Sync from v0.13
This commit is contained in:
567
vllm/tokenizers/mistral.py
Normal file
567
vllm/tokenizers/mistral.py
Normal file
@@ -0,0 +1,567 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
||||
from pathlib import Path
|
||||
from typing import TYPE_CHECKING, Any, cast
|
||||
|
||||
from vllm.entrypoints.chat_utils import ChatCompletionMessageParam
|
||||
from vllm.entrypoints.openai.protocol import ChatCompletionRequest
|
||||
from vllm.logger import init_logger
|
||||
|
||||
from .protocol import TokenizerLike
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from mistral_common.protocol.instruct.request import (
|
||||
ChatCompletionRequest as MistralChatCompletionRequest,
|
||||
)
|
||||
from mistral_common.tokens.tokenizers.tekken import Tekkenizer
|
||||
from transformers import BatchEncoding
|
||||
|
||||
try:
|
||||
# Transformers v5
|
||||
from transformers.tokenization_mistral_common import MistralCommonBackend
|
||||
except ImportError:
|
||||
# Transformers v4
|
||||
from transformers.tokenization_mistral_common import (
|
||||
MistralCommonTokenizer as MistralCommonBackend,
|
||||
)
|
||||
|
||||
logger = init_logger(__name__)
|
||||
|
||||
|
||||
def maybe_serialize_tool_calls(request: "MistralChatCompletionRequest"):
|
||||
# SEE: https://github.com/vllm-project/vllm/pull/9951
|
||||
# Credits go to: @gcalmettes
|
||||
# NOTE: There is currently a bug in pydantic where attributes
|
||||
# declared as iterables are replaced in in the instances by
|
||||
# pydantic-core ValidatorIterator instance. In particular, this
|
||||
# affects tool_calls defined in ChatCompletionAssistantMessageParam
|
||||
# model:
|
||||
# see:
|
||||
# - https://github.com/pydantic/pydantic/issues/9467
|
||||
# As a result, tool_calls from assistant messages are never
|
||||
# deserialized in the request object if the tool_calls iterator is
|
||||
# not consumed. This affect messages passed to the MistralTokenizer
|
||||
# since no chat template is applied and therefore the tools_calls
|
||||
# iterator is not directly consumed.
|
||||
# Issue is tracked on Pydantic side, with resolution planned for
|
||||
# v2.11 release. In the meantime, the official workaround is to
|
||||
# consume the iterator so the tool_calls are correctly deserialized
|
||||
# in the OpenAI ChatCompletionAssistantMessageParam object
|
||||
# https://github.com/pydantic/pydantic/issues/9467#issuecomment-2442097291 # noqa: E501
|
||||
# Official Pydantic Issues:
|
||||
# - https://github.com/pydantic/pydantic/issues/9541
|
||||
# TODO: remove when pydantic v2.11 is released
|
||||
for i, message in enumerate(request.messages):
|
||||
if message.get("role") == "assistant":
|
||||
tool_calls_validator = message.get("tool_calls", ().__iter__())
|
||||
validated_tool_calls = []
|
||||
while True:
|
||||
try:
|
||||
tool_call = next(tool_calls_validator) # type: ignore
|
||||
validated_tool_calls.append(tool_call)
|
||||
except StopIteration:
|
||||
break
|
||||
|
||||
request.messages[i]["tool_calls"] = validated_tool_calls
|
||||
|
||||
|
||||
def truncate_tool_call_ids(request: "MistralChatCompletionRequest"):
|
||||
"""Truncates tool call IDs for Mistral's ID requirements."""
|
||||
for i, message in enumerate(request.messages):
|
||||
if message.get("role") == "assistant":
|
||||
tool_calls = message.get("tool_calls", [])
|
||||
for tool_call in tool_calls:
|
||||
if len(tool_call["id"]) > 9:
|
||||
logger.warning(
|
||||
"Truncating tool call ID: %s to %s",
|
||||
tool_call["id"],
|
||||
tool_call["id"][-9:],
|
||||
)
|
||||
tool_call["id"] = tool_call["id"][-9:]
|
||||
|
||||
request.messages[i]["tool_calls"] = tool_calls
|
||||
|
||||
elif message.get("role") in {"tool_results", "tool"}:
|
||||
if "tool_call_id" in message:
|
||||
tool_call_id = message["tool_call_id"]
|
||||
|
||||
if len(tool_call_id) > 9:
|
||||
logger.warning(
|
||||
"Truncating tool_call_id: %s to %s",
|
||||
tool_call_id,
|
||||
tool_call_id[-9:],
|
||||
)
|
||||
tool_call_id = tool_call_id[-9:]
|
||||
request.messages[i]["tool_call_id"] = tool_call_id
|
||||
|
||||
|
||||
def _prepare_apply_chat_template_tools_and_messages(
|
||||
messages: list["ChatCompletionMessageParam"],
|
||||
tools: list[dict[str, Any]] | None = None,
|
||||
continue_final_message: bool = False,
|
||||
add_generation_prompt: bool = False,
|
||||
) -> tuple[list["ChatCompletionMessageParam"], list[dict[str, Any]] | None]:
|
||||
from mistral_common.protocol.instruct.tool_calls import Function, Tool
|
||||
|
||||
if add_generation_prompt and continue_final_message:
|
||||
raise ValueError(
|
||||
"Cannot set both `add_generation_prompt` and "
|
||||
"`continue_final_message` to True."
|
||||
)
|
||||
|
||||
last_message = cast(dict[str, Any], messages[-1])
|
||||
# add_generation_prompt is directly handled by the tokenizer but we
|
||||
# check if the user is trying to use it with a final assistant message
|
||||
# which is probably not what they want.
|
||||
# If add_generation_prompt is False, we don't need to check anything.
|
||||
if add_generation_prompt and last_message["role"] == "assistant":
|
||||
raise ValueError(
|
||||
"Cannot set `add_generation_prompt` to True when "
|
||||
"the last message is from the assistant. Consider "
|
||||
"using `continue_final_message` instead."
|
||||
)
|
||||
if continue_final_message and last_message["role"] != "assistant":
|
||||
raise ValueError(
|
||||
"Cannot set `continue_final_message` to True when "
|
||||
"the last message is not from the assistant."
|
||||
)
|
||||
|
||||
# mistral-common requires AssistantMessage content to be string [1].
|
||||
#
|
||||
# [1]: https://github.com/mistralai/mistral-common/blob/f4a06998b75ed78bbf5aaf569590b772ea26c9f6/src/mistral_common/protocol/instruct/messages.py#L80
|
||||
for message in messages:
|
||||
# Remove reasoning as unsupported by Mistral
|
||||
_ = message.pop("reasoning", None) # type: ignore
|
||||
|
||||
# The Mistral client, in comparison to the OpenAI client, requires the
|
||||
# "parameters" dict and the "description" string to be present
|
||||
# even if they are empty.
|
||||
if tools:
|
||||
for function in [
|
||||
tool["function"] for tool in tools if tool["type"] == "function"
|
||||
]:
|
||||
if function.get("parameters") is None:
|
||||
function["parameters"] = {}
|
||||
if function.get("description") is None:
|
||||
function["description"] = ""
|
||||
|
||||
# We filter not supported arguments to avoid throwing an error.
|
||||
# TODO(juliendenize): remove this once OpenAI API is better supported by
|
||||
# `mistral-common`.
|
||||
tools_fields = set(Tool.model_fields.keys())
|
||||
function_fields = set(Function.model_fields.keys())
|
||||
for tool in tools:
|
||||
tool_keys = list(tool.keys())
|
||||
for tool_key in tool_keys:
|
||||
if tool_key not in tools_fields:
|
||||
tool.pop(tool_key)
|
||||
logger.warning_once(
|
||||
f"'{tool_key}' is not supported by mistral-common for tools. "
|
||||
"It has been poped from the tool definition."
|
||||
)
|
||||
if tool["type"] == "function":
|
||||
function_keys = list(tool["function"].keys())
|
||||
for function_key in function_keys:
|
||||
if function_key not in function_fields:
|
||||
tool["function"].pop(function_key)
|
||||
logger.warning_once(
|
||||
f"'{function_key}' is not supported by mistral-common "
|
||||
"for function tools. It has been poped from the "
|
||||
"function definition."
|
||||
)
|
||||
else:
|
||||
raise ValueError("mistral-common only supports function tools.")
|
||||
|
||||
return messages, tools
|
||||
|
||||
|
||||
def validate_request_params(request: "ChatCompletionRequest"):
|
||||
if request.chat_template is not None or request.chat_template_kwargs is not None:
|
||||
raise ValueError("chat_template is not supported for Mistral tokenizers.")
|
||||
|
||||
|
||||
def _tekken_token_to_id(tokenizer: "Tekkenizer", t: str | bytes) -> int:
|
||||
from mistral_common.tokens.tokenizers.tekken import Tekkenizer
|
||||
|
||||
assert isinstance(tokenizer, Tekkenizer), type(tokenizer)
|
||||
|
||||
t_bytes = t.encode("utf-8") if not isinstance(t, bytes) else t
|
||||
shift = tokenizer.num_special_tokens
|
||||
try:
|
||||
return shift + tokenizer._tekken_token2id_nospecial[t_bytes]
|
||||
except KeyError:
|
||||
t_str = t_bytes.decode("utf-8")
|
||||
if t_str in tokenizer._special_tokens_reverse_vocab:
|
||||
return tokenizer._special_tokens_reverse_vocab[t_str]
|
||||
logger.warning(
|
||||
"Failed to convert token %s to id, replacing with <unk>", t_bytes
|
||||
)
|
||||
return tokenizer.unk_id
|
||||
|
||||
|
||||
class MistralTokenizer(TokenizerLike):
|
||||
@classmethod
|
||||
def from_pretrained(
|
||||
cls,
|
||||
path_or_repo_id: str | Path,
|
||||
*args,
|
||||
trust_remote_code: bool = False,
|
||||
revision: str | None = None,
|
||||
download_dir: str | None = None,
|
||||
**kwargs,
|
||||
) -> "MistralTokenizer":
|
||||
from mistral_common.protocol.instruct.validator import ValidationMode
|
||||
|
||||
try:
|
||||
# Transformers v5
|
||||
from transformers.tokenization_mistral_common import MistralCommonBackend
|
||||
except ImportError:
|
||||
# Transformers v4
|
||||
from transformers.tokenization_mistral_common import (
|
||||
MistralCommonTokenizer as MistralCommonBackend,
|
||||
)
|
||||
|
||||
tokenizer = MistralCommonBackend.from_pretrained(
|
||||
path_or_repo_id,
|
||||
*args,
|
||||
mode=ValidationMode.test,
|
||||
cache_dir=download_dir,
|
||||
revision="main" if revision is None else revision,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
return cls(tokenizer)
|
||||
|
||||
def __init__(self, tokenizer: "MistralCommonBackend") -> None:
|
||||
super().__init__()
|
||||
|
||||
from mistral_common.protocol.instruct.validator import ValidationMode
|
||||
from mistral_common.tokens.tokenizers.sentencepiece import (
|
||||
SentencePieceTokenizer,
|
||||
)
|
||||
from mistral_common.tokens.tokenizers.tekken import Tekkenizer
|
||||
|
||||
self.transformers_tokenizer = tokenizer
|
||||
self.mistral = tokenizer.tokenizer
|
||||
self.instruct = self.mistral.instruct_tokenizer
|
||||
self.tokenizer = self.instruct.tokenizer
|
||||
|
||||
mode = self.mistral._chat_completion_request_validator._mode
|
||||
if mode != ValidationMode.test:
|
||||
raise ValueError(
|
||||
"Mistral tokenizer must be in test mode. Make sure to "
|
||||
"set `mode='ValidationMode.test'` when creating the "
|
||||
"Mistral tokenizer."
|
||||
)
|
||||
|
||||
_mistral_version_str = str(self.tokenizer.version.value)
|
||||
self.version: int = int(_mistral_version_str.split("v")[-1])
|
||||
|
||||
self.is_tekken = isinstance(self.tokenizer, Tekkenizer)
|
||||
self.is_spm = isinstance(self.tokenizer, SentencePieceTokenizer)
|
||||
if not (self.is_tekken or self.is_spm):
|
||||
raise TypeError(f"Unsupported tokenizer: {type(self.tokenizer)}")
|
||||
|
||||
# Reverse order to ensure that the lowest token id is kept.
|
||||
self._vocab_dict = {
|
||||
self.convert_ids_to_tokens([i], skip_special_tokens=False)[0]: i
|
||||
for i in range(self.vocab_size - 1, -1, -1)
|
||||
}
|
||||
# Sort the dict for convenience
|
||||
self._vocab_dict = dict(sorted(self._vocab_dict.items(), key=lambda x: x[1]))
|
||||
|
||||
# Cache special tokens for faster access.
|
||||
self._special_token_ids = self._get_special_token_ids()
|
||||
self._special_token_ids_set = set(self._special_token_ids)
|
||||
self._special_tokens = self._get_special_tokens(self._special_token_ids)
|
||||
self._special_tokens_set = set(self._special_tokens)
|
||||
|
||||
# Vocab sorted by token id.
|
||||
self._vocab = self.tokenizer._vocab
|
||||
self._max_token_id = self.vocab_size - 1
|
||||
|
||||
def _get_special_token_ids(self) -> list[int]:
|
||||
from mistral_common.tokens.tokenizers.sentencepiece import (
|
||||
SentencePieceTokenizer,
|
||||
)
|
||||
from mistral_common.tokens.tokenizers.tekken import Tekkenizer
|
||||
|
||||
if self.is_tekken:
|
||||
assert isinstance(self.tokenizer, Tekkenizer), type(self.tokenizer)
|
||||
special_ids = {t["rank"] for t in self.tokenizer._all_special_tokens}
|
||||
elif self.is_spm:
|
||||
assert isinstance(self.tokenizer, SentencePieceTokenizer), type(
|
||||
self.tokenizer
|
||||
)
|
||||
special_ids = self.tokenizer._control_tokens
|
||||
else:
|
||||
raise ValueError(f"Unknown tokenizer type: {type(self.tokenizer)}")
|
||||
return sorted(special_ids)
|
||||
|
||||
def _get_special_tokens(self, all_special_ids: list[int]) -> list[str]:
|
||||
from mistral_common.tokens.tokenizers.base import SpecialTokenPolicy
|
||||
|
||||
return [
|
||||
self.tokenizer.decode([i], special_token_policy=SpecialTokenPolicy.KEEP)
|
||||
for i in all_special_ids
|
||||
]
|
||||
|
||||
def num_special_tokens_to_add(self) -> int:
|
||||
return len(self.encode(""))
|
||||
|
||||
# the following attributes are set to fit vLLM's design and are used
|
||||
# by the structured output backends.
|
||||
@property
|
||||
def all_special_tokens(self) -> list[str]:
|
||||
return self._special_tokens
|
||||
|
||||
@property
|
||||
def all_special_ids(self) -> list[int]:
|
||||
return self._special_token_ids
|
||||
|
||||
@property
|
||||
def bos_token_id(self) -> int:
|
||||
return self.tokenizer.bos_id
|
||||
|
||||
@property
|
||||
def eos_token_id(self) -> int:
|
||||
return self.tokenizer.eos_id
|
||||
|
||||
@property
|
||||
def pad_token_id(self) -> int:
|
||||
return self.tokenizer.pad_id
|
||||
|
||||
@property
|
||||
def is_fast(self) -> bool:
|
||||
return True
|
||||
|
||||
@property
|
||||
def vocab_size(self) -> int:
|
||||
return self.transformers_tokenizer.vocab_size
|
||||
|
||||
@property
|
||||
def max_token_id(self) -> int:
|
||||
return self._max_token_id
|
||||
|
||||
@property
|
||||
def truncation_side(self) -> str:
|
||||
return self.transformers_tokenizer.truncation_side
|
||||
|
||||
def _is_special_token_id(self, token_id: int) -> bool:
|
||||
return token_id in self._special_token_ids_set
|
||||
|
||||
def __hash__(self) -> int:
|
||||
return hash(id(self))
|
||||
|
||||
def __len__(self) -> int:
|
||||
return self.vocab_size
|
||||
|
||||
def __call__(
|
||||
self,
|
||||
text: str | list[str],
|
||||
text_pair: str | None = None,
|
||||
add_special_tokens: bool = True,
|
||||
truncation: bool = False,
|
||||
max_length: int | None = None,
|
||||
) -> "BatchEncoding":
|
||||
if text_pair is not None:
|
||||
raise ValueError(
|
||||
"`text_pair` is not supported by `MistralTokenizer.__call__`."
|
||||
)
|
||||
|
||||
encoded = self.transformers_tokenizer(
|
||||
text=text,
|
||||
text_pair=text_pair,
|
||||
add_special_tokens=add_special_tokens,
|
||||
truncation=truncation,
|
||||
max_length=max_length,
|
||||
)
|
||||
# TODO(juliendenize): once https://github.com/huggingface/transformers/pull/41962
|
||||
# is in, revert to only call self.transformers_tokenizer(...).
|
||||
# Hack to fix wrongly added eos token, when fix will be supported the condition
|
||||
# below will be False even before the revert is done.
|
||||
if encoded["input_ids"] and encoded["input_ids"][-1] == self.eos_token_id:
|
||||
encoded["input_ids"].pop(-1)
|
||||
if attention_mask := encoded.get("attention_mask"):
|
||||
attention_mask.pop(-1)
|
||||
return encoded
|
||||
|
||||
@property
|
||||
def vocab(self) -> list[str]:
|
||||
return self._vocab
|
||||
|
||||
def get_vocab(self) -> dict[str, int]:
|
||||
return self._vocab_dict
|
||||
|
||||
def get_added_vocab(self) -> dict[str, int]:
|
||||
# Mistral tokenizers have no added vocabulary
|
||||
return {}
|
||||
|
||||
def encode(
|
||||
self,
|
||||
text: str,
|
||||
truncation: bool | None = None,
|
||||
max_length: int | None = None,
|
||||
add_special_tokens: bool = True,
|
||||
) -> list[int]:
|
||||
# TODO(juliendenize): once https://github.com/huggingface/transformers/pull/41962
|
||||
# is in, directly call self.transformers_tokenizer.encode(...).
|
||||
encoded = self.tokenizer.encode(text, bos=add_special_tokens, eos=False)
|
||||
|
||||
if truncation is not False and max_length is not None:
|
||||
return encoded[:max_length]
|
||||
else:
|
||||
return encoded
|
||||
|
||||
def apply_chat_template(
|
||||
self,
|
||||
messages: list["ChatCompletionMessageParam"],
|
||||
tools: list[dict[str, Any]] | None = None,
|
||||
**kwargs,
|
||||
) -> list[int]:
|
||||
add_generation_prompt = kwargs.pop("add_generation_prompt", False)
|
||||
continue_final_message = kwargs.get("continue_final_message", False)
|
||||
tokenize = kwargs.get("tokenize", True)
|
||||
padding = kwargs.get("padding", False)
|
||||
truncation = kwargs.get("truncation", False)
|
||||
max_length = kwargs.get("max_length")
|
||||
|
||||
messages, tools = _prepare_apply_chat_template_tools_and_messages(
|
||||
messages, tools, continue_final_message, add_generation_prompt
|
||||
)
|
||||
|
||||
return self.transformers_tokenizer.apply_chat_template(
|
||||
conversation=messages,
|
||||
tools=tools,
|
||||
continue_final_message=continue_final_message,
|
||||
tokenize=tokenize,
|
||||
padding=padding,
|
||||
truncation=truncation,
|
||||
max_length=max_length,
|
||||
return_tensors=None,
|
||||
return_dict=False,
|
||||
)
|
||||
|
||||
def decode(self, ids: list[int] | int, skip_special_tokens: bool = False) -> str:
|
||||
# TODO(juliendenize): once https://github.com/huggingface/transformers/pull/41962
|
||||
# is in, directly call self.transformers_tokenizer.decode(...).
|
||||
if isinstance(ids, int):
|
||||
ids = [ids]
|
||||
|
||||
return self.transformers_tokenizer.decode(
|
||||
ids, skip_special_tokens=skip_special_tokens
|
||||
)
|
||||
|
||||
def batch_decode(
|
||||
self, ids: list[list[int]] | list[int], skip_special_tokens: bool = False
|
||||
) -> str:
|
||||
return self.transformers_tokenizer.batch_decode(
|
||||
ids, skip_special_tokens=skip_special_tokens
|
||||
)
|
||||
|
||||
def convert_tokens_to_string(self, tokens: list[str]) -> str:
|
||||
from mistral_common.tokens.tokenizers.base import (
|
||||
SpecialTokenPolicy,
|
||||
SpecialTokens,
|
||||
)
|
||||
from mistral_common.tokens.tokenizers.sentencepiece import (
|
||||
SentencePieceTokenizer,
|
||||
)
|
||||
from mistral_common.tokens.tokenizers.tekken import Tekkenizer
|
||||
|
||||
to_decode_special_tokens = {SpecialTokens.tool_calls}
|
||||
if self.is_tekken:
|
||||
assert isinstance(self.tokenizer, Tekkenizer), type(self.tokenizer)
|
||||
tokens = [
|
||||
t
|
||||
for t in tokens
|
||||
if (t in to_decode_special_tokens or t not in self._special_tokens_set)
|
||||
]
|
||||
|
||||
if any(isinstance(t, bytes) for t in tokens):
|
||||
# we need to encode and decode all tokens again
|
||||
ids = [_tekken_token_to_id(self.tokenizer, t) for t in tokens]
|
||||
# We filtered unwanted special tokens before
|
||||
# so we can decode the rest.
|
||||
decoded = self.tokenizer.decode(ids, SpecialTokenPolicy.KEEP)
|
||||
else:
|
||||
decoded = "".join(tokens)
|
||||
else:
|
||||
# make sure certain special tokens like Tool calls are
|
||||
# not decoded
|
||||
assert isinstance(self.tokenizer, SentencePieceTokenizer), type(
|
||||
self.tokenizer
|
||||
)
|
||||
|
||||
regular_tokens: list[str] = []
|
||||
decoded_list: list[str] = []
|
||||
decoded = ""
|
||||
|
||||
for token in tokens:
|
||||
if token in to_decode_special_tokens:
|
||||
if regular_tokens:
|
||||
decoded_list.append(
|
||||
self.tokenizer.decode(
|
||||
regular_tokens, SpecialTokenPolicy.IGNORE
|
||||
)
|
||||
)
|
||||
regular_tokens = []
|
||||
decoded_list.append(token)
|
||||
else:
|
||||
regular_tokens.append(token)
|
||||
|
||||
if regular_tokens:
|
||||
decoded_list.append(
|
||||
self.tokenizer.decode(regular_tokens, SpecialTokenPolicy.IGNORE)
|
||||
)
|
||||
decoded = "".join(decoded_list)
|
||||
|
||||
return decoded
|
||||
|
||||
def convert_ids_to_tokens(
|
||||
self,
|
||||
ids: list[int],
|
||||
skip_special_tokens: bool = False,
|
||||
) -> list[str]:
|
||||
from mistral_common.tokens.tokenizers.base import (
|
||||
SpecialTokenPolicy,
|
||||
SpecialTokens,
|
||||
)
|
||||
from mistral_common.tokens.tokenizers.instruct import InstructTokenizerV13
|
||||
|
||||
if not skip_special_tokens:
|
||||
return [self.tokenizer.id_to_piece(token_id) for token_id in ids]
|
||||
|
||||
non_skip_special_tokens_ids = {
|
||||
self.tokenizer.get_control_token(SpecialTokens.tool_calls),
|
||||
}
|
||||
if isinstance(self.instruct, InstructTokenizerV13):
|
||||
if self.instruct.BEGIN_THINK:
|
||||
non_skip_special_tokens_ids.add(self.instruct.BEGIN_THINK)
|
||||
if self.instruct.END_THINK:
|
||||
non_skip_special_tokens_ids.add(self.instruct.END_THINK)
|
||||
|
||||
ids_kept = [
|
||||
i
|
||||
for i in ids
|
||||
if i in non_skip_special_tokens_ids or not self._is_special_token_id(i)
|
||||
]
|
||||
|
||||
# We filtered unwanted special tokens so we can decode the rest.
|
||||
tokens = [self.tokenizer.id_to_piece(token_id) for token_id in ids_kept]
|
||||
|
||||
if any("<EFBFBD>" in t for t in tokens) and self.is_tekken:
|
||||
# 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
|
||||
# if underlying tokenizer is sentencepiece, we just add "<22>".
|
||||
# We filtered unwanted special tokens so we can decode the rest.
|
||||
tokens = [
|
||||
self.tokenizer.id_to_byte_piece(token_id, SpecialTokenPolicy.KEEP)
|
||||
if token_id not in self._special_token_ids_set
|
||||
else self.tokenizer.decode([token_id], SpecialTokenPolicy.KEEP)
|
||||
for token_id in ids_kept
|
||||
]
|
||||
|
||||
return tokens
|
||||
Reference in New Issue
Block a user