mirror of
https://github.com/Llewellynvdm/php-ml.git
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116 lines
4.2 KiB
PHP
116 lines
4.2 KiB
PHP
<?php
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declare(strict_types=1);
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namespace Phpml\Tests\NeuralNetwork\Network;
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use Phpml\Exception\InvalidArgumentException;
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use Phpml\NeuralNetwork\ActivationFunction;
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use Phpml\NeuralNetwork\Layer;
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use Phpml\NeuralNetwork\Network\MultilayerPerceptron;
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use Phpml\NeuralNetwork\Node\Neuron;
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use PHPUnit\Framework\TestCase;
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use PHPUnit_Framework_MockObject_MockObject;
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class MultilayerPerceptronTest extends TestCase
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{
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public function testThrowExceptionWhenHiddenLayersAreEmpty(): void
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{
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$this->expectException(InvalidArgumentException::class);
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$this->expectExceptionMessage('Provide at least 1 hidden layer');
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$this->getMockForAbstractClass(
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MultilayerPerceptron::class,
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[5, [], [0, 1], 1000, null, 0.42]
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);
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}
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public function testThrowExceptionWhenThereIsOnlyOneClass(): void
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{
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$this->expectException(InvalidArgumentException::class);
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$this->expectExceptionMessage('Provide at least 2 different classes');
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$this->getMockForAbstractClass(
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MultilayerPerceptron::class,
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[5, [3], [0], 1000, null, 0.42]
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);
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}
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public function testThrowExceptionWhenClassesAreNotUnique(): void
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{
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$this->expectException(InvalidArgumentException::class);
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$this->expectExceptionMessage('Classes must be unique');
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$this->getMockForAbstractClass(
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MultilayerPerceptron::class,
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[5, [3], [0, 1, 2, 3, 1], 1000, null, 0.42]
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);
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}
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public function testLearningRateSetter(): void
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{
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/** @var MultilayerPerceptron $mlp */
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$mlp = $this->getMockForAbstractClass(
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MultilayerPerceptron::class,
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[5, [3], [0, 1], 1000, null, 0.42]
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);
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self::assertEquals(0.42, self::readAttribute($mlp, 'learningRate'));
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$backprop = self::readAttribute($mlp, 'backpropagation');
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self::assertEquals(0.42, self::readAttribute($backprop, 'learningRate'));
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$mlp->setLearningRate(0.24);
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self::assertEquals(0.24, self::readAttribute($mlp, 'learningRate'));
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$backprop = self::readAttribute($mlp, 'backpropagation');
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self::assertEquals(0.24, self::readAttribute($backprop, 'learningRate'));
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}
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public function testLearningRateSetterWithCustomActivationFunctions(): void
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{
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$activation_function = $this->getActivationFunctionMock();
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/** @var MultilayerPerceptron $mlp */
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$mlp = $this->getMockForAbstractClass(
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MultilayerPerceptron::class,
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[5, [[3, $activation_function], [5, $activation_function]], [0, 1], 1000, null, 0.42]
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);
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self::assertEquals(0.42, self::readAttribute($mlp, 'learningRate'));
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$backprop = self::readAttribute($mlp, 'backpropagation');
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self::assertEquals(0.42, self::readAttribute($backprop, 'learningRate'));
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$mlp->setLearningRate(0.24);
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self::assertEquals(0.24, self::readAttribute($mlp, 'learningRate'));
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$backprop = self::readAttribute($mlp, 'backpropagation');
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self::assertEquals(0.24, self::readAttribute($backprop, 'learningRate'));
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}
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public function testLearningRateSetterWithLayerObject(): void
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{
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$activation_function = $this->getActivationFunctionMock();
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/** @var MultilayerPerceptron $mlp */
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$mlp = $this->getMockForAbstractClass(
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MultilayerPerceptron::class,
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[5, [new Layer(3, Neuron::class, $activation_function), new Layer(5, Neuron::class, $activation_function)], [0, 1], 1000, null, 0.42]
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);
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self::assertEquals(0.42, self::readAttribute($mlp, 'learningRate'));
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$backprop = self::readAttribute($mlp, 'backpropagation');
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self::assertEquals(0.42, self::readAttribute($backprop, 'learningRate'));
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$mlp->setLearningRate(0.24);
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self::assertEquals(0.24, self::readAttribute($mlp, 'learningRate'));
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$backprop = self::readAttribute($mlp, 'backpropagation');
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self::assertEquals(0.24, self::readAttribute($backprop, 'learningRate'));
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}
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/**
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* @return ActivationFunction|PHPUnit_Framework_MockObject_MockObject
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*/
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private function getActivationFunctionMock()
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{
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return $this->getMockForAbstractClass(ActivationFunction::class);
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}
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}
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