From 1dd4cb2935fc3fff9c156b5772d18e0a0d1861f0 Mon Sep 17 00:00:00 2001 From: Travis Johnson Date: Fri, 1 Nov 2024 11:33:15 -0600 Subject: [PATCH] [Bugfix] Fix edge cases for MistralTokenizer (#9625) Signed-off-by: Travis Johnson Signed-off-by: Prashant Gupta Co-authored-by: Prashant Gupta Co-authored-by: Patrick von Platen --- tests/tokenization/test_detokenize.py | 80 +++++++++++++++---- vllm/transformers_utils/tokenizers/mistral.py | 64 ++++++++++----- 2 files changed, 105 insertions(+), 39 deletions(-) diff --git a/tests/tokenization/test_detokenize.py b/tests/tokenization/test_detokenize.py index f4551ed42efb8..1d07885349409 100644 --- a/tests/tokenization/test_detokenize.py +++ b/tests/tokenization/test_detokenize.py @@ -1,4 +1,4 @@ -from typing import Any, Dict, List, Optional +from typing import Any, Dict, Generator, List, Optional import pytest from transformers import AutoTokenizer @@ -7,11 +7,17 @@ from vllm.transformers_utils.detokenizer import (Detokenizer, detokenize_incrementally) from vllm.transformers_utils.tokenizer_group import get_tokenizer_group +from vllm.transformers_utils.tokenizers.mistral import MistralTokenizer TRUTH = [ "Hello here, this is a simple test", "vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. It is designed to be used in production environments, where inference and serving", # noqa - "我很感谢你的热情" + "我很感谢你的热情", + # Burmese text triggers an edge-case for Mistral's V3-Tekken tokenizer (eg. + # for mistralai/Pixtral-12B-2409) where tokens may map to bytes with + # incomplete UTF-8 characters + # see https://github.com/vllm-project/vllm/pull/9625 + "ပုံပြင်လေးပြောပြပါ်", ] TOKENIZERS = [ "facebook/opt-125m", @@ -24,6 +30,7 @@ "tiiuae/falcon-7b", "meta-llama/Llama-2-7b-hf", "codellama/CodeLlama-7b-hf", + "mistralai/Pixtral-12B-2409", ] @@ -49,15 +56,55 @@ def _run_incremental_decode(tokenizer, all_input_ids, return decoded_text +@pytest.fixture +def tokenizer(tokenizer_name): + return (MistralTokenizer.from_pretrained(tokenizer_name) + if "mistral" in tokenizer_name else + AutoTokenizer.from_pretrained(tokenizer_name)) + + +@pytest.mark.parametrize("tokenizer_name", ["mistralai/Pixtral-12B-2409"]) +@pytest.mark.parametrize( + "truth", + [ + # Burmese text triggers an edge-case where tokens may map to bytes with + # incomplete UTF-8 characters + "ပုံပြင်လေးပြောပြပါ", + # Using "URGENCY" since "CY" has token id 130282 + "URGENCY🌶️", + ]) +def test_mistral_edge_case(tokenizer, truth): + """Test for a specific edge cases with V3-Tekken MistralTokenizer. + + See https://github.com/vllm-project/vllm/pull/9625 + """ + starting_index = 0 + all_input_ids = tokenizer(truth, add_special_tokens=False).input_ids + + decoded_text = _run_incremental_decode(tokenizer, + all_input_ids, + skip_special_tokens=True, + starting_index=starting_index) + assert decoded_text == truth + + +@pytest.fixture +def skip_special_tokens(request, tokenizer_name) -> Generator[bool, Any, None]: + if "mistral" in tokenizer_name: + yield ( + bool(True) if request.param else + pytest.skip("mistral doesn't support skip_special_tokens=False")) + else: + yield bool(True) if request.param else bool(False) + + @pytest.mark.parametrize("truth", TRUTH) @pytest.mark.parametrize("with_prompt", [True, False]) -@pytest.mark.parametrize("tokenizer_id", TOKENIZERS) -@pytest.mark.parametrize("skip_special_tokens", (True, False)) -def test_decode_streaming(tokenizer_id, truth, with_prompt, - skip_special_tokens): - tokenizer = AutoTokenizer.from_pretrained(tokenizer_id) +@pytest.mark.parametrize("tokenizer_name", TOKENIZERS) +@pytest.mark.parametrize("skip_special_tokens", (True, False), indirect=True) +def test_decode_streaming(tokenizer, truth, with_prompt, skip_special_tokens): if with_prompt: - truth_tokens = tokenizer(truth, add_special_tokens=False)["input_ids"] + truth_tokens = tokenizer(truth, add_special_tokens=False).input_ids prompt_input_ids = truth_tokens[:len(truth) // 2] generated_input_ids = truth_tokens[len(truth) // 2:] all_input_ids = prompt_input_ids + generated_input_ids @@ -68,7 +115,7 @@ def test_decode_streaming(tokenizer_id, truth, with_prompt, else: generated = truth starting_index = 0 - all_input_ids = tokenizer(truth, add_special_tokens=False)["input_ids"] + all_input_ids = tokenizer(truth, add_special_tokens=False).input_ids if skip_special_tokens: if tokenizer.bos_token_id is not None: all_input_ids = [tokenizer.bos_token_id] + all_input_ids @@ -98,7 +145,7 @@ def detokenizer(tokenizer_name: str) -> Detokenizer: enable_lora=False, max_num_seqs=100, max_input_length=None, - tokenizer_mode="auto", + tokenizer_mode="mistral" if "mistral" in tokenizer_name else "auto", trust_remote_code=False, revision=None, ) @@ -113,9 +160,8 @@ def detokenizer(tokenizer_name: str) -> Detokenizer: @pytest.fixture(name="complete_sequence_token_ids") def create_complete_sequence_token_ids(complete_sequence: str, - tokenizer_name: str) -> List[int]: - tokenizer = AutoTokenizer.from_pretrained(tokenizer_name) - complete_sequence_token_ids = tokenizer(complete_sequence)["input_ids"] + tokenizer) -> List[int]: + complete_sequence_token_ids = tokenizer(complete_sequence).input_ids return complete_sequence_token_ids @@ -150,7 +196,7 @@ def create_dummy_prompt_logprobs( @pytest.mark.parametrize("complete_sequence", TRUTH) @pytest.mark.parametrize("tokenizer_name", TOKENIZERS) -@pytest.mark.parametrize("skip_special_tokens", [True, False]) +@pytest.mark.parametrize("skip_special_tokens", [True, False], indirect=True) def test_decode_sequence_logprobs(complete_sequence: str, complete_sequence_token_ids: List[int], detokenizer: Detokenizer, @@ -208,9 +254,9 @@ def test_decode_prompt_logprobs(complete_sequence_token_ids: List[int], # decoded_prompt_logprobs doesn't contain the first token. token_ids = complete_sequence_token_ids - tokenzier = detokenizer.get_tokenizer_for_seq(seq) - text_full = tokenzier.decode(token_ids, skip_special_tokens=True) - text_first = tokenzier.decode(token_ids[0], skip_special_tokens=True) + tokenizer = detokenizer.get_tokenizer_for_seq(seq) + text_full = tokenizer.decode(token_ids, skip_special_tokens=True) + text_first = tokenizer.decode(token_ids[0], skip_special_tokens=True) text = text_full[len(text_first):] # Text for logprobs for the chosen token should be the same as the diff --git a/vllm/transformers_utils/tokenizers/mistral.py b/vllm/transformers_utils/tokenizers/mistral.py index 80e21c2d32ecc..896f70bc1dafd 100644 --- a/vllm/transformers_utils/tokenizers/mistral.py +++ b/vllm/transformers_utils/tokenizers/mistral.py @@ -16,9 +16,13 @@ from mistral_common.tokens.tokenizers.tekken import (SpecialTokenPolicy, Tekkenizer) +from vllm.logger import init_logger + if TYPE_CHECKING: from vllm.entrypoints.chat_utils import ChatCompletionMessageParam +logger = init_logger(__name__) + @dataclass class Encoding: @@ -72,20 +76,21 @@ def __init__(self, tokenizer: PublicMistralTokenizer) -> None: # Make sure special tokens will not raise tokenizer_.special_token_policy = SpecialTokenPolicy.IGNORE - self._vocab = { - token: idx - for idx, token in enumerate(tokenizer_.vocab()) - } elif isinstance(tokenizer_, SentencePieceTokenizer): - self._vocab = { - token: idx - for idx, token in enumerate(tokenizer_.vocab()) - } + pass else: raise TypeError(f"Unsupported tokenizer: {type(tokenizer_)}") + self._vocab = tokenizer_.vocab() + # Convert to a Dict[str, int] to match protocol, but this is a lossy + # conversion. There may be multiple token ids that decode to the same + # string due to partial UTF-8 byte sequences being converted to � + self._vocab_dict = { + token: idx + for idx, token in enumerate(self._vocab) + } self.tokenizer = tokenizer_ - self._max_token_id = max(self._vocab.values()) + self._max_token_id = self.vocab_size - 1 @classmethod def from_pretrained(cls, @@ -182,7 +187,9 @@ def __call__( return Encoding(input_ids=input_ids) def get_vocab(self) -> Dict[str, int]: - return self._vocab + # NB: the dictionary form of the vocabulary collapses token ids that map + # to the same string but have different bytes + return self._vocab_dict def get_added_vocab(self) -> Dict[str, int]: # Mistral tokenizers have no added vocabulary @@ -220,14 +227,20 @@ def convert_tokens_to_string(self, tokens: List[str]) -> str: if any(isinstance(t, bytes) for t in tokens): # we need to encode and decode all tokens again shift = self.tokenizer.num_special_tokens - byte_tokens = [ - t.encode("utf-8") if not isinstance(t, bytes) else t - for t in tokens - ] - ids = [ - self.tokenizer._tekken_token2id_nospecial[t] + shift - for t in byte_tokens - ] + + def _token_to_id(t: str): + t_bytes = t.encode("utf-8") \ + if not isinstance(t, bytes) else t + try: + return shift + \ + self.tokenizer._tekken_token2id_nospecial[t_bytes] + except KeyError: + logger.warning( + "Failed to convert token %s to id," + " replacing with ", t_bytes) + return self.tokenizer.unk_id + + ids = [_token_to_id(t) for t in tokens] decoded = self.tokenizer.decode(ids) else: decoded = "".join(tokens) @@ -236,7 +249,13 @@ def convert_tokens_to_string(self, tokens: List[str]) -> str: return decoded - def decode(self, ids: Union[List[int], int]) -> str: + def decode(self, + ids: Union[List[int], int], + skip_special_tokens: bool = True) -> str: + assert ( + skip_special_tokens + ), "Skipping special tokens is not supported for Mistral tokenizers." + if isinstance(ids, int): ids = [ids] return self.tokenizer.decode(ids) @@ -257,10 +276,11 @@ def convert_ids_to_tokens( tokens = [self.tokenizer.id_to_piece(id) for id in ids] - if any(t.strip() == "�" for t in tokens): - # if any stripped decoded token is undefined - # because it's invalid unicode then pass bytes + if any("�" in t for t in tokens): + # if a decoded token contains the replacement character, then the + # token has an incomplete UTF-8 character so we must use bytes # See: https://github.com/vllm-project/vllm/pull/8640 + # https://github.com/vllm-project/vllm/pull/9625 tokens = [self.tokenizer.id_to_byte_piece(id) for id in ids] return tokens