question_generator.input_shape = image_embedding_dim # Calculate image features and store them if save is True obj_dir = os.path.join('data', dataset, 'obj') if not os.path.exists(obj_dir): os.makedirs(obj_dir) train_imagefeat_dict_name = os.path.join(obj_dir, 'train_imagefeat_dict.pkl') test_imagefeat_dict_name = os.path.join(obj_dir, 'test_imagefeat_dict.pkl') dev_imagefeat_dict_name = os.path.join(obj_dir, 'dev_imagefeat_dict.pkl') if os.path.exists(test_imagefeat_dict_name): datasets.test_image_id_imagefeat_dict = load_obj( test_imagefeat_dict_name) datasets.load_test_data() # Set this variable to True if you want to save the image features save = False if save: save_obj(datasets.test_image_id_imagefeat_dict, test_imagefeat_dict_name) if is_training == 'YES': if os.path.exists(train_imagefeat_dict_name): datasets.train_image_id_imagefeat_dict = load_obj( train_imagefeat_dict_name) # Validation part of pipeline is commented out to speedup training process # if os.path.exists(dev_imagefeat_dict_name):