Files

40 lines
1.2 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import torch
_SMALLEST_LOGIT = float("-inf")
def _apply_bad_words_single_batch(
logits: torch.Tensor,
bad_words_token_ids: list[list[int]],
past_tokens_ids: list[int],
) -> None:
for bad_word_ids in bad_words_token_ids:
if len(bad_word_ids) > len(past_tokens_ids) + 1:
continue
prefix_length = len(bad_word_ids) - 1
last_token_id = bad_word_ids[-1]
if prefix_length > 0:
actual_prefix = past_tokens_ids[-prefix_length:]
else:
actual_prefix = []
expected_prefix = bad_word_ids[:prefix_length]
assert len(actual_prefix) == len(expected_prefix)
if actual_prefix == expected_prefix:
logits[last_token_id] = _SMALLEST_LOGIT
def apply_bad_words(
logits: torch.Tensor,
bad_words_token_ids: dict[int, list[list[int]]],
past_tokens_ids: list[list[int]],
) -> None:
for i, bad_words_ids in bad_words_token_ids.items():
_apply_bad_words_single_batch(logits[i], bad_words_ids,
past_tokens_ids[i])