Close open files to suppress ResourceWarning

examples/legacy/seq2seq/run_distributed_eval.py

@@ -204,7 +204,8 @@ def run_generate():
             save_json(preds, save_path)
             return
         tgt_file = Path(args.data_dir).joinpath(args.type_path + ".target")
-        labels = [x.rstrip() for x in open(tgt_file).readlines()][: len(preds)]
+        with open(tgt_file) as f:
+            labels = [x.rstrip() for x in f.readlines()][: len(preds)]
 
         # Calculate metrics, save metrics,  and save _generations.txt
         calc_bleu = "translation" in args.task

examples/research_projects/seq2seq-distillation/run_eval.py

@@ -115,7 +115,8 @@ def run_generate(verbose=True):
     parsed_args = parse_numeric_n_bool_cl_kwargs(rest)
     if parsed_args and verbose:
         print(f"parsed the following generate kwargs: {parsed_args}")
-    examples = [" " + x.rstrip() if "t5" in args.model_name else x.rstrip() for x in open(args.input_path).readlines()]
+    with open(args.input_path) as f:
+        examples = [" " + x.rstrip() if "t5" in args.model_name else x.rstrip() for x in f.readlines()]
     if args.n_obs > 0:
         examples = examples[: args.n_obs]
     Path(args.save_path).parent.mkdir(exist_ok=True)

src/transformers/convert_slow_tokenizer.py

@@ -305,7 +305,8 @@ def __init__(self, *args):
         from .utils import sentencepiece_model_pb2 as model_pb2
 
         m = model_pb2.ModelProto()
-        m.ParseFromString(open(self.original_tokenizer.vocab_file, "rb").read())
+        with open(self.original_tokenizer.vocab_file, "rb") as f:
+            m.ParseFromString(f.read())
         self.proto = m
 
     def vocab(self, proto):