Delete megawika.py

megawika.py

@@ -1,197 +0,0 @@
-"""MegaWika dataset loading script for HuggingFace Datasets."""
-
-import csv
-import json
-import os
-import re
-import pathlib
-from pathlib import Path
-import yaml
-from ast import literal_eval
-import urllib.request
-import datasets
-
-_CITATION = """\
-@article{barham2023megawika,
-  title={MegaWika: Millions of reports and their sources across 50 diverse languages},
-  author={Barham, Samuel and Weller, Orion and
-          Yuan, Michelle and Murray, Kenton and
-          Yarmohammadi, Mahsa and Jiang, Zhengping and
-          Vashishtha, Siddharth and Martin, Alexander and
-          Liu, Anqi and White, Aaron Steven and
-          Boyd-Graber, Jordan and Van Durme, Benjamin
-  },
-  journal={INSERT ARXIV PREPRINT ID HERE},
-  year={2023}
-}
-"""
-
-_DESCRIPTION = """\
-MegaWika is a multi- and crosslingual text dataset containing 30 million
-Wikipedia passages with their scraped and cleaned web citations across 50 languages.
-"""
-
-_HOMEPAGE = "https://huggingface.co/datasets/DataProvenanceInitiative/Megawika_subset"
-_LICENSE = "cc-by-sa-4.0"
-_URL = "https://huggingface.co/datasets/DataProvenanceInitiative/Megawika_subset"
-
-def load_file_paths():
-    """Load and parse the files.yml containing dataset file paths.
-    
-    Expected YAML structure:
-    en:
-        - https://huggingface.co/datasets/DataProvenanceInitiative/Megawika_subset/resolve/main/en/en-00000-of-06154.jsonl
-    fr:
-        - https://huggingface.co/datasets/DataProvenanceInitiative/Megawika_subset/resolve/main/fr/fr-00000-of-00123.jsonl
-    ...
-    
-    Returns:
-        dict: Dictionary mapping language codes to lists of file URLs
-    """
-    file_list_url = "https://huggingface.co/datasets/DataProvenanceInitiative/Megawika_subset/raw/main/files.yml"
-    try:
-        with urllib.request.urlopen(file_list_url) as f:
-            # Direct YAML parsing - the structure is already in the correct format
-            return yaml.safe_load(f)
-    except (yaml.YAMLError, urllib.error.URLError) as exc:
-        print(f"Error loading dataset file paths: {exc}")
-        return {}
-
-class MegaWikaConfig(datasets.BuilderConfig):
-    """BuilderConfig for MegaWika."""
-
-    def __init__(self, language=None, **kwargs):
-        """BuilderConfig for MegaWika.
-        
-        Args:
-            language: Language identifier for the dataset split
-            **kwargs: Keyword arguments forwarded to super.
-        """
-        super().__init__(**kwargs)
-        self.language = language
-
-class MegaWika(datasets.GeneratorBasedBuilder):
-    """MegaWika dataset."""
-    
-    VERSION = datasets.Version("1.0.0")
-    
-    # Load available languages directly from YAML structure
-    LANGUAGES = list(load_file_paths().keys())
-    
-    BUILDER_CONFIGS = ([
-        MegaWikaConfig(
-            name="all",
-            language=None,
-            version=VERSION,
-            description="Complete MegaWika dataset across all languages",
-        )
-    ] + [
-        MegaWikaConfig(
-            name=lang,
-            language=lang,
-            version=VERSION,
-            description=f"MegaWika dataset for {lang} language",
-        )
-        for lang in LANGUAGES
-    ])
-    
-    DEFAULT_CONFIG_NAME = "all"
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # Load the file paths afresh to ensure we have the latest data
-        data_sources = load_file_paths()
-        
-        if self.config.name == "all":
-            # Process all languages
-            selected_sources = data_sources
-        else:
-            # Process single language
-            if self.config.name not in data_sources:
-                raise ValueError(
-                    f"Language '{self.config.name}' not found in available languages: {list(data_sources.keys())}"
-                )
-            selected_sources = {self.config.name: data_sources[self.config.name]}
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepaths": dl_manager.download(urls),
-                    "language": lang
-                }
-            )
-            for lang, urls in selected_sources.items()
-        ]
-
-    def _get_qa_pair_list_features(self, qa_pair, feature_name):
-        """Helper function to extract QA pair features."""
-        if feature_name in qa_pair and qa_pair[feature_name]:
-            return qa_pair[feature_name]
-        elif feature_name.startswith('en'):
-            base_feature = '_'.join(feature_name.split('_')[1:])
-            if base_feature in qa_pair and qa_pair[base_feature]:
-                return qa_pair[base_feature]
-        return []
-
-    def _generate_examples(self, filepaths, language):
-        """Yields examples."""
-        _id = 0
-        for filepath in filepaths:
-            try:
-                with open(filepath, "r", encoding="utf-8") as f:
-                    for line in f:
-                        if line.strip():
-                            example = json.loads(line)
-                            if isinstance(example, dict):
-                                yield _id, {
-                                    "article_title": example.get("article_title", ""),
-                                    "article_text": example.get("article_text", ""),
-                                    "entries": [
-                                        {
-                                            "id": entry.get("id", "").lower(),
-                                            "passage": {
-                                                "text": entry['passage'].get("text", []),
-                                                "parse": json.dumps(entry['passage'].get("parse", [{}])),
-                                                "en_tokens": list(entry['passage'].get("en_tokens", {}).values()),
-                                                "lang_tokens": list(entry['passage'].get("lang_tokens", {}).values()),
-                                                "en_lang_token_map": [
-                                                    [int(k), int(v)] for k, v in 
-                                                    entry['passage'].get("en_lang_token_map", {}).items()
-                                                ]
-                                            },
-                                            "mt": {
-                                                "original": entry.get("original", ""),
-                                                "original_sents": entry.get("original_sents", []),
-                                                "translation": entry.get("translation", ""),
-                                                "translation_sents": entry.get("translation_sents", []),
-                                                "translation_probs": entry.get("translation_probs", [[]]),
-                                                "repetitious_translation": entry.get("repetitious_translation", False)
-                                            },
-                                            "source_lang": entry.get("source_lang", ""),
-                                            "source_url": entry.get("source_url", ""),
-                                            "source_text": entry.get("source_text", ""),
-                                            "qa_pairs": [
-                                                {
-                                                    "question": qa_pair.get('question', ""),
-                                                    "en_answer": qa_pair.get('en_answer', qa_pair.get('answer', "")),
-                                                    'lang_answer': qa_pair.get('lang_answer', ''),
-                                                    'frames': qa_pair.get('frames', []),
-                                                    "en_matches_in_source": self._get_qa_pair_list_features(qa_pair, "en_matches_in_source"),
-                                                    "en_match_in_passage": self._get_qa_pair_list_features(qa_pair, "en_match_in_passage"),
-                                                    "lang_matches_in_source": self._get_qa_pair_list_features(qa_pair, "lang_matches_in_source"),
-                                                    "lang_match_in_passage": self._get_qa_pair_list_features(qa_pair, "lang_match_in_passage"),
-                                                    "passage": qa_pair.get('passage', []),
-                                                    "en_answer_tokens": qa_pair.get('en_answer_tokens', qa_pair.get('answer_tokens', [])),
-                                                    "match_disambiguated_question": qa_pair.get('match_disambiguated_question', ""),
-                                                }
-                                                for qa_pair in entry.get('qa_pairs', [])
-                                            ]
-                                        }
-                                        for entry in example.get("entries", [])
-                                    ]
-                                }
-                                _id += 1
-            except Exception as e:
-                print(f"Error reading file {filepath}: {str(e)}")
-                continue