Files
FastDeploy/fastdeploy/__init__.py

87 lines
2.6 KiB
Python

"""
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
import os
import uuid
# suppress warning log from paddlepaddle
os.environ["GLOG_minloglevel"] = "2"
# suppress log from aistudio
os.environ["AISTUDIO_LOG"] = "critical"
# set prometheus dir
if os.getenv("PROMETHEUS_MULTIPROC_DIR", "") == "":
prom_dir = f"/tmp/fd_prom_{str(uuid.uuid4())}"
os.environ["PROMETHEUS_MULTIPROC_DIR"] = prom_dir
if os.path.exists(prom_dir):
os.rmdir(prom_dir)
os.mkdir(prom_dir)
import typing
# first import prometheus setup to set PROMETHEUS_MULTIPROC_DIR
# otherwise, the Prometheus package will be imported first,
# which will prevent correct multi-process setup
from fastdeploy.metrics.prometheus_multiprocess_setup import (
setup_multiprocess_prometheus,
)
setup_multiprocess_prometheus()
from paddleformers.utils.log import logger as pf_logger
from fastdeploy.engine.sampling_params import SamplingParams
from fastdeploy.entrypoints.llm import LLM
from fastdeploy.utils import current_package_version, envs
if envs.FD_DEBUG != 1:
import logging
pf_logger.logger.setLevel(logging.INFO)
try:
import use_triton_in_paddle
use_triton_in_paddle.make_triton_compatible_with_paddle()
except ImportError:
pass
# TODO(tangbinhan): remove this code
__version__ = current_package_version()
MODULE_ATTRS = {"ModelRegistry": ".model_executor.models.model_base:ModelRegistry", "version": ".utils:version"}
if typing.TYPE_CHECKING:
from fastdeploy.model_executor.models.model_base import ModelRegistry
else:
def __getattr__(name: str) -> typing.Any:
from importlib import import_module
if name in MODULE_ATTRS:
try:
module_name, attr_name = MODULE_ATTRS[name].split(":")
module = import_module(module_name, __package__)
return getattr(module, attr_name)
except ModuleNotFoundError:
print(f"Module {MODULE_ATTRS[name]} not found.")
else:
print(f"module {__package__} has no attribute {name}")
__all__ = ["LLM", "SamplingParams", "ModelRegistry", "version"]