| """Wikipedia snippets in parquet format""" | |
| import math | |
| import pyarrow.parquet as pq | |
| import datasets | |
| logger = datasets.logging.get_logger(__name__) | |
| _CITATION = """\ | |
| @ONLINE {wikidump, | |
| author = {Wikimedia Foundation}, | |
| title = {Wikimedia Downloads}, | |
| url = {https://dumps.wikimedia.org} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| The dataset was built from the Wikipedia dump (https://dumps.wikimedia.org/). | |
| Each example contains the content of one full Wikipedia article with cleaning to strip | |
| markdown and unwanted sections (references, etc.). | |
| """ | |
| _LICENSE = ( | |
| "This work is licensed under the Creative Commons Attribution-ShareAlike " | |
| "3.0 Unported License. To view a copy of this license, visit " | |
| "http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to " | |
| "Creative Commons, PO Box 1866, Mountain View, CA 94042, USA." | |
| ) | |
| class WikipediaSnippetsStreamed(datasets.GeneratorBasedBuilder): | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "wiki_id": datasets.Value("string"), | |
| "start_paragraph": datasets.Value("int32"), | |
| "start_character": datasets.Value("int32"), | |
| "end_paragraph": datasets.Value("int32"), | |
| "end_character": datasets.Value("int32"), | |
| "article_title": datasets.Value("string"), | |
| "section_title": datasets.Value("string"), | |
| "passage_text": datasets.Value("string"), | |
| } | |
| ), | |
| supervised_keys=None, | |
| homepage="https://dumps.wikimedia.org", | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| url = "https://storage.googleapis.com/huggingface-nlp/cache/datasets/wiki40b/en/1.1.0/wiki40b-train.parquet" | |
| downloaded_file = dl_manager.download(url) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}), | |
| ] | |
| def wiki40b_article_snippets(self, article, passage_len=100, overlap=0): | |
| paragraphs = article["text"].split("\n") | |
| aticle_idx = paragraphs.index("_START_ARTICLE_") + 1 | |
| article_title = paragraphs[aticle_idx] if aticle_idx < len(paragraphs) else "" | |
| section_indices = [i + 1 for i, par in enumerate(paragraphs[:-1]) if par == "_START_SECTION_"] | |
| par_tabs = [par.split(" ") for par in paragraphs] | |
| word_map = [ | |
| (i, len(" ".join(par[:j])), w) | |
| for i, par in enumerate(par_tabs) | |
| if not par[0].startswith("_START_") | |
| for j, w in enumerate(par) | |
| if i > 0 | |
| ] | |
| step_size = passage_len - overlap | |
| passages = [] | |
| for i in range(math.ceil(len(word_map) / step_size)): | |
| pre_toks = word_map[i * step_size: i * step_size + passage_len] | |
| start_section_id = max([0] + [j for j in section_indices if j <= pre_toks[0][0]]) | |
| section_ids = [j for j in section_indices if j >= start_section_id and j <= pre_toks[-1][0]] | |
| section_ids = section_ids if len(section_ids) > 0 else [0] | |
| passage_text = " ".join([w for p_id, s_id, w in pre_toks]) | |
| passages += [ | |
| { | |
| "article_title": article_title, | |
| "section_title": " & ".join([paragraphs[j] for j in section_ids]), | |
| "wiki_id": article["wikidata_id"], | |
| "start_paragraph": pre_toks[0][0], | |
| "start_character": pre_toks[0][1], | |
| "end_paragraph": pre_toks[-1][0], | |
| "end_character": pre_toks[-1][1] + len(pre_toks[-1][2]) + 1, | |
| "passage_text": passage_text.replace("_NEWLINE_", "\n"), | |
| } | |
| ] | |
| return passages | |
| def _generate_examples(self, filepath): | |
| logger.info("generating examples from = %s", filepath) | |
| passage_counter = 0 | |
| with open(filepath, "rb") as f: | |
| pf = pq.ParquetFile(f) | |
| for i in range(pf.num_row_groups): | |
| batch_table_dict = pf.read_row_group(i).to_pydict() | |
| for idx, article_text in enumerate(batch_table_dict["text"]): | |
| article = {"text": article_text, "wikidata_id": batch_table_dict["wikidata_id"][idx]} | |
| passages = self.wiki40b_article_snippets(article) | |
| for passage in passages: | |
| yield ++passage_counter, passage | |