Fixing some issues with unassigned questions

examples/training_quora_duplicate_questions/create_splits.py

@@ -48,6 +48,8 @@
 import os
 from sentence_transformers import util
 
+random.seed(42)
+
 #Get raw file
 source_file = "quora-IR-dataset/quora_duplicate_questions.tsv"
 os.makedirs('quora-IR-dataset', exist_ok=True)
@@ -104,7 +106,6 @@
 #Distribute rows to train/dev/test split
 #Ensure that sets contain distinct sentences
 is_assigned = set()
-random.seed(42)
 random.shuffle(rows)
 
 train_ids = set()
@@ -113,15 +114,28 @@
 
 counter = 0
 for row in rows:
-    if row['qid1'] in is_assigned or row['qid2'] in is_assigned:
+    if row['qid1'] in is_assigned and row['qid2'] in is_assigned:
         continue
-
-    #Distribution about 85%/5%/10%
-    target_set = train_ids
-    if counter%10 == 0:
-        target_set = dev_ids
-    elif counter%10 == 1 or counter%10 == 2:
-        target_set = test_ids
+    elif row['qid1'] in is_assigned or row['qid2'] in is_assigned:
+
+        if row['qid2'] in is_assigned: #Ensure that qid1 is assigned and qid2 not yet
+            row['qid1'], row['qid2'] = row['qid2'], row['qid1']
+
+        #Move qid2 to the same split as qid1
+        target_set = train_ids
+        if row['qid1'] in dev_ids:
+            target_set = dev_ids
+        elif row['qid1'] in test_ids:
+            target_set = test_ids
+
+    else:
+        #Distribution about 85%/5%/10%
+        target_set = train_ids
+        if counter%10 == 0:
+            target_set = dev_ids
+        elif counter%10 == 1 or counter%10 == 2:
+            target_set = test_ids
+        counter += 1
 
     #Get the sentence with all duplicates and add it to the respective sets
     target_set.add(row['qid1'])
@@ -134,9 +148,14 @@
         target_set.add(b)
         is_assigned.add(b)
 
-    counter += 1
 
-print("Train sentences:", len(train_ids))
+#Assert all sets are mutually exclusive
+assert len(train_ids.intersection(dev_ids)) == 0
+assert len(train_ids.intersection(test_ids)) == 0
+assert len(test_ids.intersection(dev_ids)) == 0
+
+
+print("\nTrain sentences:", len(train_ids))
 print("Dev sentences:", len(dev_ids))
 print("Test sentences:", len(test_ids))
 
@@ -154,8 +173,8 @@ def get_duplicate_set(ids_set):
 test_duplicates = get_duplicate_set(test_ids)
 
 
-print("Train duplicates", len(train_duplicates))
-print("dev duplicates", len(dev_duplicates))
+print("\nTrain duplicates", len(train_duplicates))
+print("Dev duplicates", len(dev_duplicates))
 print("Test duplicates", len(test_duplicates))
 
 ############### Write general files about the duplate questions graph ############
@@ -174,7 +193,7 @@ def get_duplicate_set(ids_set):
 duplicates_list = sorted(duplicates_list, key=lambda x: x[0]*1000000+x[1])
 
 
-print("Write duplicate graph in pairwise format")
+print("\nWrite duplicate graph in pairwise format")
 with open('quora-IR-dataset/graph/duplicates-graph-pairwise.tsv', 'w', encoding='utf8') as fOut:
     fOut.write("qid1\tqid2\n")
     for a, b in duplicates_list:
@@ -192,7 +211,7 @@ def get_duplicate_set(ids_set):
 def write_qids(name, ids_list):
     with open('quora-IR-dataset/graph/'+name+'-questions.tsv', 'w', encoding='utf8') as fOut:
         fOut.write("qid\n")
-        fOut.write("\n".join(sorted(ids_list)))
+        fOut.write("\n".join(sorted(ids_list, key=lambda x: int(x))))
 
 write_qids('train', train_ids)
 write_qids('dev', dev_ids)
@@ -249,54 +268,60 @@ def write_mining_files(name, ids, dups):
 test_queries = set()
 
 #Create dev queries
-for a, b in dev_duplicates:
-    if a not in corpus_ids and b not in corpus_ids:
-        if len(dev_queries) < num_dev_queries:
+rnd_dev_ids = sorted(list(dev_ids))
+random.shuffle(rnd_dev_ids)
+
+for a in rnd_dev_ids:
+    if a not in corpus_ids:
+        if len(dev_queries) < num_dev_queries and len(duplicates[a]) > 0:
             dev_queries.add(a)
         else:
             corpus_ids.add(a)
 
-        corpus_ids.add(b)
-        for further_dups in duplicates[b]:
-            if further_dups not in dev_queries:
-                corpus_ids.add(further_dups)
+        for b in duplicates[a]:
+            if b not in dev_queries:
+                corpus_ids.add(b)
 
 #Create test queries
-for a, b in test_duplicates:
-    if a not in corpus_ids and b not in corpus_ids:
-        if len(test_queries) < num_test_queries:
+rnd_test_ids = sorted(list(test_ids))
+random.shuffle(rnd_test_ids)
+
+for a in rnd_test_ids:
+    if a not in corpus_ids:
+        if len(test_queries) < num_test_queries and len(duplicates[a]) > 0:
             test_queries.add(a)
         else:
             corpus_ids.add(a)
 
-        corpus_ids.add(b)
-        for further_dups in duplicates[b]:
-            if further_dups not in test_queries:
-                corpus_ids.add(further_dups)
+        for b in duplicates[a]:
+            if b not in test_queries:
+                corpus_ids.add(b)
 
 #Write output for information-retrieval
+print("\nInformation Retrival Setup")
 print("Corpus size:", len(corpus_ids))
 print("Dev queries:", len(dev_queries))
 print("Test queries:", len(test_queries))
 
 with open('quora-IR-dataset/information-retrieval/corpus.tsv', 'w', encoding='utf8') as fOut:
     fOut.write("qid\tquestion\n")
-    for id in corpus_ids:
+    for id in sorted(corpus_ids, key=lambda id: int(id)):
         fOut.write("{}\t{}\n".format(id, sentences[id]))
 
 with open('quora-IR-dataset/information-retrieval/dev-queries.tsv', 'w', encoding='utf8') as fOut:
     fOut.write("qid\tquestion\tduplicate_qids\n")
-    for id in dev_queries:
+    for id in sorted(dev_queries, key=lambda id: int(id)):
         fOut.write("{}\t{}\t{}\n".format(id, sentences[id], ",".join(duplicates[id])))
 
 with open('quora-IR-dataset/information-retrieval/test-queries.tsv', 'w', encoding='utf8') as fOut:
     fOut.write("qid\tquestion\tduplicate_qids\n")
-    for id in test_queries:
+    for id in sorted(test_queries, key=lambda id: int(id)):
         fOut.write("{}\t{}\t{}\n".format(id, sentences[id], ",".join(duplicates[id])))
 
 
+print("--DONE--")
+
 
 
 
 
-print("--DONE--")