Update megawika.py

megawika.py

@@ -1,66 +1,106 @@
-import datasets
-import json
-import yaml
-import urllib.request
+# 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.
 
-_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."""
+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 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
+
+
+# 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 others},
+  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}
-}"""
+}
+"""
+
+# 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/hltcoe/megawika"
 
-_HOMEPAGE = "https://huggingface.co/datasets/conceptofmind/MegaWika"
 _LICENSE = "cc-by-sa-4.0"
 
-# Load the file paths for all the splits
-file_list_url = "https://huggingface.co/datasets/conceptofmind/MegaWika/raw/main/files.yml"
-
-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
+_URL = "https://huggingface.co/datasets/hltcoe/megawika"
+
+# Load the file paths for all the splits (per language currently)
+
+file_list_url = "https://huggingface.co/datasets/hltcoe/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())
+
 
 class MegaWika(datasets.GeneratorBasedBuilder):
-    """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
+    BUILDER_CONFIGS = [datasets.BuilderConfig(name) for name in _VARIANTS]
 
     def _info(self):
         return datasets.DatasetInfo(
@@ -72,24 +112,32 @@ 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")]]
+                                "en_lang_token_map": [[datasets.Value("int32")]] # list of pairs
                             },
+
+                            # MT
                             "mt": {
                                 "original": datasets.Value("string"),
                                 "original_sents": [datasets.Value("string")],
                                 "translation": datasets.Value("string"),
                                 "translation_sents": [datasets.Value("string")],
-                                "translation_probs": [[datasets.Value("string")]],
+                                "translation_probs": [[datasets.Value("float32")]],
                                 "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"),
@@ -101,10 +149,10 @@ class MegaWika(datasets.GeneratorBasedBuilder):
                                             "argument": datasets.Value("string")
                                         }
                                     ),
-                                    "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")],
+                                    "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
                                     "passage": [datasets.Value("string")],
                                     "en_answer_tokens": [datasets.Value("string")],
                                     "match_disambiguated_question": datasets.Value("string"),
@@ -115,42 +163,45 @@ class MegaWika(datasets.GeneratorBasedBuilder):
                 }
             ),
             supervised_keys=None,
-            homepage=_HOMEPAGE,
+            homepage=_URL,
             citation=_CITATION,
-            license=_LICENSE
         )
 
     def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        if self.config.language == "all":
-            data_sources = self._DATA_URL
+        if self.config.name == "all":
+            data_sources = _DATA_URL
         else:
-            data_sources = {self.config.language: self._DATA_URL[self.config.language]}
+            data_sources = {self.config.name: _DATA_URL[self.config.name]}
 
         return [
             datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,  # Using TRAIN as default split
+                name=lang,
                 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):
-        """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 []
+        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)
 
+        return res
+    
     def _generate_examples(self, filepaths):
-        """Yields examples."""
+        """This function returns the examples in the raw (text) form by iterating on all the files."""
         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:
@@ -166,11 +217,19 @@ 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", {}).values()),
+                                                "en_tokens": list(entry['passage'].get(
+                                                    "en_tokens",
+                                                    {
+                                                        token: token
+                                                        for tokens in entry['passage'].get("tokens", {})
+                                                        for token in 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": {
@@ -179,7 +238,7 @@ 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", False)
+                                                "repetitious_translation": entry.get("repetitious_translation", None)
                                             },
                                             "source_lang": entry.get("source_lang", ""),
                                             "source_url": entry.get("source_url", ""),
@@ -190,20 +249,34 @@ 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 Exception as e:
-                print(f"Error reading file {filepath}: {str(e)}")
+            except:
+                print("Error reading file:", filepath)
+
+
+
+# "entries": datasets.features.Sequence(
+#     {
+#         "qa_pairs": datasets.Sequence(
+#             {
+#                 "question": datasets.Value("string"),
+#                 "answer": datasets.Value("string"),
+#             }
+#         )
+#     }