php-ml/tests/Phpml/NeuralNetwork/Network/LayeredNetworkTest.php

74 lines
2.1 KiB
PHP

<?php
declare(strict_types=1);
namespace Phpml\Tests\NeuralNetwork\Network;
use Phpml\NeuralNetwork\ActivationFunction;
use Phpml\NeuralNetwork\Layer;
use Phpml\NeuralNetwork\Network\LayeredNetwork;
use Phpml\NeuralNetwork\Node\Input;
use PHPUnit\Framework\TestCase;
use PHPUnit_Framework_MockObject_MockObject;
class LayeredNetworkTest extends TestCase
{
public function testLayersSettersAndGetters(): void
{
$network = $this->getLayeredNetworkMock();
$network->addLayer($layer1 = new Layer());
$network->addLayer($layer2 = new Layer());
$this->assertEquals([$layer1, $layer2], $network->getLayers());
}
public function testGetLastLayerAsOutputLayer(): void
{
$network = $this->getLayeredNetworkMock();
$network->addLayer($layer1 = new Layer());
$this->assertEquals($layer1, $network->getOutputLayer());
$network->addLayer($layer2 = new Layer());
$this->assertEquals($layer2, $network->getOutputLayer());
}
public function testSetInputAndGetOutput(): void
{
$network = $this->getLayeredNetworkMock();
$network->addLayer(new Layer(2, Input::class));
$network->setInput($input = [34, 43]);
$this->assertEquals($input, $network->getOutput());
$network->addLayer(new Layer(1));
$this->assertEquals([0.5], $network->getOutput());
}
public function testSetInputAndGetOutputWithCustomActivationFunctions(): void
{
$network = $this->getLayeredNetworkMock();
$network->addLayer(new Layer(2, Input::class, $this->getActivationFunctionMock()));
$network->setInput($input = [34, 43]);
$this->assertEquals($input, $network->getOutput());
}
/**
* @return LayeredNetwork|PHPUnit_Framework_MockObject_MockObject
*/
private function getLayeredNetworkMock()
{
return $this->getMockForAbstractClass(LayeredNetwork::class);
}
/**
* @return ActivationFunction|PHPUnit_Framework_MockObject_MockObject
*/
private function getActivationFunctionMock()
{
return $this->getMockForAbstractClass(ActivationFunction::class);
}
}