english roberta large no finetune

roberta_large_no_finetune/predict.py

@@ -0,0 +1,62 @@
+import torch
+from fairseq.models.roberta import  RobertaModel
+from fairseq import hub_utils
+from fairseq.models.roberta import RobertaModel, RobertaHubInterface
+
+import os
+from tqdm import tqdm
+
+
+roberta = torch.hub.load('pytorch/fairseq', 'roberta.large')
+
+roberta.eval() 
+roberta.cuda()
+
+
+preds = roberta.fill_mask('I like <mask> and apples', topk=3)
+#import pdb; pdb.set_trace()
+
+# raise CUDA RuntimeError from which 
+# the process does not recover
+BLACKLIST = ['aeeadb08042bbd49dcbefcefa1f13806',
+            '01ba303704bb62bcb59f8cb7cb5663d7',
+            '98bdfa711364f45f1bcffb1359793614',
+            'a9da7950abcbd531a5207c04c3bdc840',
+            '4cd7f730ee72451406afa89c5c6431d6',
+        ]
+
+def predict(f_in_path,f_out_path):
+    f_in = open(f_in_path,'r', newline='\n')
+    f_out = open(f_out_path,'w', newline='\n')
+
+    for line in tqdm(f_in,total = 88000):
+        id,_, before, after = line.split('\t')
+        before = before.replace('\\n', '\n')
+        after = after.replace('\\n', '\n')
+        before = ' '.join(before.split(' ')[-40:]) # tu można poprawić, żeby  śmigał na tokenal spm a nie zakładał że jest jak ze spacjami
+        after = ' '.join(after.split(' ')[:40])
+        input = before + ' <mask> ' + after
+        try:
+            if id in BLACKLIST:
+                f_out.write(':1\n')
+                continue
+            preds = roberta.fill_mask(input, topk=10)
+            hyps = []
+            probs_sum = 0.0
+            for pred in preds:
+                if pred[2] == '<unk>':
+                    continue
+                hyps.append(pred[2].rstrip().lstrip() + ':' + str(pred[1]))
+                probs_sum += pred[1]
+            hyps.append(':' + str(1 - probs_sum))
+            preds_line = ' '.join(hyps)
+            f_out.write(preds_line + '\n')
+        except RuntimeError:
+            import pdb ; pdb.set_trace()
+            print('RUNTIMEERROR')
+            f_out.write(':1\n')
+
+    f_out.close()
+
+predict('../dev-0/in.tsv', '../dev-0/out.tsv')
+predict('../test-A/in.tsv', '../test-A/out.tsv')