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https://github.com/huggingface/transformers.git
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Close open files to suppress ResourceWarning (#11240)
Co-authored-by: Sudharsan Thirumalai <sudharsan.t@sprinklr.com>
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@ -204,7 +204,8 @@ def run_generate():
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save_json(preds, save_path)
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return
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tgt_file = Path(args.data_dir).joinpath(args.type_path + ".target")
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labels = [x.rstrip() for x in open(tgt_file).readlines()][: len(preds)]
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with open(tgt_file) as f:
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labels = [x.rstrip() for x in f.readlines()][: len(preds)]
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# Calculate metrics, save metrics, and save _generations.txt
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calc_bleu = "translation" in args.task
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@ -115,7 +115,8 @@ def run_generate(verbose=True):
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parsed_args = parse_numeric_n_bool_cl_kwargs(rest)
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if parsed_args and verbose:
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print(f"parsed the following generate kwargs: {parsed_args}")
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examples = [" " + x.rstrip() if "t5" in args.model_name else x.rstrip() for x in open(args.input_path).readlines()]
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with open(args.input_path) as f:
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examples = [" " + x.rstrip() if "t5" in args.model_name else x.rstrip() for x in f.readlines()]
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if args.n_obs > 0:
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examples = examples[: args.n_obs]
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Path(args.save_path).parent.mkdir(exist_ok=True)
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@ -305,7 +305,8 @@ class SpmConverter(Converter):
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from .utils import sentencepiece_model_pb2 as model_pb2
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m = model_pb2.ModelProto()
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m.ParseFromString(open(self.original_tokenizer.vocab_file, "rb").read())
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with open(self.original_tokenizer.vocab_file, "rb") as f:
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m.ParseFromString(f.read())
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self.proto = m
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def vocab(self, proto):
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