Cast to long when masking tokens
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@@ -195,6 +195,7 @@ def _rotate_checkpoints(args, checkpoint_prefix="checkpoint", use_mtime=False) -
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def mask_tokens(inputs: torch.Tensor, tokenizer: PreTrainedTokenizer, args) -> Tuple[torch.Tensor, torch.Tensor]:
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""" Prepare masked tokens inputs/labels for masked language modeling: 80% MASK, 10% random, 10% original. """
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inputs = inputs.clone().type(dtype=torch.long)
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labels = inputs.clone()
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# We sample a few tokens in each sequence for masked-LM training (with probability args.mlm_probability defaults to 0.15 in Bert/RoBERTa)
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probability_matrix = torch.full(labels.shape, args.mlm_probability)
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