import json import datasets import os logger = datasets.logging.get_logger(__name__) class Dataset(datasets.GeneratorBasedBuilder): def _info(self): return datasets.DatasetInfo( features=datasets.Features({ "images": datasets.Sequence(datasets.Image()), "id": datasets.Value("int32"), "conversations": datasets.Sequence(datasets.Features({ "from": datasets.Value("string"), "value": datasets.Value("string") })) }) ) def _split_generators(self, dl_manager: datasets.DownloadManager): dl_manager.download_config.token = True dl_manager.download_config.num_proc = 10 base_url = "https://huggingface.co/datasets/empower-dev-staging/cord/resolve/main/data" train_image_files = dl_manager.download_and_extract( f"{base_url}/train/train.tar.gz" ) test_image_files = dl_manager.download_and_extract( f"{base_url}/test/test.tar.gz" ) image_files = train_image_files + test_image_files image_file_to_full_path_mapping = dict([ ('images/' + '/'.join(image_file.split('/')[-2:]), image_file) for image_file in dl_manager.iter_files(image_files) ]) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "filepath": dl_manager.download_and_extract( f"{base_url}/train.jsonl"), "image_file_to_full_path_mapping": image_file_to_full_path_mapping }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "filepath": dl_manager.download_and_extract( f"{base_url}/test.jsonl"), "image_file_to_full_path_mapping": image_file_to_full_path_mapping }, ), ] def _get_step_info(self, item): first_image_path = item['images'][0] folder = '/'.join(first_image_path.split('/')[-2:-1]) task = folder.split('-')[0] step = folder.split('-')[1].split('_') step_number = step[0] retry_index = int(step[1]) return { "task_name": task, "step_name": f"{task}-{step_number}", "retry_index": retry_index } def _generate_examples(self, filepath, image_file_to_full_path_mapping): with open(filepath, "r") as f: lines = f.readlines() items = [] step_name_to_retry_count = {} for id, line in enumerate(lines): item = json.loads(line) if len(json.loads(item["conversations"][1]["value"])["actions"]) == 0: continue items.append(item) step_name = self._get_step_info(item)["step_name"] if step_name not in step_name_to_retry_count: step_name_to_retry_count[step_name] = 0 step_name_to_retry_count[step_name] += 1 for id, item in enumerate(items): step_info = self._get_step_info(item) yield id, { "images": [ image_file_to_full_path_mapping[image] for image in item["images"] ], "conversations": item["conversations"], "length": item["length"], "task_name": step_info["task_name"], "step_name": step_info["step_name"], "has_retry": step_name_to_retry_count[step_info['step_name']] > 1, "retry_index": step_info["retry_index"], "total_retries": step_name_to_retry_count[step_info['step_name']] }