Added download sizes and implemented generate_examples for 'test_collection'

trec-cast-2019-multi-turn.py

@@ -49,17 +49,13 @@ _URLs = {
     'topics': _URL+"cast2019_test_annotated.tsv",
     'qrels': _URL+"2019qrels.txt",
     'test_collection': {
-        'msmarco': 'https://msmarco.blob.core.windows.net/msmarcoranking/collection.tar.gz',
         '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',
     }
 }
 
 
 class TrecCast2019MultiTurn(datasets.GeneratorBasedBuilder):
-    """
-
-    """
-
     VERSION = datasets.Version("1.0.0")
 
     # This is an example of a dataset with multiple configurations.
@@ -90,24 +86,29 @@ class TrecCast2019MultiTurn(datasets.GeneratorBasedBuilder):
 
     def _info(self):
         # This is the name of the configuration selected in BUILDER_CONFIGS above
+        download_size = None
         if self.config.name == "topics":
             features = datasets.Features({
                 "qid": datasets.Value("string"),
                 "history": datasets.features.Sequence(feature=datasets.Value('string')),
                 "query": datasets.Value("string"),
             })
+            download_size = 1138032
         elif self.config.name == "qrels":
             features = datasets.Features({
                 "qid": datasets.Value("string"),
                 "qrels": datasets.features.Sequence(feature=datasets.Features({
                     'docno': datasets.Value("string"),
-                    'rank': datasets.Value("string"),
+                    'relevance': datasets.Value("string"),
                 })),
             })
+            download_size = 8010
         elif self.config.name == 'test_collection':
             features = datasets.Features({
-                "docid": datasets.Value("string"),
+                "docno": datasets.Value("string"),
+                "text": datasets.Value("string"),
             })
+            download_size = 5085726092 + 1035009698
         return datasets.DatasetInfo(
             # This is the description that will appear on the datasets page.
             description=_DESCRIPTION,
@@ -123,6 +124,7 @@ class TrecCast2019MultiTurn(datasets.GeneratorBasedBuilder):
             license=_LICENSE,
             # Citation for the dataset
             citation=_CITATION,
+            download_size=download_size
         )
 
     def _split_generators(self, dl_manager):
@@ -158,8 +160,8 @@ class TrecCast2019MultiTurn(datasets.GeneratorBasedBuilder):
             for row in qrels_file:
                 qid = row[0]
                 docno = row[2]
-                rank = row[3]
-                qrels[qid].append({'docno': docno, 'rank': rank})
+                relevance = row[3]
+                qrels[qid].append({'docno': docno, 'relevance': relevance})
 
             for qid in qrels.keys():
                 yield qid, {'qid': qid, 'qrels': qrels[qid]}
@@ -178,6 +180,19 @@ 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':
+            with open(file['msmarco']+"/collection.tsv") 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})
+
+            with open(file['car']+"/collection.tsv", 'rb') as f:
+                car = csv.reader(f, delimiter="\t")
+                for line in car:
+                    docid, text = line.split(" ")
+                    docid = f"CAR_{docid}"
+                    yield docid, ({"docno": docid, "text": text})
         else:
             raise NotImplementedError(f"'{split}' is not yet implemented")