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| from argparse import ArgumentParser | |
| from json import load | |
| import pathlib | |
| import os | |
| def multi_grep(d, l1, l2, l3): | |
| return d.get(l1, {}).get(l2, {}).get(l3, "[Needs More Information]") | |
| def multi_grep2(d, l1, l2, l3): | |
| return d.get(l1, {}).get(l2, {}).get(l3, ["unknown"]) | |
| def sanitize_md_url(s): | |
| """Strip out MD fragments if they exist.""" | |
| if len(s.split("](")) > 1: | |
| return s.split("](")[1].replace(")", "") | |
| else: | |
| return s | |
| # --- | |
| # annotations_creators: | |
| # - expert-generated | |
| # language_creators: | |
| # - found | |
| # languages: | |
| # - en | |
| # licenses: | |
| # - unknown | |
| # multilinguality: | |
| # - monolingual | |
| # pretty_name: FairytaleQA | |
| # size_categories: | |
| # - 10K<n<100K | |
| # source_datasets: | |
| # - original | |
| # task_categories: | |
| # - question-generation | |
| # task_ids: | |
| # - abstractive-qg | |
| # --- | |
| def construct_preamble(data, name): | |
| pre = "---\n" | |
| pre += "annotations_creators:\n" | |
| # - expert-generated | |
| s = multi_grep(data, "curation", "annotations", "origin") | |
| if s == "[Needs More Information]": | |
| pre += "- unknown\n" | |
| else: | |
| pre += "- " + s.replace(" ", "-") + "\n" | |
| pre += "language_creators:\n- unknown\n" | |
| pre += "languages:" | |
| languages = multi_grep2(data, "overview", "languages", "language_names") | |
| for l in languages: | |
| pre += f"\n- {l}" | |
| pre += "\nlicenses:\n" | |
| s = multi_grep(data, "overview", "languages", "license") | |
| if s == "[Needs More Information]": | |
| pre += "- unknown\n" | |
| else: | |
| pre += "- " + s.split(":")[0] + "\n" | |
| pre += "multilinguality:\n" | |
| if languages == ["unknown"]: | |
| pre += "- unknown" | |
| elif len(languages) == 1: | |
| pre += "- monolingual" | |
| else: | |
| pre += "- multilingual" | |
| # - monolingual | |
| pre += f"\npretty_name: {name}\n" | |
| pre += "size_categories:\n- unknown\n" | |
| pre += "source_datasets:\n- original\n" | |
| pre += "task_categories:\n" | |
| s = multi_grep(data, "overview", "languages", "task") | |
| if s == "[Needs More Information]": | |
| pre += "- unknown\n" | |
| else: | |
| pre += "- " + "-".join(s.lower().split(" ")) + "\n" | |
| # - question-generation | |
| pre += "task_ids:\n- unknown\n" | |
| # - abstractive-qg | |
| pre += "---\n\n" | |
| return pre | |
| ## Table of Contents | |
| # - [Dataset Description](#dataset-description) | |
| # - [Dataset Summary](#dataset-summary) | |
| # - [Supported Tasks](#supported-tasks-and-leaderboards) | |
| # - [Languages](#languages) | |
| # - [Dataset Structure](#dataset-structure) | |
| # - [Data Instances](#data-instances) | |
| # - [Data Fields](#data-instances) | |
| # - [Data Splits](#data-instances) | |
| # - [Dataset Creation](#dataset-creation) | |
| # - [Curation Rationale](#curation-rationale) | |
| # - [Source Data](#source-data) | |
| # - [Annotations](#annotations) | |
| # - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| # - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| # - [Social Impact of Dataset](#social-impact-of-dataset) | |
| # - [Discussion of Biases](#discussion-of-biases) | |
| # - [Other Known Limitations](#other-known-limitations) | |
| # - [Additional Information](#additional-information) | |
| # - [Dataset Curators](#dataset-curators) | |
| # - [Licensing Information](#licensing-information) | |
| # - [Citation Information](#citation-information) | |
| def construct_toc(data): | |
| pass | |
| def construct_links(data): | |
| links = "## Dataset Description\n\n" | |
| s = sanitize_md_url(multi_grep(data, "overview", "where", "website")) | |
| links += f"- **Homepage:** {s}\n" | |
| s = sanitize_md_url(multi_grep(data, "overview", "where", "data-url")) | |
| links += f"- **Repository:** {s}\n" | |
| s = sanitize_md_url(multi_grep(data, "overview", "where", "paper-url")) | |
| links += f"- **Paper:** {s}\n" | |
| s = sanitize_md_url(multi_grep(data, "overview", "where", "leaderboard-url")) | |
| links += f"- **Leaderboard:** {s}\n" | |
| s = multi_grep(data, "overview", "where", "contact-name") | |
| links += f"- **Point of Contact:** {s}\n\n" | |
| return links | |
| def json_to_markdown(filename, original_json_path): | |
| json = load(open(filename)) | |
| original_json = load(open(original_json_path)) | |
| dataset_name = pathlib.Path(original_json_path).stem | |
| preamble = construct_preamble(original_json, dataset_name) | |
| markdown = preamble | |
| markdown += f'# Dataset Card for GEM/{json["name"]}\n\n' | |
| # ToC here. | |
| markdown += construct_links(original_json) | |
| markdown += "### Link to Main Data Card\n\n" | |
| markdown += f'You can find the main data card on the [GEM Website](https://gem-benchmark.com/data_cards/{dataset_name}).\n\n' | |
| markdown += "### Dataset Summary \n\n" | |
| markdown += json['summary'] + '\n\n' | |
| for key in json: | |
| if key not in ('name', 'summary', 'sections'): | |
| markdown += f'#### {key}\n{json[key]}\n\n' | |
| markdown += '\n'.join(section_to_markdown(section) \ | |
| for section in json['sections']) | |
| readme_path = os.path.join(pathlib.Path(original_json_path).parents[0], "README.md") | |
| with open(readme_path, 'w') as f: | |
| f.write(markdown) | |
| def section_to_markdown(section): | |
| markdown = f'{"#" * section["level"]} {section["title"]}\n\n' | |
| markdown += '\n'.join(subsection_to_markdown(subsection) \ | |
| for subsection in section['subsections']) | |
| return markdown + '\n' | |
| def subsection_to_markdown(subsection): | |
| markdown = f'{"#" * subsection["level"]} {subsection["title"]}\n\n' | |
| markdown += '\n'.join(field_to_markdown(field) \ | |
| for field in subsection['fields']) | |
| return markdown + '\n' | |
| def field_to_markdown(field): | |
| markdown = f'{"#" * field["level"]} {field["title"]}\n\n' | |
| if 'flags' in field and 'quick' in field['flags']: | |
| markdown += f'<!-- quick -->\n' | |
| if field.get('info', False): | |
| markdown += f'<!-- info: {field["info"]} -->\n' | |
| if field.get('scope', False): | |
| markdown += f'<!-- scope: {field["scope"]} -->\n' | |
| markdown += field.get('content', '') | |
| return markdown + '\n' | |
| # def main(): | |
| # """Converts JSON output from `reformat_json.py` | |
| # to Markdown input for Data Cards Labs.""" | |
| # args = parse_args() | |
| # for filename in args.input: | |
| # if filename[-5:] == '.json': | |
| # json_to_markdown(filename) | |
| if __name__ == "__main__": | |
| for dataset in os.listdir("../../../GEMv2"): | |
| data_card_path = f"../../../GEMv2/{dataset}/{dataset}.json" | |
| if os.path.exists(data_card_path): | |
| print(f"Now processing {dataset}.") | |
| # This script assumes you have run reformat_json.py | |
| new_path = f"datacards/{dataset}.json" | |
| md_string = json_to_markdown(new_path, data_card_path) | |
| else: | |
| print(f"{dataset} has no data card!") | |