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| """ | |
| { | |
| "document": "", | |
| "question": "", | |
| "long_answer_candidates": ["", "", ""], | |
| "long_answer_candidate_index": 0, | |
| "short_answers": ["", "", ""] | |
| } | |
| """ | |
| import sys | |
| import jsonlines | |
| from datasets import load_dataset | |
| from huggingface_hub import HfApi | |
| def clean(raw, path): | |
| fp = open(path, "a") | |
| writer = jsonlines.Writer(fp) | |
| count = 0 | |
| dataset = [] | |
| for data in raw: | |
| try: | |
| document = "" | |
| startmax, endmax = max(data["document"]["tokens"]["start_byte"]), max(data["document"]["tokens"]["end_byte"]) | |
| start2token, end2start = [-1] * (startmax + 1), [-1] * (endmax + 1) | |
| tokens = data["document"]["tokens"] | |
| for i in range(len(tokens["token"])): | |
| start2token[tokens["start_byte"][i]] = { | |
| "token": tokens["token"][i], | |
| "is_html": tokens["is_html"][i] | |
| } | |
| end2start[tokens["end_byte"][i]] = tokens["start_byte"][i] | |
| if not(tokens["is_html"][i]): | |
| document += tokens["token"][i] + " " | |
| candidates = [] | |
| for i in range(len(data["long_answer_candidates"]["start_byte"])): | |
| candidates.append(" ".join(start2token[j]["token"] for j in range(data["long_answer_candidates"]["start_byte"][i], end2start[data["long_answer_candidates"]["end_byte"][i]]) if (start2token[j] != -1) and not(start2token[j]["is_html"]))) | |
| short_answers = list(map(lambda x: x["text"][0] if x["text"] else "", data["annotations"]["short_answers"])) | |
| dataset.append({ | |
| "id": data["id"], | |
| "document": document, | |
| "question": data["question"]["text"], | |
| "long_answer_candidates": candidates, | |
| "long_answer_candidate_index": data["annotations"]["long_answer"][0]["candidate_index"], | |
| "short_answers": short_answers | |
| }) | |
| except Exception as ex: | |
| # raise ex | |
| print("Exception: " + str(ex)) | |
| if (count + 1) % 1000 == 0: | |
| writer.write_all(dataset) | |
| dataset = [] | |
| print("Done: " + str(count), end="\r") | |
| count += 1 | |
| if dataset: | |
| writer.write_all(dataset) | |
| writer.close() | |
| fp.close() | |
| if __name__ == "__main__": | |
| if len(sys.argv) < 1: | |
| raise AttributeError("Missing required argument: repository id") | |
| repo = sys.argv[1] | |
| api = HfApi() | |
| train = load_dataset("natural_questions", split="train", streaming=True) | |
| train_path = "data/train.jsonl" | |
| clean(train, train_path) | |
| api.upload_file( | |
| path_or_fileobj=train_path, | |
| path_in_repo="raw/train.jsonl", | |
| repo_id=repo, | |
| repo_type="dataset", | |
| ) | |
| val = load_dataset("natural_questions", split="validation", streaming=True) | |
| val_path = "data/validation.jsonl" | |
| clean(val, val_path) | |
| api.upload_file( | |
| path_or_fileobj=val_path, | |
| path_in_repo="raw/validation.jsonl", | |
| repo_id=repo, | |
| repo_type="dataset", | |
| ) |