Proyectos de Subversion Moodle

<?php

// This file is part of Moodle - http://moodle.org/

//

// Moodle is free software: you can redistribute it and/or modify

// it under the terms of the GNU General Public License as published by

// the Free Software Foundation, either version 3 of the License, or

// (at your option) any later version.

//

// Moodle is distributed in the hope that it will be useful,

// but WITHOUT ANY WARRANTY; without even the implied warranty of

// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the

// GNU General Public License for more details.

//

// You should have received a copy of the GNU General Public License

// along with Moodle.  If not, see <http://www.gnu.org/licenses/>.

/**

 * Python predictions processor

 *

 * @package   mlbackend_python

 * @copyright 2016 David Monllao {@link http://www.davidmonllao.com}

 * @license   http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later

 */

namespace mlbackend_python;

defined('MOODLE_INTERNAL') || die();

/**

 * Python predictions processor.

 *

 * @package   mlbackend_python

 * @copyright 2016 David Monllao {@link http://www.davidmonllao.com}

 * @license   http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later

 */

class processor implements  \core_analytics\classifier, \core_analytics\regressor, \core_analytics\packable {

    /**

     * The required version of the python package that performs all calculations.

     */

    const REQUIRED_PIP_PACKAGE_VERSION = '3.0.5';

    /**

     * The python package is installed in a server.

     * @var bool

     */

    protected $useserver;

    /**

     * The path to the Python bin.

     *

     * @var string

     */

    protected $pathtopython;

    /**

     * Remote server host

     * @var string

     */

    protected $host;

    /**

     * Remote server port

     * @var int

     */

    protected $port;

    /**

     * Whether to use http or https.

     * @var bool

     */

    protected $secure;

    /**

     * Server username.

     * @var string

     */

    protected $username;

    /**

     * Server password for $this->username.

     * @var string

     */

    protected $password;

    /**

     * The constructor.

     *

     */

    public function __construct() {

        global $CFG;

        $config = get_config('mlbackend_python');

        $this->useserver = !empty($config->useserver);

        if (!$this->useserver) {

            // Set the python location if there is a value.

            if (!empty($CFG->pathtopython)) {

                $this->pathtopython = $CFG->pathtopython;

            }

        } else {

            $this->host = $config->host ?? '';

            $this->port = $config->port ?? '';

            $this->secure = $config->secure ?? false;

            $this->username = $config->username ?? '';

            $this->password = $config->password ?? '';

        }

    }

    /**

     * Is the plugin ready to be used?.

     *

     * @return bool|string Returns true on success, a string detailing the error otherwise

     */

    public function is_ready() {

        if (!$this->useserver) {

            return $this->is_webserver_ready();

        } else {

            return $this->is_python_server_ready();

        }

    }

    /**

     * Checks if the python package is available in the web server executing this script.

     *

     * @return bool|string Returns true on success, a string detailing the error otherwise

     */

    protected function is_webserver_ready() {

        if (empty($this->pathtopython)) {

            $settingurl = new \moodle_url('/admin/settings.php', array('section' => 'systempaths'));

            return get_string('pythonpathnotdefined', 'mlbackend_python', $settingurl->out());

        }

        // Check the installed pip package version.

        $cmd = "{$this->pathtopython} -m moodlemlbackend.version";

        $output = null;

        $exitcode = null;

        // Execute it sending the standard error to $output.

        $result = exec($cmd . ' 2>&1', $output, $exitcode);

        if ($exitcode != 0) {

            return get_string('pythonpackagenotinstalled', 'mlbackend_python', $cmd);

        }

        $vercheck = self::check_pip_package_version($result);

        return $this->version_check_return($result, $vercheck);

    }

    /**

     * Checks if the server can be accessed.

     *

     * @return bool|string True or an error string.

     */

    protected function is_python_server_ready() {

        if (empty($this->host) || empty($this->port) || empty($this->username) || empty($this->password)) {

            return get_string('errornoconfigdata', 'mlbackend_python');

        }

        // Connection is allowed to use 'localhost' and other potentially blocked hosts/ports.

        $curl = new \curl(['ignoresecurity' => true]);

        $responsebody = $curl->get($this->get_server_url('version')->out(false));

        if ($curl->info['http_code'] !== 200) {

            return get_string('errorserver', 'mlbackend_python', $this->server_error_str($curl->info['http_code'], $responsebody));

        }

        $vercheck = self::check_pip_package_version($responsebody);

        return $this->version_check_return($responsebody, $vercheck);

    }

    /**

     * Delete the model version output directory.

     *

     * @throws \moodle_exception

     * @param string $uniqueid

     * @param string $modelversionoutputdir

     * @return null

     */

    public function clear_model($uniqueid, $modelversionoutputdir) {

        if (!$this->useserver) {

            remove_dir($modelversionoutputdir);

        } else {

            // Use the server.

            $url = $this->get_server_url('deletemodel');

            list($responsebody, $httpcode) = $this->server_request($url, 'post', ['uniqueid' => $uniqueid]);

        }

    }

    /**

     * Delete the model output directory.

     *

     * @throws \moodle_exception

     * @param string $modeloutputdir

     * @param string $uniqueid

     * @return null

     */

    public function delete_output_dir($modeloutputdir, $uniqueid) {

        if (!$this->useserver) {

            remove_dir($modeloutputdir);

        } else {

            $url = $this->get_server_url('deletemodel');

            list($responsebody, $httpcode) = $this->server_request($url, 'post', ['uniqueid' => $uniqueid]);

        }

    }

    /**

     * Trains a machine learning algorithm with the provided dataset.

     *

     * @param string $uniqueid

     * @param \stored_file $dataset

     * @param string $outputdir

     * @return \stdClass

     */

    public function train_classification($uniqueid, \stored_file $dataset, $outputdir) {

        if (!$this->useserver) {

            // Use the local file system.

            list($result, $exitcode) = $this->exec_command('training', [$uniqueid, $outputdir,

                $this->get_file_path($dataset)], 'errornopredictresults');

        } else {

            // Use the server.

            $requestparams = ['uniqueid' => $uniqueid, 'dirhash' => $this->hash_dir($outputdir),

                'dataset' => $dataset];

            $url = $this->get_server_url('training');

            list($result, $httpcode) = $this->server_request($url, 'post', $requestparams);

        }

        if (!$resultobj = json_decode($result)) {

            throw new \moodle_exception('errorpredictwrongformat', 'analytics', '', json_last_error_msg());

        }

        if ($resultobj->status != 0) {

            $resultobj = $this->format_error_info($resultobj);

        }

        return $resultobj;

    }

    /**

     * Classifies the provided dataset samples.

     *

     * @param string $uniqueid

     * @param \stored_file $dataset

     * @param string $outputdir

     * @return \stdClass

     */

    public function classify($uniqueid, \stored_file $dataset, $outputdir) {

        if (!$this->useserver) {

            // Use the local file system.

            list($result, $exitcode) = $this->exec_command('prediction', [$uniqueid, $outputdir,

                $this->get_file_path($dataset)], 'errornopredictresults');

        } else {

            // Use the server.

            $requestparams = ['uniqueid' => $uniqueid, 'dirhash' => $this->hash_dir($outputdir),

                'dataset' => $dataset];

            $url = $this->get_server_url('prediction');

            list($result, $httpcode) = $this->server_request($url, 'post', $requestparams);

        }

        if (!$resultobj = json_decode($result)) {

            throw new \moodle_exception('errorpredictwrongformat', 'analytics', '', json_last_error_msg());

        }

        if ($resultobj->status != 0) {

            $resultobj = $this->format_error_info($resultobj);

        }

        return $resultobj;

    }

    /**

     * Evaluates this processor classification model using the provided supervised learning dataset.

     *

     * @param string $uniqueid

     * @param float $maxdeviation

     * @param int $niterations

     * @param \stored_file $dataset

     * @param string $outputdir

     * @param  string $trainedmodeldir

     * @return \stdClass

     */

    public function evaluate_classification($uniqueid, $maxdeviation, $niterations, \stored_file $dataset,

            $outputdir, $trainedmodeldir) {

        global $CFG;

        if (!$this->useserver) {

            // Use the local file system.

            $datasetpath = $this->get_file_path($dataset);

            $params = [$uniqueid, $outputdir, $datasetpath, \core_analytics\model::MIN_SCORE,

                $maxdeviation, $niterations];

            if ($trainedmodeldir) {

                $params[] = $trainedmodeldir;

            }

            list($result, $exitcode) = $this->exec_command('evaluation', $params, 'errornopredictresults');

            if (!$resultobj = json_decode($result)) {

                throw new \moodle_exception('errorpredictwrongformat', 'analytics', '', json_last_error_msg());

            }

        } else {

            // Use the server.

            $requestparams = ['uniqueid' => $uniqueid, 'minscore' => \core_analytics\model::MIN_SCORE,

                'maxdeviation' => $maxdeviation, 'niterations' => $niterations,

                'dirhash' => $this->hash_dir($outputdir), 'dataset' => $dataset];

            if ($trainedmodeldir) {

                $requestparams['trainedmodeldirhash'] = $this->hash_dir($trainedmodeldir);

            }

            $url = $this->get_server_url('evaluation');

            list($result, $httpcode) = $this->server_request($url, 'post', $requestparams);

            if (!$resultobj = json_decode($result)) {

                throw new \moodle_exception('errorpredictwrongformat', 'analytics', '', json_last_error_msg());

            }

            // We need an extra request to get the resources generated during the evaluation process.

            // Directory to temporarly store the evaluation log zip returned by the server.

            $evaluationtmpdir = make_request_directory();

            $evaluationzippath = $evaluationtmpdir . DIRECTORY_SEPARATOR . 'evaluationlog.zip';

            $requestparams = ['uniqueid' => $uniqueid, 'dirhash' => $this->hash_dir($outputdir),

            'runid' => $resultobj->runid];

            $url = $this->get_server_url('evaluationlog');

            list($result, $httpcode) = $this->server_request($url, 'download_one', $requestparams,

                ['filepath' => $evaluationzippath]);

            $rundir = $outputdir . DIRECTORY_SEPARATOR . 'logs' . DIRECTORY_SEPARATOR . $resultobj->runid;

            if (!mkdir($rundir, $CFG->directorypermissions, true)) {

                throw new \moodle_exception('errorexportmodelresult', 'analytics');

            }

            $zip = new \zip_packer();

            $success = $zip->extract_to_pathname($evaluationzippath, $rundir, null, null, true);

            if (!$success) {

                $a = 'The evaluation files can not be exported to ' . $rundir;

                throw new \moodle_exception('errorpredictionsprocessor', 'analytics', '', $a);

            }

            $resultobj->dir = $rundir;

        }

        $resultobj = $this->add_extra_result_info($resultobj);

        return $resultobj;

    }

    /**

     * Exports the machine learning model.

     *

     * @throws \moodle_exception

     * @param  string $uniqueid  The model unique id

     * @param  string $modeldir  The directory that contains the trained model.

     * @return string            The path to the directory that contains the exported model.

     */

    public function export(string $uniqueid, string $modeldir): string {

        $exporttmpdir = make_request_directory();

        if (!$this->useserver) {

            // Use the local file system.

            // We include an exporttmpdir as we want to be sure that the file is not deleted after the

            // python process finishes.

            list($exportdir, $exitcode) = $this->exec_command('export', [$uniqueid, $modeldir, $exporttmpdir],

                'errorexportmodelresult');

            if ($exitcode != 0) {

                throw new \moodle_exception('errorexportmodelresult', 'analytics');

            }

        } else {

            // Use the server.

            $requestparams = ['uniqueid' => $uniqueid, 'dirhash' => $this->hash_dir($modeldir)];

            $exportzippath = $exporttmpdir . DIRECTORY_SEPARATOR . 'export.zip';

            $url = $this->get_server_url('export');

            list($result, $httpcode) = $this->server_request($url, 'download_one', $requestparams,

                ['filepath' => $exportzippath]);

            $exportdir = make_request_directory();

            $zip = new \zip_packer();

            $success = $zip->extract_to_pathname($exportzippath, $exportdir, null, null, true);

            if (!$success) {

                throw new \moodle_exception('errorexportmodelresult', 'analytics');

            }

        }

        return $exportdir;

    }

    /**

     * Imports the provided machine learning model.

     *

     * @param  string $uniqueid The model unique id

     * @param  string $modeldir  The directory that will contain the trained model.

     * @param  string $importdir The directory that contains the files to import.

     * @return bool Success

     */

    public function import(string $uniqueid, string $modeldir, string $importdir): bool {

        if (!$this->useserver) {

            // Use the local file system.

            list($result, $exitcode) = $this->exec_command('import', [$uniqueid, $modeldir, $importdir],

                'errorimportmodelresult');

            if ($exitcode != 0) {

                throw new \moodle_exception('errorimportmodelresult', 'analytics');

            }

        } else {

            // Use the server.

            // Zip the $importdir to send a single file.

            $importzipfile = $this->zip_dir($importdir);

            if (!$importzipfile) {

                // There was an error zipping the directory.

                throw new \moodle_exception('errorimportmodelresult', 'analytics');

            }

            $requestparams = ['uniqueid' => $uniqueid, 'dirhash' => $this->hash_dir($modeldir),

                'importzip' => curl_file_create($importzipfile, null, 'import.zip')];

            $url = $this->get_server_url('import');

            list($result, $httpcode) = $this->server_request($url, 'post', $requestparams);

        }

        return (bool)$result;

    }

    /**

     * Train this processor regression model using the provided supervised learning dataset.

     *

     * @throws new \coding_exception

     * @param string $uniqueid

     * @param \stored_file $dataset

     * @param string $outputdir

     * @return \stdClass

     */

    public function train_regression($uniqueid, \stored_file $dataset, $outputdir) {

        throw new \coding_exception('This predictor does not support regression yet.');

    }

    /**

     * Estimates linear values for the provided dataset samples.

     *

     * @throws new \coding_exception

     * @param string $uniqueid

     * @param \stored_file $dataset

     * @param mixed $outputdir

     * @return void

     */

    public function estimate($uniqueid, \stored_file $dataset, $outputdir) {

        throw new \coding_exception('This predictor does not support regression yet.');

    }

    /**

     * Evaluates this processor regression model using the provided supervised learning dataset.

     *

     * @throws new \coding_exception

     * @param string $uniqueid

     * @param float $maxdeviation

     * @param int $niterations

     * @param \stored_file $dataset

     * @param string $outputdir

     * @param  string $trainedmodeldir

     * @return \stdClass

     */

    public function evaluate_regression($uniqueid, $maxdeviation, $niterations, \stored_file $dataset,

            $outputdir, $trainedmodeldir) {

        throw new \coding_exception('This predictor does not support regression yet.');

    }

    /**

     * Returns the path to the dataset file.

     *

     * @param \stored_file $file

     * @return string

     */

    protected function get_file_path(\stored_file $file) {

        // From moodle filesystem to the local file system.

        // This is not ideal, but there is no read access to moodle filesystem files.

        return $file->copy_content_to_temp('core_analytics');

    }

    /**

     * Check that the given package version can be used and return the error status.

     *

     * When evaluating the version, we assume the sematic versioning scheme as described at

     * https://semver.org/.

     *

     * @param string $actual The actual Python package version

     * @param string $required The required version of the package

     * @return int -1 = actual version is too low, 1 = actual version too high, 0 = actual version is ok

     */

    public static function check_pip_package_version($actual, $required = self::REQUIRED_PIP_PACKAGE_VERSION) {

        if (empty($actual)) {

            return -1;

        }

        if (version_compare($actual, $required, '<')) {

            return -1;

        }

        $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;

    }

}