Added sample set for testing

README.md

@@ -38,6 +38,12 @@ text: str
   The content of the passage.
 ```
 
+#### Sample
+Instead of using the entire data set, you can also download a sample set:
+```python
+collection = load_dataset('trec-cast-2019-multi-turn', 'test_collection_sample')
+```
+
 ### Topics
 You can get the topics as followed:
 ```python

test.py

@@ -1,6 +1,6 @@
 from datasets import load_dataset
 
-collection = load_dataset('trec-cast-2019-multi-turn.py')
+collection = load_dataset('trec-cast-2019-multi-turn.py', 'test_collection_sample')
 collection.items()
 
 qrels = load_dataset('trec-cast-2019-multi-turn.py', 'qrels')

trec-cast-2019-multi-turn.py

@@ -52,7 +52,7 @@ _URLs = {
     'test_collection': {
         'car': "http://trec-car.cs.unh.edu/datareleases/v2.0/paragraphCorpus.v2.0.tar.xz",
         'msmarco': 'https://msmarco.blob.core.windows.net/msmarcoranking/collection.tar.gz',
-    }
+    },
 }
 
 
@@ -80,6 +80,9 @@ class TrecCast2019MultiTurn(datasets.GeneratorBasedBuilder):
         datasets.BuilderConfig(name="test_collection",
                                version=VERSION,
                                description="The test collection will provide the passages of TREC CAR and MSMARCO"),
+        datasets.BuilderConfig(name="test_collection_sample",
+                               version=VERSION,
+                               description="A small sample of 20000 of the test collection passages."),
     ]
 
     # It's not mandatory to have a default configuration. Just use one if it make sense.
@@ -136,7 +139,8 @@ class TrecCast2019MultiTurn(datasets.GeneratorBasedBuilder):
         # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
-        my_urls = _URLs[self.config.name]
+        urlkey = 'test_collection' if self.config.name == 'test_collection_sample' else self.config.name
+        my_urls = _URLs[urlkey]
         downloaded_files = dl_manager.download_and_extract(my_urls)
         return [
             datasets.SplitGenerator(
@@ -181,18 +185,28 @@ class TrecCast2019MultiTurn(datasets.GeneratorBasedBuilder):
                     query = queries[idx]
                     qid = f"{conversation_id}_{str(idx+1)}"
                     yield qid, ({'query': query, 'history': queries[:idx], 'qid': qid})
-        elif split == 'test_collection':
+        elif split == 'test_collection' or split == 'test_collection_sample':
             car_file = file['car'] + "/paragraphCorpus/dedup.articles-paragraphs.cbor"
             msmarco_file = file['msmarco']+"/collection.tsv"
-            for para in read_data.iter_paragraphs(open(car_file, 'rb')):
-                docid = f"CAR_{para.para_id}"
-                yield docid, ({"docno": docid, "text": para.get_text()})
-
+            is_sample = split == 'test_collection_sample'
+            i = 0
+            with open(car_file, 'rb') as f:
+                for para in read_data.iter_paragraphs(f):
+                    docid = f"CAR_{para.para_id}"
+                    yield docid, ({"docno": docid, "text": para.get_text()})
+                    i += 1
+                    if is_sample and i >= 10000:
+                        break
+
+            i = 0
             with open(msmarco_file) as f:
                 msmarco = csv.reader(f, delimiter="\t")
                 for line in msmarco:
                     docid, text = line
                     docid = f"MARCO_{docid}"
                     yield docid, ({"docno": docid, "text": text})
+                    i += 1
+                    if is_sample and i >= 10000:
+                        break
         else:
             raise NotImplementedError(f"'{split}' is not yet implemented")