def test(self): test_loader = DataLoader( os.path.join(self.config['global']['folders']['datasets'], self.config['global']['files']['datasets']['test'])) self.model.evaluate_generator( generator=test_loader.flow(batch=self.batch), val_samples=test_loader.size)
def train(self): train_loader = DataLoader( os.path.join(self.config['global']['folders']['datasets'], self.config['global']['files']['datasets']['train'])) validation_loader = DataLoader(os.path.join( self.config['global']['folders']['datasets'], self.config['global']['files']['datasets']['validation']), random=False) h = self.model.fit_generator(train_loader.flow(self.batch), samples_per_epoch=self.samples, nb_epoch=self.epochs, validation_data=validation_loader.flow( self.batch), nb_val_samples=validation_loader.size) self.dump(h.history)