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- '''
- This code was copied from
- https://github.com/PygmalionAI/gradio-ui/
- '''
- import torch
- import transformers
- class _SentinelTokenStoppingCriteria(transformers.StoppingCriteria):
- def __init__(self, sentinel_token_ids: torch.LongTensor,
- starting_idx: int):
- transformers.StoppingCriteria.__init__(self)
- self.sentinel_token_ids = sentinel_token_ids
- self.starting_idx = starting_idx
- def __call__(self, input_ids: torch.LongTensor,
- _scores: torch.FloatTensor) -> bool:
- for sample in input_ids:
- trimmed_sample = sample[self.starting_idx:]
- # Can't unfold, output is still too tiny. Skip.
- if trimmed_sample.shape[-1] < self.sentinel_token_ids.shape[-1]:
- continue
- for window in trimmed_sample.unfold(
- 0, self.sentinel_token_ids.shape[-1], 1):
- if torch.all(torch.eq(self.sentinel_token_ids, window)):
- return True
- return False
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