Added loading script

ciral.py

@@ -0,0 +1,148 @@
+# 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.
+
+
+import csv
+import json
+import os
+
+import datasets
+from collections import defaultdict
+
+
+_CITATION = ""
+
+languages = ['hausa', 'yoruba']
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+This dataset consists of the queries and relevance judgements in the CIRAL test collection. 
+"""
+
+_HOMEPAGE = ""
+
+_LICENSE = ""
+
+_URLS = {
+    lang: {
+        'train': [
+            f'https://huggingface.co/datasets/CIRAL/ciral/resolve/main/ciral-{lang}/qrels/qrels.ciral-{lang}-train.txt',
+            f'https://huggingface.co/datasets/CIRAL/ciral/resolve/main/ciral-{lang}/topics/topics.ciral-{lang}-train.txt',
+        ],
+        'test':[]
+    } for lang in languages
+}
+
+
+def load_queries(_file):
+    if _file is None:
+        return None
+
+    queries = {}
+    with open(_file, encoding="utf-8") as query_file:
+        for line in query_file:
+            id, query = line.strip().split('\t')
+            queries[id] = query
+    return queries
+
+def load_qrels(_file):
+    if _file is None:
+        return None
+
+    qrels = defaultdict(dict)
+    with open(_file, encoding="utf-8") as qrel_file:
+        for line in qrel_file:
+            qid, _, docid, rel = line.strip().split('\t')
+            qrels[qid][docid] = int(rel)
+    return qrels
+
+
+
+class CIRAL(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name=lang,
+            version=VERSION, 
+            description=f"CIRAL data for {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"),
+                    "title": datasets.Value("string"),
+                    "text": datasets.Value("string")}],
+                "negative passages": datasets.features.Sequence({
+                    "docid": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                    "text": 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,  
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        
+        lang = self.config.name
+        downloaded_files = dl_manager.download_and_extract(_URLS[lang])
+        return [
+            datasets.SplitGenerator(
+                name='train',
+                gen_kwargs={
+                    'filepaths': downloaded_files['train'],
+                },
+            ),
+            datasets.SplitGenerator(
+                name='test',
+                gen_kwargs={
+                    'filepaths': downloaded_files['test'],
+                },
+            ),
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepaths, split):
+        lang = self.config.name
+        corpus = datasets.load_dataset('ciral/ciral-corpus', lang)
+        docid2doc = {doc['docid']: (doc['title'], doc['text']) for doc in corpus}
+
+        query_file, qrel_file = (filepaths) if len(filepaths) == 2 else (filepaths[0], None)
+        queries = load_queries(query_file)
+        qrels = load_qrels(qrel_file)
+        for query_id in queries:
+            data = {}
+            data['Query Id'] = query_id
+            data['Query'] = queries[query]
+            data['Judgements'] = [{
+                'docid': docid,
+                'Judgement': judgement,
+                'text': docid2doc[docid]
+            } for docid, judgement in qrels[query_id].items()]
+
+            yield query_id, data