PHP Classes

File: TEST/TrainingTest/untitled.php

Recommend this page to a friend!
  Classes of Cuthbert Martin Lwinga   PHP Neural Net Library   TEST/TrainingTest/untitled.php   Download  
File: TEST/TrainingTest/untitled.php
Role: Example script
Content type: text/plain
Description: Example script
Class: PHP Neural Net Library
Build, train, evaluate, and use neural networks
Author: By
Last change:
Date: 11 months ago
Size: 1,086 bytes
 

Contents

Class file image Download
<?php
ini_set
('memory_limit', '1024M'); // Increase the memory limit to 1024MB
include_once("../../CLASSES/Headers.php");
use
NameSpaceNumpyLight\NumpyLight;
use
NameSpaceRandomGenerator\RandomGenerator;
use
NameSpaceActivationRelu\Activation_Relu;
use
NameSpaceOptimizerSGD\Optimizer_SGD;
use
NameSpaceOptimizerAdagrad\Optimizer_Adagrad;
use
NameSpaceOptimizerRMSprop\Optimizer_RMSprop;

list(
$X, $y) = NumpyLight::spiral_data(1000,2);

$y = NumpyLight::reshape($y,[-1,1]);



// $validation = NumpyLight::spiral_data(1000,3);


// $Model = new Model();
// $Model->add(new Layer_Dense(2,64,$weight_regularizer_l2 = 5e-4 ,$bias_regularizer_l2 = 5e-4));
// $Model->add(new Activation_Relu());
// $Model->add(new Layer_Dense(64,1));
// $Model->add(new Activation_Sigmoid());
// $Model->set(
// $loss_function = new Loss_BinaryCrossentropy(),
// $optimizer = new Optimizer_Adam($learning_rate = 0.001, $decay = 5e-7),
// $accuracy = new Accuracy_Categorical()
// );

// $Model->finalize();


// $Model->train($X, $y,$epoch = 10000,$print_every = 100,$validation_data = $validation);

?>