Merge remote-tracking branch 'upstream/main' into feat/optimizer

# Conflicts:
#	classifier.py
#	datasets.py

classifier.py

@@ -379,24 +379,3 @@ def get_args():
 
     print('Evaluating on SST...')
     test(config)
-
-    print('Training Sentiment Classifier on cfimdb...')
-    config = SimpleNamespace(
-        filepath='cfimdb-classifier.pt',
-        lr=args.lr,
-        use_gpu=args.use_gpu,
-        epochs=args.epochs,
-        batch_size=8,
-        hidden_dropout_prob=args.hidden_dropout_prob,
-        train='data/ids-cfimdb-train.csv',
-        dev='data/ids-cfimdb-dev.csv',
-        test='data/ids-cfimdb-test-student.csv',
-        option=args.option,
-        dev_out='predictions/' + args.option + '-cfimdb-dev-out.csv',
-        test_out='predictions/' + args.option + '-cfimdb-test-out.csv'
-    )
-
-    train(config)
-
-    print('Evaluating on cfimdb...')
-    test(config)

datasets.py

@@ -211,16 +211,16 @@ def load_multitask_test_data():
     sentiment_data = []
 
     with open(sentiment_filename, 'r', encoding='utf-8') as fp:
-        for record in csv.DictReader(fp, delimiter='\t'):
+        for record in csv.DictReader(fp,delimiter = '\t'):
             sent = record['sentence'].lower().strip()
             sentiment_data.append(sent)
 
     print(f"Loaded {len(sentiment_data)} test examples from {sentiment_filename}")
 
     paraphrase_data = []
     with open(paraphrase_filename, 'r', encoding='utf-8') as fp:
-        for record in csv.DictReader(fp, delimiter='\t'):
-            # if record['split'] != split:
+        for record in csv.DictReader(fp,delimiter = '\t'):
+            #if record['split'] != split:
             #    continue
             paraphrase_data.append((preprocess_string(record['sentence1']),
                                     preprocess_string(record['sentence2']),
@@ -230,7 +230,7 @@ def load_multitask_test_data():
 
     similarity_data = []
     with open(similarity_filename, 'r', encoding='utf-8') as fp:
-        for record in csv.DictReader(fp, delimiter='\t'):
+        for record in csv.DictReader(fp,delimiter = '\t'):
             similarity_data.append((preprocess_string(record['sentence1']),
                                     preprocess_string(record['sentence2']),
                                     ))
@@ -245,13 +245,13 @@ def load_multitask_data(sentiment_filename, paraphrase_filename, similarity_file
     num_labels = {}
     if split == 'test':
         with open(sentiment_filename, 'r', encoding='utf-8') as fp:
-            for record in csv.DictReader(fp, delimiter='\t'):
+            for record in csv.DictReader(fp,delimiter = '\t'):
                 sent = record['sentence'].lower().strip()
                 sent_id = record['id'].lower().strip()
                 sentiment_data.append((sent, sent_id))
     else:
         with open(sentiment_filename, 'r', encoding='utf-8') as fp:
-            for record in csv.DictReader(fp, delimiter='\t'):
+            for record in csv.DictReader(fp,delimiter = '\t'):
                 sent = record['sentence'].lower().strip()
                 sent_id = record['id'].lower().strip()
                 label = int(record['sentiment'].strip())
@@ -264,16 +264,15 @@ def load_multitask_data(sentiment_filename, paraphrase_filename, similarity_file
     paraphrase_data = []
     if split == 'test':
         with open(paraphrase_filename, 'r', encoding='utf-8') as fp:
-            for record in csv.DictReader(fp, delimiter='\t'):
+            for record in csv.DictReader(fp,delimiter = '\t'):
                 sent_id = record['id'].lower().strip()
                 paraphrase_data.append((preprocess_string(record['sentence1']),
                                         preprocess_string(record['sentence2']),
                                         sent_id))
 
     else:
         with open(paraphrase_filename, 'r', encoding='utf-8') as fp:
-            print(fp)
-            for record in csv.DictReader(fp, delimiter='\t'):
+            for record in csv.DictReader(fp,delimiter = '\t'):
                 try:
                     sent_id = record['id'].lower().strip()
                     paraphrase_data.append((preprocess_string(record['sentence1']),
@@ -287,14 +286,14 @@ def load_multitask_data(sentiment_filename, paraphrase_filename, similarity_file
     similarity_data = []
     if split == 'test':
         with open(similarity_filename, 'r', encoding='utf-8') as fp:
-            for record in csv.DictReader(fp, delimiter='\t'):
+            for record in csv.DictReader(fp,delimiter = '\t'):
                 sent_id = record['id'].lower().strip()
                 similarity_data.append((preprocess_string(record['sentence1']),
                                         preprocess_string(record['sentence2'])
                                         , sent_id))
     else:
         with open(similarity_filename, 'r', encoding='utf-8') as fp:
-            for record in csv.DictReader(fp, delimiter='\t'):
+            for record in csv.DictReader(fp,delimiter = '\t'):
                 sent_id = record['id'].lower().strip()
                 similarity_data.append((preprocess_string(record['sentence1']),
                                         preprocess_string(record['sentence2']),