def create_metrics(self): return SoftmaxMetrics( self.args.blank_symbol, self.args.char_map, self.args.timesteps, self.image_size, uses_original_data=self.args.is_original_fsns, )
curriculum = BabyStepCurriculum( args.dataset_specification, FileBasedDataset, args.blank_label, attributes_to_adjust=attributes_to_adjust, trigger=(args.test_interval, 'iteration'), min_delta=0.1, ) train_dataset, validation_dataset = curriculum.load_dataset(0) # the metrics object calculates the loss metrics = SoftmaxMetrics( args.blank_label, args.char_map, train_dataset.num_timesteps, image_size, area_loss_factor=args.area_factor, aspect_ratio_loss_factor=args.aspect_factor, area_scaling_factor=args.area_scale_factor, uses_original_data=args.is_original_fsns, ) # create the localization net localization_net = FSNSSingleSTNLocalizationNet( args.dropout_ratio, train_dataset.num_timesteps, zoom=args.zoom, use_dropout=args.use_dropout, ) # create the recognition net recognition_net = FSNSRecognitionResnet(