60 lines
1.4 KiB
PHP
60 lines
1.4 KiB
PHP
<?php
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declare(strict_types=1);
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namespace Phpml\Tests\NeuralNetwork\ActivationFunction;
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use Phpml\NeuralNetwork\ActivationFunction\PReLU;
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use PHPUnit\Framework\TestCase;
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class PReLUTest extends TestCase
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{
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/**
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* @dataProvider preluProvider
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*
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* @param float|int $value
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*/
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public function testPReLUActivationFunction(float $beta, float $expected, $value): void
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{
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$prelu = new PReLU($beta);
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self::assertEqualsWithDelta($expected, $prelu->compute($value), 0.001);
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}
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public function preluProvider(): array
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{
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return [
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[0.01, 0.367, 0.367],
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[0.0, 1, 1],
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[0.3, -0.3, -1],
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[0.9, 3, 3],
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[0.02, -0.06, -3],
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];
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}
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/**
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* @dataProvider preluDerivativeProvider
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*
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* @param float|int $value
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*/
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public function testPReLUDerivative(float $beta, float $expected, $value): void
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{
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$prelu = new PReLU($beta);
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$activatedValue = $prelu->compute($value);
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self::assertEquals($expected, $prelu->differentiate($value, $activatedValue));
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}
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public function preluDerivativeProvider(): array
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{
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return [
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[0.5, 0.5, -3],
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[0.5, 1, 0],
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[0.5, 1, 1],
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[0.01, 1, 1],
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[1, 1, 1],
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[0.3, 1, 0.1],
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[0.1, 0.1, -0.1],
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];
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}
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}
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