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polish code with new pre-commit rule (#2923)

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This commit is contained in:
Zero Rains
2025-07-19 23:19:27 +08:00
committed by GitHub
parent b8676d71a8
commit 25698d56d1
424 changed files with 14307 additions and 13518 deletions
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65
fastdeploy/model_executor/guided_decoding/base_guided_decoding.py
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@@ -17,7 +17,7 @@
import os
from concurrent.futures import ThreadPoolExecutor
from fastdeploy.config import FDConfig, ErnieArchitectures
from fastdeploy.config import ErnieArchitectures, FDConfig
from fastdeploy.engine.request import Request
from fastdeploy.utils import llm_logger
@@ -48,7 +48,7 @@ class LogitsProcessorBase:
Raises:
NotImplementedError: This method should be implemented in subclasses.
"""
raise NotImplementedError()
raise NotImplementedError
def apply_token_mask(self, logits, token_bitmask):
"""
@@ -61,7 +61,7 @@ class LogitsProcessorBase:
Raises:
NotImplementedError: This method should be implemented in subclasses.
"""
raise NotImplementedError()
raise NotImplementedError
def allocate_token_bitmask(self, batch_size, vocab_size):
"""
@@ -74,7 +74,7 @@ class LogitsProcessorBase:
Returns:
tensor: The allocated token bitmask.
"""
raise NotImplementedError()
raise NotImplementedError
def accept_token(self, token):
"""
@@ -86,7 +86,7 @@ class LogitsProcessorBase:
Raises:
NotImplementedError: This method should be implemented in subclasses.
"""
raise NotImplementedError()
raise NotImplementedError
def is_terminated(self):
"""
@@ -95,13 +95,13 @@ class LogitsProcessorBase:
Raises:
NotImplementedError: This method should be implemented in subclasses.
"""
raise NotImplementedError()
raise NotImplementedError
def reset(self):
"""
Reset the matcher state.
"""
raise NotImplementedError()
raise NotImplementedError
def copy(self):
"""
@@ -110,7 +110,7 @@ class LogitsProcessorBase:
Returns:
BackendBase: A copy of the backend instance.
"""
raise NotImplementedError()
raise NotImplementedError
class BackendBase:
@@ -146,7 +146,7 @@ class BackendBase:
Raises:
NotImplementedError: This method should be implemented in subclasses.
"""
raise NotImplementedError()
raise NotImplementedError
def _json_processor(self, schemata):
"""
@@ -158,7 +158,7 @@ class BackendBase:
Raises:
NotImplementedError: This method should be implemented in subclasses.
"""
raise NotImplementedError()
raise NotImplementedError
def _regex_processor(self, schemata):
"""
@@ -170,7 +170,7 @@ class BackendBase:
Raises:
NotImplementedError: This method should be implemented in subclasses.
"""
raise NotImplementedError()
raise NotImplementedError
def _grammar_processor(self, schemata):
"""
@@ -182,7 +182,7 @@ class BackendBase:
Raises:
NotImplementedError: This method should be implemented in subclasses.
"""
raise NotImplementedError()
raise NotImplementedError
def _structural_tag_processor(self, schemata):
"""
@@ -194,7 +194,7 @@ class BackendBase:
Raises:
NotImplementedError: This method should be implemented in subclasses.
"""
raise NotImplementedError()
raise NotImplementedError
def _unsupported_processor_type(self, key_type, schemata):
"""
@@ -206,8 +206,7 @@ class BackendBase:
"""
raise Exception(f"Unsupported processor type {key_type}.")
def _init_logits_processor(
self, schemata_key: tuple[str, str]) -> LogitsProcessorBase:
def _init_logits_processor(self, schemata_key: tuple[str, str]) -> LogitsProcessorBase:
"""
init logits processor by type and schemata.
@@ -233,9 +232,7 @@ class BackendBase:
llm_logger.error(f"Unsupported processor type {key_type}.")
return None
def get_logits_processor(
self,
schemata_key: tuple[str, str]) -> tuple[LogitsProcessorBase, bool]:
def get_logits_processor(self, schemata_key: tuple[str, str]) -> tuple[LogitsProcessorBase, bool]:
"""
get logits processor by key from cache or create new one.
@@ -271,39 +268,41 @@ class BackendBase:
if not ErnieArchitectures.contains_ernie_arch(architectures):
from transformers import AutoTokenizer, PreTrainedTokenizerFast
tokenizer = AutoTokenizer.from_pretrained(
self.fd_config.parallel_config.model_name_or_path,
use_fast=False,
)
if not isinstance(tokenizer, PreTrainedTokenizerFast):
tokenizer = PreTrainedTokenizerFast(
__slow_tokenizer=tokenizer)
tokenizer = PreTrainedTokenizerFast(__slow_tokenizer=tokenizer)
else:
from fastdeploy.model_executor.guided_decoding.ernie_tokenizer import \
ErnieBotTokenizer
from fastdeploy.model_executor.guided_decoding.ernie_tokenizer import (
ErnieBotTokenizer,
)
vocab_file_names = [
"tokenizer.model", "spm.model", "ernie_token_100k.model"
"tokenizer.model",
"spm.model",
"ernie_token_100k.model",
]
for i in range(len(vocab_file_names)):
if os.path.exists(
os.path.join(
self.fd_config.parallel_config.
model_name_or_path, vocab_file_names[i])):
ErnieBotTokenizer.vocab_files_names[
"vocab_file"] = vocab_file_names[i]
os.path.join(
self.fd_config.parallel_config.model_name_or_path,
vocab_file_names[i],
)
):
ErnieBotTokenizer.vocab_files_names["vocab_file"] = vocab_file_names[i]
break
tokenizer = ErnieBotTokenizer.from_pretrained(
self.fd_config.parallel_config.model_name_or_path)
tokenizer = ErnieBotTokenizer.from_pretrained(self.fd_config.parallel_config.model_name_or_path)
return tokenizer
except Exception as e:
raise Exception(f"Fail to initialize hf tokenizer: {e}")
def add_cache(self, schemata_key: tuple[str, str],
processor: LogitsProcessorBase) -> None:
def add_cache(self, schemata_key: tuple[str, str], processor: LogitsProcessorBase) -> None:
"""
add logits processor to cache.
@@ -343,4 +342,4 @@ class BaseChecker:
Returns:
request (Request): request object with formatted schema.
"""
raise NotImplementedError()
raise NotImplementedError