mirror of
https://github.com/moodle/moodle.git
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748 lines
24 KiB
PHP
748 lines
24 KiB
PHP
<?php
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// This file is part of Moodle - http://moodle.org/
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//
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// Moodle is free software: you can redistribute it and/or modify
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// it under the terms of the GNU General Public License as published by
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// the Free Software Foundation, either version 3 of the License, or
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// (at your option) any later version.
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//
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// Moodle is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU General Public License
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// along with Moodle. If not, see <http://www.gnu.org/licenses/>.
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/**
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* Python predictions processor
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*
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* @package mlbackend_python
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* @copyright 2016 David Monllao {@link http://www.davidmonllao.com}
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* @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
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*/
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namespace mlbackend_python;
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defined('MOODLE_INTERNAL') || die();
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/**
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* Python predictions processor.
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*
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* @package mlbackend_python
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* @copyright 2016 David Monllao {@link http://www.davidmonllao.com}
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* @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
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*/
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class processor implements \core_analytics\classifier, \core_analytics\regressor, \core_analytics\packable {
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/**
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* The required version of the python package that performs all calculations.
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*/
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const REQUIRED_PIP_PACKAGE_VERSION = '3.0.4';
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/**
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* The python package is installed in a server.
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* @var bool
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*/
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protected $useserver;
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/**
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* The path to the Python bin.
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*
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* @var string
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*/
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protected $pathtopython;
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/**
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* Remote server host
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* @var string
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*/
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protected $host;
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/**
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* Remote server port
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* @var int
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*/
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protected $port;
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/**
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* Whether to use http or https.
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* @var bool
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*/
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protected $secure;
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/**
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* Server username.
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* @var string
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*/
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protected $username;
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/**
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* Server password for $this->username.
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* @var string
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*/
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protected $password;
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/**
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* The constructor.
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*
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*/
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public function __construct() {
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global $CFG;
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$config = get_config('mlbackend_python');
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$this->useserver = !empty($config->useserver);
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if (!$this->useserver) {
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// Set the python location if there is a value.
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if (!empty($CFG->pathtopython)) {
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$this->pathtopython = $CFG->pathtopython;
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}
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} else {
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$this->host = $config->host ?? '';
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$this->port = $config->port ?? '';
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$this->secure = $config->secure ?? false;
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$this->username = $config->username ?? '';
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$this->password = $config->password ?? '';
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}
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}
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/**
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* Is the plugin ready to be used?.
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*
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* @return bool|string Returns true on success, a string detailing the error otherwise
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*/
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public function is_ready() {
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if (!$this->useserver) {
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return $this->is_webserver_ready();
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} else {
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return $this->is_python_server_ready();
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}
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}
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/**
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* Checks if the python package is available in the web server executing this script.
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*
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* @return bool|string Returns true on success, a string detailing the error otherwise
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*/
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protected function is_webserver_ready() {
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if (empty($this->pathtopython)) {
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$settingurl = new \moodle_url('/admin/settings.php', array('section' => 'systempaths'));
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return get_string('pythonpathnotdefined', 'mlbackend_python', $settingurl->out());
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}
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// Check the installed pip package version.
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$cmd = "{$this->pathtopython} -m moodlemlbackend.version";
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$output = null;
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$exitcode = null;
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// Execute it sending the standard error to $output.
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$result = exec($cmd . ' 2>&1', $output, $exitcode);
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if ($exitcode != 0) {
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return get_string('pythonpackagenotinstalled', 'mlbackend_python', $cmd);
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}
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$vercheck = self::check_pip_package_version($result);
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return $this->version_check_return($result, $vercheck);
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}
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/**
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* Checks if the server can be accessed.
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*
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* @return bool|string True or an error string.
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*/
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protected function is_python_server_ready() {
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if (empty($this->host) || empty($this->port) || empty($this->username) || empty($this->password)) {
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return get_string('errornoconfigdata', 'mlbackend_python');
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}
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// Connection is allowed to use 'localhost' and other potentially blocked hosts/ports.
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$curl = new \curl(['ignoresecurity' => true]);
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$responsebody = $curl->get($this->get_server_url('version')->out(false));
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if ($curl->info['http_code'] !== 200) {
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return get_string('errorserver', 'mlbackend_python', $this->server_error_str($curl->info['http_code'], $responsebody));
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}
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$vercheck = self::check_pip_package_version($responsebody);
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return $this->version_check_return($responsebody, $vercheck);
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}
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/**
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* Delete the model version output directory.
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*
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* @throws \moodle_exception
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* @param string $uniqueid
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* @param string $modelversionoutputdir
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* @return null
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*/
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public function clear_model($uniqueid, $modelversionoutputdir) {
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if (!$this->useserver) {
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remove_dir($modelversionoutputdir);
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} else {
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// Use the server.
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$url = $this->get_server_url('deletemodel');
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list($responsebody, $httpcode) = $this->server_request($url, 'post', ['uniqueid' => $uniqueid]);
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}
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}
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/**
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* Delete the model output directory.
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*
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* @throws \moodle_exception
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* @param string $modeloutputdir
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* @param string $uniqueid
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* @return null
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*/
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public function delete_output_dir($modeloutputdir, $uniqueid) {
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if (!$this->useserver) {
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remove_dir($modeloutputdir);
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} else {
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$url = $this->get_server_url('deletemodel');
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list($responsebody, $httpcode) = $this->server_request($url, 'post', ['uniqueid' => $uniqueid]);
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}
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}
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/**
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* Trains a machine learning algorithm with the provided dataset.
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*
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* @param string $uniqueid
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* @param \stored_file $dataset
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* @param string $outputdir
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* @return \stdClass
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*/
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public function train_classification($uniqueid, \stored_file $dataset, $outputdir) {
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if (!$this->useserver) {
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// Use the local file system.
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list($result, $exitcode) = $this->exec_command('training', [$uniqueid, $outputdir,
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$this->get_file_path($dataset)], 'errornopredictresults');
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} else {
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// Use the server.
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$requestparams = ['uniqueid' => $uniqueid, 'dirhash' => $this->hash_dir($outputdir),
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'dataset' => $dataset];
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$url = $this->get_server_url('training');
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list($result, $httpcode) = $this->server_request($url, 'post', $requestparams);
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}
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if (!$resultobj = json_decode($result)) {
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throw new \moodle_exception('errorpredictwrongformat', 'analytics', '', json_last_error_msg());
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}
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if ($resultobj->status != 0) {
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$resultobj = $this->format_error_info($resultobj);
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}
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return $resultobj;
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}
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/**
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* Classifies the provided dataset samples.
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*
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* @param string $uniqueid
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* @param \stored_file $dataset
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* @param string $outputdir
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* @return \stdClass
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*/
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public function classify($uniqueid, \stored_file $dataset, $outputdir) {
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if (!$this->useserver) {
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// Use the local file system.
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list($result, $exitcode) = $this->exec_command('prediction', [$uniqueid, $outputdir,
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$this->get_file_path($dataset)], 'errornopredictresults');
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} else {
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// Use the server.
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$requestparams = ['uniqueid' => $uniqueid, 'dirhash' => $this->hash_dir($outputdir),
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'dataset' => $dataset];
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$url = $this->get_server_url('prediction');
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list($result, $httpcode) = $this->server_request($url, 'post', $requestparams);
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}
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if (!$resultobj = json_decode($result)) {
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throw new \moodle_exception('errorpredictwrongformat', 'analytics', '', json_last_error_msg());
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}
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if ($resultobj->status != 0) {
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$resultobj = $this->format_error_info($resultobj);
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}
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return $resultobj;
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}
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/**
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* Evaluates this processor classification model using the provided supervised learning dataset.
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*
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* @param string $uniqueid
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* @param float $maxdeviation
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* @param int $niterations
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* @param \stored_file $dataset
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* @param string $outputdir
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* @param string $trainedmodeldir
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* @return \stdClass
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*/
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public function evaluate_classification($uniqueid, $maxdeviation, $niterations, \stored_file $dataset,
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$outputdir, $trainedmodeldir) {
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global $CFG;
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if (!$this->useserver) {
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// Use the local file system.
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$datasetpath = $this->get_file_path($dataset);
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$params = [$uniqueid, $outputdir, $datasetpath, \core_analytics\model::MIN_SCORE,
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$maxdeviation, $niterations];
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if ($trainedmodeldir) {
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$params[] = $trainedmodeldir;
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}
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list($result, $exitcode) = $this->exec_command('evaluation', $params, 'errornopredictresults');
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if (!$resultobj = json_decode($result)) {
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throw new \moodle_exception('errorpredictwrongformat', 'analytics', '', json_last_error_msg());
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}
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} else {
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// Use the server.
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$requestparams = ['uniqueid' => $uniqueid, 'minscore' => \core_analytics\model::MIN_SCORE,
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'maxdeviation' => $maxdeviation, 'niterations' => $niterations,
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'dirhash' => $this->hash_dir($outputdir), 'dataset' => $dataset];
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if ($trainedmodeldir) {
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$requestparams['trainedmodeldirhash'] = $this->hash_dir($trainedmodeldir);
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}
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$url = $this->get_server_url('evaluation');
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list($result, $httpcode) = $this->server_request($url, 'post', $requestparams);
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if (!$resultobj = json_decode($result)) {
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throw new \moodle_exception('errorpredictwrongformat', 'analytics', '', json_last_error_msg());
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}
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// We need an extra request to get the resources generated during the evaluation process.
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// Directory to temporarly store the evaluation log zip returned by the server.
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$evaluationtmpdir = make_request_directory();
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$evaluationzippath = $evaluationtmpdir . DIRECTORY_SEPARATOR . 'evaluationlog.zip';
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$requestparams = ['uniqueid' => $uniqueid, 'dirhash' => $this->hash_dir($outputdir),
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'runid' => $resultobj->runid];
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$url = $this->get_server_url('evaluationlog');
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list($result, $httpcode) = $this->server_request($url, 'download_one', $requestparams,
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['filepath' => $evaluationzippath]);
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$rundir = $outputdir . DIRECTORY_SEPARATOR . 'logs' . DIRECTORY_SEPARATOR . $resultobj->runid;
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if (!mkdir($rundir, $CFG->directorypermissions, true)) {
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throw new \moodle_exception('errorexportmodelresult', 'analytics');
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}
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$zip = new \zip_packer();
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$success = $zip->extract_to_pathname($evaluationzippath, $rundir, null, null, true);
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if (!$success) {
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$a = 'The evaluation files can not be exported to ' . $rundir;
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throw new \moodle_exception('errorpredictionsprocessor', 'analytics', '', $a);
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}
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$resultobj->dir = $rundir;
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}
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$resultobj = $this->add_extra_result_info($resultobj);
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return $resultobj;
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}
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/**
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* Exports the machine learning model.
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*
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* @throws \moodle_exception
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* @param string $uniqueid The model unique id
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* @param string $modeldir The directory that contains the trained model.
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* @return string The path to the directory that contains the exported model.
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*/
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public function export(string $uniqueid, string $modeldir) : string {
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$exporttmpdir = make_request_directory();
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if (!$this->useserver) {
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// Use the local file system.
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// We include an exporttmpdir as we want to be sure that the file is not deleted after the
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// python process finishes.
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list($exportdir, $exitcode) = $this->exec_command('export', [$uniqueid, $modeldir, $exporttmpdir],
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'errorexportmodelresult');
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if ($exitcode != 0) {
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throw new \moodle_exception('errorexportmodelresult', 'analytics');
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}
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} else {
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// Use the server.
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$requestparams = ['uniqueid' => $uniqueid, 'dirhash' => $this->hash_dir($modeldir)];
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$exportzippath = $exporttmpdir . DIRECTORY_SEPARATOR . 'export.zip';
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$url = $this->get_server_url('export');
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list($result, $httpcode) = $this->server_request($url, 'download_one', $requestparams,
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['filepath' => $exportzippath]);
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$exportdir = make_request_directory();
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$zip = new \zip_packer();
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$success = $zip->extract_to_pathname($exportzippath, $exportdir, null, null, true);
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if (!$success) {
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throw new \moodle_exception('errorexportmodelresult', 'analytics');
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}
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}
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return $exportdir;
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}
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/**
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* Imports the provided machine learning model.
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*
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* @param string $uniqueid The model unique id
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* @param string $modeldir The directory that will contain the trained model.
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* @param string $importdir The directory that contains the files to import.
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* @return bool Success
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*/
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public function import(string $uniqueid, string $modeldir, string $importdir) : bool {
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if (!$this->useserver) {
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// Use the local file system.
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list($result, $exitcode) = $this->exec_command('import', [$uniqueid, $modeldir, $importdir],
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'errorimportmodelresult');
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if ($exitcode != 0) {
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throw new \moodle_exception('errorimportmodelresult', 'analytics');
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}
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} else {
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// Use the server.
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// Zip the $importdir to send a single file.
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$importzipfile = $this->zip_dir($importdir);
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if (!$importzipfile) {
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// There was an error zipping the directory.
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throw new \moodle_exception('errorimportmodelresult', 'analytics');
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}
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$requestparams = ['uniqueid' => $uniqueid, 'dirhash' => $this->hash_dir($modeldir),
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'importzip' => curl_file_create($importzipfile, null, 'import.zip')];
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$url = $this->get_server_url('import');
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list($result, $httpcode) = $this->server_request($url, 'post', $requestparams);
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}
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return (bool)$result;
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}
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/**
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* Train this processor regression model using the provided supervised learning dataset.
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*
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* @throws new \coding_exception
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* @param string $uniqueid
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* @param \stored_file $dataset
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* @param string $outputdir
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* @return \stdClass
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*/
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public function train_regression($uniqueid, \stored_file $dataset, $outputdir) {
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throw new \coding_exception('This predictor does not support regression yet.');
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}
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/**
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* Estimates linear values for the provided dataset samples.
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*
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* @throws new \coding_exception
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* @param string $uniqueid
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* @param \stored_file $dataset
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* @param mixed $outputdir
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* @return void
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*/
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public function estimate($uniqueid, \stored_file $dataset, $outputdir) {
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throw new \coding_exception('This predictor does not support regression yet.');
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}
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/**
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* Evaluates this processor regression model using the provided supervised learning dataset.
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*
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* @throws new \coding_exception
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* @param string $uniqueid
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* @param float $maxdeviation
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* @param int $niterations
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* @param \stored_file $dataset
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* @param string $outputdir
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* @param string $trainedmodeldir
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* @return \stdClass
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*/
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public function evaluate_regression($uniqueid, $maxdeviation, $niterations, \stored_file $dataset,
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$outputdir, $trainedmodeldir) {
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throw new \coding_exception('This predictor does not support regression yet.');
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}
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/**
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* Returns the path to the dataset file.
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*
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* @param \stored_file $file
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* @return string
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*/
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protected function get_file_path(\stored_file $file) {
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// From moodle filesystem to the local file system.
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// This is not ideal, but there is no read access to moodle filesystem files.
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return $file->copy_content_to_temp('core_analytics');
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}
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/**
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* Check that the given package version can be used and return the error status.
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*
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* When evaluating the version, we assume the sematic versioning scheme as described at
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* https://semver.org/.
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*
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* @param string $actual The actual Python package version
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* @param string $required The required version of the package
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* @return int -1 = actual version is too low, 1 = actual version too high, 0 = actual version is ok
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*/
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public static function check_pip_package_version($actual, $required = self::REQUIRED_PIP_PACKAGE_VERSION) {
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if (empty($actual)) {
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return -1;
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}
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if (version_compare($actual, $required, '<')) {
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return -1;
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}
|
|
|
|
$parts = explode('.', $required);
|
|
$requiredapiver = reset($parts);
|
|
|
|
$parts = explode('.', $actual);
|
|
$actualapiver = reset($parts);
|
|
|
|
if ($requiredapiver > 0 || $actualapiver > 1) {
|
|
if (version_compare($actual, $requiredapiver + 1, '>=')) {
|
|
return 1;
|
|
}
|
|
}
|
|
|
|
return 0;
|
|
}
|
|
|
|
/**
|
|
* Executes the specified module.
|
|
*
|
|
* @param string $modulename
|
|
* @param array $params
|
|
* @param string $errorlangstr
|
|
* @return array [0] is the result body and [1] the exit code.
|
|
*/
|
|
protected function exec_command(string $modulename, array $params, string $errorlangstr) {
|
|
|
|
$cmd = $this->pathtopython . ' -m moodlemlbackend.' . $modulename . ' ';
|
|
foreach ($params as $param) {
|
|
$cmd .= escapeshellarg($param) . ' ';
|
|
}
|
|
|
|
if (!PHPUNIT_TEST && CLI_SCRIPT) {
|
|
debugging($cmd, DEBUG_DEVELOPER);
|
|
}
|
|
|
|
$output = null;
|
|
$exitcode = null;
|
|
$result = exec($cmd, $output, $exitcode);
|
|
|
|
if (!$result) {
|
|
throw new \moodle_exception($errorlangstr, 'analytics');
|
|
}
|
|
|
|
return [$result, $exitcode];
|
|
}
|
|
|
|
/**
|
|
* Formats the errors and info in a single info string.
|
|
*
|
|
* @param \stdClass $resultobj
|
|
* @return \stdClass
|
|
*/
|
|
private function format_error_info(\stdClass $resultobj) {
|
|
if (!empty($resultobj->errors)) {
|
|
$errors = $resultobj->errors;
|
|
if (is_array($errors)) {
|
|
$errors = implode(', ', $errors);
|
|
}
|
|
} else if (!empty($resultobj->info)) {
|
|
// Show info if no errors are returned.
|
|
$errors = $resultobj->info;
|
|
if (is_array($errors)) {
|
|
$errors = implode(', ', $errors);
|
|
}
|
|
}
|
|
$resultobj->info = array(get_string('errorpredictionsprocessor', 'analytics', $errors));
|
|
|
|
return $resultobj;
|
|
}
|
|
|
|
/**
|
|
* Returns the url to the python ML server.
|
|
*
|
|
* @param string|null $path
|
|
* @return \moodle_url
|
|
*/
|
|
private function get_server_url(?string $path = null) {
|
|
$protocol = !empty($this->secure) ? 'https' : 'http';
|
|
$url = $protocol . '://' . rtrim($this->host, '/');
|
|
if (!empty($this->port)) {
|
|
$url .= ':' . $this->port;
|
|
}
|
|
|
|
if ($path) {
|
|
$url .= '/' . $path;
|
|
}
|
|
|
|
return new \moodle_url($url);
|
|
}
|
|
|
|
/**
|
|
* Sends a request to the python ML server.
|
|
*
|
|
* @param \moodle_url $url The requested url in the python ML server
|
|
* @param string $method The curl method to use
|
|
* @param array $requestparams Curl request params
|
|
* @param array|null $options Curl request options
|
|
* @return array [0] for the response body and [1] for the http code
|
|
*/
|
|
protected function server_request($url, string $method, array $requestparams, ?array $options = null) {
|
|
|
|
if ($method !== 'post' && $method !== 'get' && $method !== 'download_one') {
|
|
throw new \coding_exception('Incorrect request method provided. Only "get", "post" and "download_one"
|
|
actions are available.');
|
|
}
|
|
|
|
// Connection is allowed to use 'localhost' and other potentially blocked hosts/ports.
|
|
$curl = new \curl(['ignoresecurity' => true]);
|
|
|
|
$authorization = $this->username . ':' . $this->password;
|
|
$curl->setHeader('Authorization: Basic ' . base64_encode($authorization));
|
|
|
|
$responsebody = $curl->{$method}($url, $requestparams, $options);
|
|
|
|
if ($curl->info['http_code'] !== 200) {
|
|
throw new \moodle_exception('errorserver', 'mlbackend_python', '',
|
|
$this->server_error_str($curl->info['http_code'], $responsebody));
|
|
}
|
|
|
|
return [$responsebody, $curl->info['http_code']];
|
|
}
|
|
|
|
/**
|
|
* Adds extra information to results info.
|
|
*
|
|
* @param \stdClass $resultobj
|
|
* @return \stdClass
|
|
*/
|
|
protected function add_extra_result_info(\stdClass $resultobj): \stdClass {
|
|
|
|
if (!empty($resultobj->dir)) {
|
|
$dir = $resultobj->dir . DIRECTORY_SEPARATOR . 'tensor';
|
|
$resultobj->info[] = get_string('tensorboardinfo', 'mlbackend_python', $dir);
|
|
}
|
|
return $resultobj;
|
|
}
|
|
|
|
/**
|
|
* Returns the proper return value for the version checking.
|
|
*
|
|
* @param string $actual Actual moodlemlbackend version
|
|
* @param int $vercheck Version checking result
|
|
* @return true|string Returns true on success, a string detailing the error otherwise
|
|
*/
|
|
private function version_check_return($actual, $vercheck) {
|
|
|
|
if ($vercheck === 0) {
|
|
return true;
|
|
}
|
|
|
|
if ($actual) {
|
|
$a = [
|
|
'installed' => $actual,
|
|
'required' => self::REQUIRED_PIP_PACKAGE_VERSION,
|
|
];
|
|
|
|
if ($vercheck < 0) {
|
|
return get_string('packageinstalledshouldbe', 'mlbackend_python', $a);
|
|
|
|
} else if ($vercheck > 0) {
|
|
return get_string('packageinstalledtoohigh', 'mlbackend_python', $a);
|
|
}
|
|
}
|
|
|
|
if (!$this->useserver) {
|
|
$cmd = "{$this->pathtopython} -m moodlemlbackend.version";
|
|
} else {
|
|
// We can't not know which is the python bin in the python ML server, the most likely
|
|
// value is 'python'.
|
|
$cmd = "python -m moodlemlbackend.version";
|
|
}
|
|
return get_string('pythonpackagenotinstalled', 'mlbackend_python', $cmd);
|
|
}
|
|
|
|
/**
|
|
* Hashes the provided dir as a string.
|
|
*
|
|
* @param string $dir Directory path
|
|
* @return string Hash
|
|
*/
|
|
private function hash_dir(string $dir) {
|
|
return md5($dir);
|
|
}
|
|
|
|
/**
|
|
* Zips the provided directory.
|
|
*
|
|
* @param string $dir Directory path
|
|
* @return string The zip filename
|
|
*/
|
|
private function zip_dir(string $dir) {
|
|
|
|
$ziptmpdir = make_request_directory();
|
|
$ziptmpfile = $ziptmpdir . DIRECTORY_SEPARATOR . 'mlbackend.zip';
|
|
|
|
$files = get_directory_list($dir);
|
|
$zipfiles = [];
|
|
foreach ($files as $file) {
|
|
$fullpath = $dir . DIRECTORY_SEPARATOR . $file;
|
|
// Use the relative path to the file as the path in the zip.
|
|
$zipfiles[$file] = $fullpath;
|
|
}
|
|
|
|
$zip = new \zip_packer();
|
|
if (!$zip->archive_to_pathname($zipfiles, $ziptmpfile)) {
|
|
return false;
|
|
}
|
|
|
|
return $ziptmpfile;
|
|
}
|
|
|
|
/**
|
|
* Error string for httpcode !== 200
|
|
*
|
|
* @param int $httpstatuscode The HTTP status code
|
|
* @param string $responsebody The body of the response
|
|
*/
|
|
private function server_error_str(int $httpstatuscode, string $responsebody): string {
|
|
return 'HTTP status code ' . $httpstatuscode . ': ' . $responsebody;
|
|
}
|
|
}
|