Update megawika.py

megawika.py

@@ -1,105 +1,66 @@
-# Copyright 2020 The HuggingFace Datasets Authors and
-# the Johns Hopkins University (JHU) Human Language Technology
-# Center of Excellence.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""
-This file provides a HuggingFace dataset loader implementation for
-the JHU/HLTCOE MegaWika dataset.
-MegaWika is a multi- and crosslingual text dataset containing 30 million
-Wikipedia passages with their scraped and cleaned web citations. The
-passages span 50 Wikipedias in 50 languages, and the articles in which
-the passages were originally embedded are included for convenience. Where
-a Wikipedia passage is in a non-English language, an automated English
-translation is provided. Furthermore, nearly 130 million English
-question/answer pairs were extracted from the passages, and FrameNet events
-occurring in the passages are detected using the LOME FrameNet parser.
-"""
-
-
-import csv
+import datasets
 import json
-import os
-import re
-import pathlib
-from pathlib import Path
 import yaml
-from ast import literal_eval
-
-import datasets
-
-# import gzip
-# try:
-#     import lzma as xz
-# except ImportError:
-#     import pylzma as xz
+import urllib.request
 
+_DESCRIPTION = """\
+MegaWika is a multi- and crosslingual text dataset containing 30 million
+Wikipedia passages with their scraped and cleaned web citations. The
+passages span 50 Wikipedias in 50 languages, and the articles in which
+the passages were originally embedded are included for convenience."""
 
-# TODO: Add BibTeX citation
-# Find for instance the citation on arxiv or on the dataset repo/website
 _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
-  },
+  author={Barham, Samuel and Weller, Orion and others},
   journal={INSERT ARXIV PREPRINT ID HERE},
   year={2023}
-}
-"""
-
-# TODO: Add description of the dataset here
-# You can copy an official description
-_DESCRIPTION = """\
-MegaWika is a multi- and crosslingual text dataset containing 30 million
-Wikipedia passages with their scraped and cleaned web citations. The
-passages span 50 Wikipedias in 50 languages, and the articles in which
-the passages were originally embedded are included for convenience. Where
-a Wikipedia passage is in a non-English language, an automated English
-translation is provided. Furthermore, nearly 130 million English
-question/answer pairs were extracted from the passages, and FrameNet events
-occurring in the passages are detected using the LOME FrameNet parser.
-"""
+}"""
 
 _HOMEPAGE = "https://huggingface.co/datasets/conceptofmind/MegaWika"
-
 _LICENSE = "cc-by-sa-4.0"
 
-_URL = "https://huggingface.co/datasets/conceptofmind/MegaWika"
-
-# Load the file paths for all the splits (per language currently)
-
+# Load the file paths for all the splits
 file_list_url = "https://huggingface.co/datasets/conceptofmind/MegaWika/raw/main/files.yml"
 
-import urllib.request
-with urllib.request.urlopen(file_list_url) as f:
-    try:
-        fnames = yaml.safe_load(f)
-    except yaml.YAMLError as exc:
-        print("Error loading the file paths for the dataset splits. Aborting.")
-        exit(1)
-
-_DATA_URL = fnames['fnames']
-
-_VARIANTS = ["all"] + list(_DATA_URL.keys())
-
+def get_data_urls():
+    with urllib.request.urlopen(file_list_url) as f:
+        try:
+            fnames = yaml.safe_load(f)
+            return fnames['fnames']
+        except yaml.YAMLError as exc:
+            print("Error loading the file paths for the dataset splits. Aborting.")
+            return {}
+
+class MegaWikaConfig(datasets.BuilderConfig):
+    """BuilderConfig for MegaWika."""
+
+    def __init__(self, language=None, **kwargs):
+        """BuilderConfig for MegaWika.
+        
+        Args:
+          language: The language of the dataset split
+          **kwargs: Keyword arguments forwarded to super.
+        """
+        super(MegaWikaConfig, self).__init__(**kwargs)
+        self.language = language
 
 class MegaWika(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [datasets.BuilderConfig(name) for name in _VARIANTS]
+    """MegaWika dataset."""
+    
+    # Get available languages from the data URLs
+    _DATA_URL = get_data_urls()
+    BUILDER_CONFIGS = [
+        MegaWikaConfig(
+            name=lang if lang != "all" else "default",
+            language=lang,
+            version=datasets.Version("1.0.0"),
+            description=f"MegaWika {lang} configuration"
+        )
+        for lang in ["all"] + list(_DATA_URL.keys())
+    ]
+    
+    DEFAULT_CONFIG_NAME = "default"  # For the "all" configuration
 
     def _info(self):
         return datasets.DatasetInfo(
@@ -111,17 +72,13 @@ class MegaWika(datasets.GeneratorBasedBuilder):
                     "entries": datasets.features.Sequence(
                         {
                             "id": datasets.Value("string"),
-
-                            # Wiki passage
                             "passage": {
                                 "text": [datasets.Value("string")],
                                 "parse": datasets.Value("string"),
                                 "en_tokens": [datasets.Value("string")],
                                 "lang_tokens": [datasets.Value("string")],
-                                "en_lang_token_map": [[datasets.Value("int32")]] # list of pairs
+                                "en_lang_token_map": [[datasets.Value("int32")]]
                             },
-
-                            # MT
                             "mt": {
                                 "original": datasets.Value("string"),
                                 "original_sents": [datasets.Value("string")],
@@ -130,13 +87,9 @@ class MegaWika(datasets.GeneratorBasedBuilder):
                                 "translation_probs": [[datasets.Value("string")]],
                                 "repetitious_translation": datasets.Value("bool")
                             },
-
-                            # Source document
                             "source_lang": datasets.Value("string"),
                             "source_url": datasets.Value("string"),
                             "source_text": datasets.Value("string"),
-                            
-                            # Question/answer pairs
                             "qa_pairs": datasets.Sequence(
                                 {
                                     "question": datasets.Value("string"),
@@ -148,10 +101,10 @@ class MegaWika(datasets.GeneratorBasedBuilder):
                                             "argument": datasets.Value("string")
                                         }
                                     ),
-                                    "en_matches_in_source": [[datasets.Value("int32")]], # list of pair of int indices
-                                    "en_match_in_passage": [datasets.Value("int32")], # pair of int indices
-                                    "lang_matches_in_source": [[datasets.Value("int32")]], # list of pair of int indices
-                                    "lang_match_in_passage": [datasets.Value("int32")], # pair of int indices
+                                    "en_matches_in_source": [[datasets.Value("int32")]],
+                                    "en_match_in_passage": [datasets.Value("int32")],
+                                    "lang_matches_in_source": [[datasets.Value("int32")]],
+                                    "lang_match_in_passage": [datasets.Value("int32")],
                                     "passage": [datasets.Value("string")],
                                     "en_answer_tokens": [datasets.Value("string")],
                                     "match_disambiguated_question": datasets.Value("string"),
@@ -162,45 +115,42 @@ class MegaWika(datasets.GeneratorBasedBuilder):
                 }
             ),
             supervised_keys=None,
-            homepage=_URL,
+            homepage=_HOMEPAGE,
             citation=_CITATION,
+            license=_LICENSE
         )
 
     def _split_generators(self, dl_manager):
-        if self.config.name == "all":
-            data_sources = _DATA_URL
+        """Returns SplitGenerators."""
+        if self.config.language == "all":
+            data_sources = self._DATA_URL
         else:
-            data_sources = {self.config.name: _DATA_URL[self.config.name]}
+            data_sources = {self.config.language: self._DATA_URL[self.config.language]}
 
         return [
             datasets.SplitGenerator(
-                name=lang,
+                name=datasets.Split.TRAIN,  # Using TRAIN as default split
                 gen_kwargs={
                     "filepaths": dl_manager.download(data_sources[lang])
                 }
             )
-            for lang
-            in data_sources
+            for lang in data_sources
         ]
 
     def _get_qa_pair_list_features(self, qa_pair, feature_name):
-        res = []
-
-        if feature_name in qa_pair:
-            if qa_pair[feature_name]:
-                return qa_pair[feature_name]  
-        else:
-            if feature_name.startswith('en'):
-                feature_name = '_'.join(feature_name.split('_')[1:])
-                return self._get_qa_pair_list_features(qa_pair, feature_name)
+        """Helper method 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 []
 
-        return res
-    
     def _generate_examples(self, filepaths):
-        """This function returns the examples in the raw (text) form by iterating on all the files."""
+        """Yields examples."""
         id_ = 0
         for filepath in filepaths:
-            # logger.info("Generating examples from = %s", filepath)
             try:
                 with open(filepath, "r", encoding="utf-8") as f:
                     for line in f:
@@ -216,19 +166,11 @@ class MegaWika(datasets.GeneratorBasedBuilder):
                                             "passage": {
                                                 "text": entry['passage'].get("text", []),
                                                 "parse": json.dumps(entry['passage'].get("parse", [{}])),
-                                                "en_tokens": list(entry['passage'].get(
-                                                    "en_tokens",
-                                                    {
-                                                        token: token
-                                                        for tokens in entry['passage'].get("tokens", {})
-                                                        for token in tokens
-                                                    }
-                                                ).values()),
+                                                "en_tokens": list(entry['passage'].get("en_tokens", {}).values()),
                                                 "lang_tokens": list(entry['passage'].get("lang_tokens", {}).values()),
                                                 "en_lang_token_map": [
                                                     (int(item[0]), int(item[1]))
-                                                    for item
-                                                    in entry['passage'].get("en_lang_token_map", {}).items()
+                                                    for item in entry['passage'].get("en_lang_token_map", {}).items()
                                                 ]
                                             },
                                             "mt": {
@@ -237,7 +179,7 @@ class MegaWika(datasets.GeneratorBasedBuilder):
                                                 "translation": entry.get("translation", ""),
                                                 "translation_sents": entry.get("translation_sents", []),
                                                 "translation_probs": entry.get("translation_probs", [[]]),
-                                                "repetitious_translation": entry.get("repetitious_translation", None)
+                                                "repetitious_translation": entry.get("repetitious_translation", False)
                                             },
                                             "source_lang": entry.get("source_lang", ""),
                                             "source_url": entry.get("source_url", ""),
@@ -248,34 +190,20 @@ class MegaWika(datasets.GeneratorBasedBuilder):
                                                     "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"), 
+                                                    "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 qa_pair in entry.get('qa_pairs', [])
                                             ]
                                         }
-                                        for entry
-                                        in example.get("entries", [])
+                                        for entry in example.get("entries", [])
                                     ]
                                 }
                                 id_ += 1
-            except:
-                print("Error reading file:", filepath)
-
-
-
-# "entries": datasets.features.Sequence(
-#     {
-#         "qa_pairs": datasets.Sequence(
-#             {
-#                 "question": datasets.Value("string"),
-#                 "answer": datasets.Value("string"),
-#             }
-#         )
-#     }
+            except Exception as e:
+                print(f"Error reading file {filepath}: {str(e)}")