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