Update miracl.py

miracl.py

@@ -0,0 +1,142 @@
+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+
+# Lint as: python3
+
+import json
+import datasets
+from collections import defaultdict
+from dataclasses import dataclass
+
+_CITATION = '''
+'''
+
+languages = ['ar', 'bn', 'en', 'es', 'fa', 'fi', 'fr', 'hi', 'id', 'ja', 'ko', 'ru', 'sw', 'te', 'th', 'zh']
+non_surprise_languages = languages
+
+_DESCRIPTION = 'dataset load script for MIRACL'
+
+_DATASET_URLS = {
+    lang: {
+        'train': [
+            f'https://huggingface.co/datasets/miracl/miracl/resolve/main/miracl-v1.0-{lang}/topics/{lang}.topic.train.tsv',
+            f'https://huggingface.co/datasets/miracl/miracl/resolve/main/miracl-v1.0-{lang}/qrels/{lang}.qrels.train.tsv',
+        ],
+        'dev': [
+            f'https://huggingface.co/datasets/miracl/miracl/resolve/main/miracl-v1.0-{lang}/topics/{lang}.topic.dev.tsv',
+            f'https://huggingface.co/datasets/miracl/miracl/resolve/main/miracl-v1.0-{lang}/qrels/{lang}.qrels.dev.tsv',
+        ]
+    } for lang in languages
+}
+
+
+def load_topic(fn):
+    qid2topic = {}
+    with open(fn, encoding="utf-8") as f:
+        for line in f:
+            qid, topic = line.strip().split('\t')
+            qid2topic[qid] = topic
+    return qid2topic
+
+
+def load_qrels(fn):
+    qrels = defaultdict(dict)
+    with open(fn, encoding="utf-8") as f:
+        for line in f:
+            qid, _, docid, rel = line.strip().split('\t')
+            qrels[qid][docid] = int(rel)
+    return qrels
+
+
+class MIRACL(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [datasets.BuilderConfig(
+            version=datasets.Version('1.0.0'),
+            name=lang, description=f'MIRACL dataset in language {lang}.'
+        ) for lang in languages
+    ]
+
+    def _info(self):
+        features = datasets.Features({
+            'query_id': datasets.Value('string'),
+            'query': datasets.Value('string'),
+
+            'positive_passages': [{
+                'docid': datasets.Value('string'),
+                'text': datasets.Value('string'), 'title': datasets.Value('string')
+            }],
+            'negative_passages': [{
+                'docid': datasets.Value('string'),
+                'text': datasets.Value('string'), 'title': datasets.Value('string'),
+            }],
+        })
+
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage='https://project-miracl.github.io',
+            # License for the dataset if available
+            license='',
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        lang = self.config.name
+        downloaded_files = dl_manager.download_and_extract(_DATASET_URLS[lang])
+
+        splits = [
+            datasets.SplitGenerator(
+                name='train',
+                gen_kwargs={
+                    'filepaths': downloaded_files['train'],
+                },
+            ),
+            datasets.SplitGenerator(
+                name='dev',
+                gen_kwargs={
+                    'filepaths': downloaded_files['dev'],
+                },
+            ),
+        ]
+        return splits
+
+    def _generate_examples(self, filepaths):
+        lang = self.config.name
+        miracl_corpus = datasets.load_dataset('miracl/miracl-corpus', lang)['train']
+        docid2doc = {doc['docid']: (doc['title'], doc['text']) for doc in miracl_corpus}
+
+        topic_fn, qrel_fn = filepaths
+        qid2topic = load_topic(topic_fn)
+        qrels = load_qrels(qrel_fn)
+        for qid in qid2topic:
+            data = {}
+            data['query_id'] = qid
+            data['query'] = qid2topic[qid]
+            
+            pos_docids = [docid for docid, rel in qrels[qid].items() if rel == 1]
+            neg_docids = [docid for docid, rel in qrels[qid].items() if rel == 0]
+            data['positive_passages'] = [{
+                'docid': docid, 
+                **dict(zip(['title', 'text'], docid2doc[docid]))
+            } for docid in pos_docids]
+            data['negative_passages'] = [{
+                'docid': docid, 
+                **dict(zip(['title', 'text'], docid2doc[docid]))
+            } for docid in neg_docids]
+            yield qid, data