save_pretrained: mkdir(exist_ok=True) (#5258)
* all save_pretrained methods mkdir if not os.path.exists
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@@ -809,10 +809,6 @@ def main():
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# Save the trained model and the tokenizer
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if args.do_train and (args.local_rank == -1 or torch.distributed.get_rank() == 0):
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# Create output directory if needed
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if not os.path.exists(args.output_dir) and args.local_rank in [-1, 0]:
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os.makedirs(args.output_dir)
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logger.info("Saving model checkpoint to %s", args.output_dir)
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# Save a trained model, configuration and tokenizer using `save_pretrained()`.
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# They can then be reloaded using `from_pretrained()`
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