mixed $data) : string
+    {
+        if ($this->hasIgbinary) {
+            return igbinary_serialize($data);
+        }
+
+        return serialize($data);
+    }
+
+    private function unserialize(string $serialized) : mixed
+    {
+        if ($this->hasIgbinary) {
+            return igbinary_unserialize($serialized);
+        }
+
+        return unserialize($serialized);
+    }
+
+    /**
+     * Return the string representation of the object.
+     *
+     * @internal
+     *
+     * @return string
+     */
+    public function __toString() : string
+    {
+        return 'Swoole';
+    }
+}

src/Classifiers/LogisticRegression.php

@@ -491,4 +491,20 @@ public function __toString() : string
     {
         return 'Logistic Regression (' . Params::stringify($this->params()) . ')';
     }
+
+    /**
+     * Without this method, causes errors with Swoole backend + Igbinary
+     * serialization.
+     *
+     * Can be removed if it's no longer the case.
+     *
+     * @internal
+     * @param array<string,mixed> $data
+     */
+    public function __unserialize(array $data) : void
+    {
+        foreach ($data as $propertyName => $propertyValue) {
+            $this->{$propertyName} = $propertyValue;
+        }
+    }
 }

src/EstimatorWrapper.php

@@ -0,0 +1,20 @@
+<?php
+
+namespace Rubix\ML;
+
+/**
+ * Wrapper
+ *
+ * @category    Machine Learning
+ * @package     Rubix/ML
+ * @author      Ronan Giron
+ */
+interface EstimatorWrapper extends Estimator
+{
+    /**
+     * Return the base estimator instance.
+     *
+     * @return Estimator
+     */
+    public function base() : Estimator;
+}

src/GridSearch.php

@@ -39,7 +39,7 @@
  * @package     Rubix/ML
  * @author      Andrew DalPino
  */
-class GridSearch implements Estimator, Learner, Parallel, Verbose, Persistable
+class GridSearch implements EstimatorWrapper, Learner, Parallel, Verbose, Persistable
 {
     use AutotrackRevisions, Multiprocessing, LoggerAware;
 

src/PersistentModel.php

@@ -21,7 +21,7 @@
  * @package     Rubix/ML
  * @author      Andrew DalPino
  */
-class PersistentModel implements Estimator, Learner, Probabilistic, Scoring
+class PersistentModel implements EstimatorWrapper, Learner, Probabilistic, Scoring
 {
     /**
      * The persistable base learner.

src/Pipeline.php

@@ -25,7 +25,7 @@
  * @package     Rubix/ML
  * @author      Andrew DalPino
  */
-class Pipeline implements Online, Probabilistic, Scoring, Persistable
+class Pipeline implements Online, Probabilistic, Scoring, Persistable, EstimatorWrapper
 {
     use AutotrackRevisions;