Use logger instead of echo

train.php

@@ -2,6 +2,7 @@
 
 include __DIR__ . '/vendor/autoload.php';
 
+use Rubix\ML\Other\Loggers\Screen;
 use Rubix\ML\Datasets\Labeled;
 use Rubix\ML\PersistentModel;
 use Rubix\ML\Pipeline;
@@ -15,14 +16,15 @@
 use Rubix\ML\NeuralNet\ActivationFunctions\LeakyReLU;
 use Rubix\ML\NeuralNet\Optimizers\Adam;
 use Rubix\ML\Persisters\Filesystem;
-use Rubix\ML\Other\Loggers\Screen;
 use Rubix\ML\Datasets\Unlabeled;
 
 use function Rubix\ML\array_transpose;
 
 ini_set('memory_limit', '-1');
 
-echo 'Loading data into memory ...' . PHP_EOL;
+$logger = new Screen();
+
+$logger->info('Loading data into memory');
 
 $samples = $labels = [];
 
@@ -54,9 +56,7 @@
     new Filesystem('mnist.model', true)
 );
 
-$estimator->setLogger(new Screen());
-
-echo 'Training ...' .  PHP_EOL;
+$estimator->setLogger($logger);
 
 $estimator->train($dataset);
 
@@ -67,7 +67,7 @@
     ->toCSV(['scores', 'losses'])
     ->write('progress.csv');
 
-echo 'Progress saved to progress.csv' . PHP_EOL;
+$logger->info('Progress saved to progress.csv');
 
 if (strtolower(trim(readline('Save this model? (y|[n]): '))) === 'y') {
     $estimator->save();

validate.php

@@ -2,6 +2,7 @@
 
 include __DIR__ . '/vendor/autoload.php';
 
+use Rubix\ML\Other\Loggers\Screen;
 use Rubix\ML\Datasets\Labeled;
 use Rubix\ML\PersistentModel;
 use Rubix\ML\Persisters\Filesystem;
@@ -11,7 +12,9 @@
 
 ini_set('memory_limit', '-1');
 
-echo 'Loading data into memory ...' . PHP_EOL;
+$logger = new Screen();
+
+$logger->info('Loading data into memory');
 
 $samples = $labels = [];
 
@@ -26,7 +29,7 @@
 
 $estimator = PersistentModel::load(new Filesystem('mnist.model'));
 
-echo 'Making predictions ...' . PHP_EOL;
+$logger->info('Making predictions');
 
 $predictions = $estimator->predict($dataset);
 
@@ -41,4 +44,4 @@
 
 $results->toJSON()->write('report.json');
 
-echo 'Report saved to report.json' . PHP_EOL;
+$logger->info('Report saved to report.json');