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Update server_fastapi.py. Avoid loading the model repeatedly. Add logger (#145)

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* Update server_fastapi.py. Avoid loading the model repeatedly. Add loguru logger.

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This commit is contained in:
Sora
2023-11-03 13:09:58 +08:00
committed by GitHub
parent 7737079323
commit 25ea864b56
3 changed files with 92 additions and 55 deletions
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131
server_fastapi.py
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@@ -6,7 +6,7 @@ import gc
import random
import utils
from fastapi import FastAPI, Query
from fastapi import FastAPI, Query, Request
from fastapi.responses import Response, FileResponse
from fastapi.staticfiles import StaticFiles
from io import BytesIO
@@ -16,9 +16,10 @@ import torch
import webbrowser
import psutil
import GPUtil
from typing import Dict, Optional, List
from typing import Dict, Optional, List, Set
import os
from loguru import logger
from tools.log import logger
from urllib.parse import unquote
from infer import infer, get_net_g, latest_version
import tools.translate as trans
@@ -67,25 +68,7 @@ class Models:
self.num = 0
# spkInfo[角色名][模型id] = 角色id
self.spk_info: Dict[str, Dict[int, int]] = dict()
self.paths: Dict[str, int] = dict() # 路径, 引用数
def add_model(self, model: Model):
"""添加一个模型"""
self.models[self.num] = model
# 添加角色信息
for speaker, speaker_id in model.spk2id.items():
if speaker not in self.spk_info.keys():
self.spk_info[speaker] = {self.num: speaker_id}
else:
self.spk_info[speaker][self.num] = speaker_id
# 添加路径信息
model_path = os.path.realpath(model.model_path)
if model_path not in self.paths.keys():
self.paths[model_path] = 1
else:
self.paths[model_path] += 1
# 修改计数
self.num += 1
self.path2ids: Dict[str, Set[int]] = dict() # 路径指向的model的id
def init_model(
self, config_path: str, model_path: str, device: str, language: str
@@ -98,26 +81,30 @@ class Models:
:param device: 模型推理使用设备
:param language: 模型推理默认语言
"""
self.models[self.num] = Model(
config_path=config_path,
model_path=model_path,
device=device,
language=language,
)
# 若路径中的模型已存在，则不添加模型，若不存在，则进行初始化。
model_path = os.path.realpath(model_path)
if model_path not in self.path2ids.keys():
self.path2ids[model_path] = {self.num}
self.models[self.num] = Model(
config_path=config_path,
model_path=model_path,
device=device,
language=language,
)
logger.success(f"添加模型{model_path}，使用配置文件{os.path.realpath(config_path)}")
else:
# 获取一个指向id
m_id = next(iter(self.path2ids[model_path]))
self.models[self.num] = self.models[m_id]
self.path2ids[model_path].add(self.num)
logger.success("模型已存在，添加模型引用。")
# 添加角色信息
for speaker, speaker_id in self.models[self.num].spk2id.items():
if speaker not in self.spk_info.keys():
self.spk_info[speaker] = {self.num: speaker_id}
else:
self.spk_info[speaker][self.num] = speaker_id
# 添加路径信息
model_path = os.path.realpath(self.models[self.num].model_path)
if model_path not in self.paths.keys():
self.paths[model_path] = 1
else:
self.paths[model_path] += 1
# 修改计数
logger.success(f"添加模型{model_path}，使用配置文件{os.path.realpath(config_path)}")
self.num += 1
return self.num - 1
@@ -133,13 +120,13 @@ class Models:
self.spk_info.pop(speaker)
# 删除路径信息
model_path = os.path.realpath(self.models[index].model_path)
self.paths[model_path] -= 1
assert self.paths[model_path] >= 0
if self.paths[model_path] == 0:
# 引用数为零时予以清空
self.paths.pop(model_path)
self.path2ids[model_path].remove(index)
if len(self.path2ids[model_path]) == 0:
self.path2ids.pop(model_path)
logger.success(f"删除模型{model_path}, id = {index}")
else:
logger.success(f"删除模型引用{model_path}, id = {index}")
# 删除模型
logger.success(f"卸载模型{model_path}, id = {index}")
self.models.pop(index)
gc.collect()
if torch.cuda.is_available():
@@ -181,6 +168,7 @@ if __name__ == "__main__":
@app.get("/voice")
def voice(
request: Request, # fastapi自动注入
text: str = Query(..., description="输入文字"),
model_id: int = Query(..., description="模型ID"), # 模型序号
speaker_name: str = Query(
@@ -195,7 +183,9 @@ if __name__ == "__main__":
auto_translate: bool = Query(False, description="自动翻译"),
):
"""语音接口"""
logger.info(
f"{request.client.host}:{request.client.port}/voice { unquote(str(request.query_params) )}"
)
# 检查模型是否存在
if model_id not in loaded_models.models.keys():
return {"status": 10, "detail": f"模型model_id={model_id}未加载"}
@@ -235,7 +225,7 @@ if __name__ == "__main__":
return response
@app.get("/models/info")
def get_loaded_models_info():
def get_loaded_models_info(request: Request):
"""获取已加载模型信息"""
result: Dict[str, Dict] = dict()
@@ -244,9 +234,13 @@ if __name__ == "__main__":
return result
@app.get("/models/delete")
def delete_model(model_id: int = Query(..., description="删除模型id")):
def delete_model(
request: Request, model_id: int = Query(..., description="删除模型id")
):
"""删除指定模型"""
logger.info(
f"{request.client.host}:{request.client.port}/models/delete { unquote(str(request.query_params) )}"
)
result = loaded_models.del_model(model_id)
if result is None:
return {"status": 14, "detail": f"模型{model_id}不存在，删除失败"}
@@ -254,6 +248,7 @@ if __name__ == "__main__":
@app.get("/models/add")
def add_model(
request: Request,
model_path: str = Query(..., description="添加模型路径"),
config_path: str = Query(
None, description="添加模型配置文件路径，不填则使用./config.json或../config.json"
@@ -261,7 +256,10 @@ if __name__ == "__main__":
device: str = Query("cuda", description="推理使用设备"),
language: str = Query("ZH", description="模型默认语言"),
):
"""添加指定模型：允许重复添加相同路径模型，注意，当前实现中模型会重复加载，加载两次占用两份内存"""
"""添加指定模型：允许重复添加相同路径模型，且不重复占用内存"""
logger.info(
f"{request.client.host}:{request.client.port}/models/add { unquote(str(request.query_params) )}"
)
if config_path is None:
model_dir = os.path.dirname(model_path)
if os.path.isfile(os.path.join(model_dir, "config.json")):
@@ -296,6 +294,7 @@ if __name__ == "__main__":
}
def _get_all_models(root_dir: str = "Data", only_unloaded: bool = False):
"""从root_dir搜索获取所有可用模型"""
result: Dict[str, List[str]] = dict()
files = os.listdir(root_dir) + ["."]
for file in files:
@@ -307,11 +306,12 @@ if __name__ == "__main__":
model_files = []
for sub_file in sub_files:
relpath = os.path.realpath(os.path.join(sub_dir, sub_file))
if only_unloaded and relpath in loaded_models.paths.keys():
if only_unloaded and relpath in loaded_models.path2count.keys():
continue
if sub_file.endswith(".pth") and sub_file.startswith("G_"):
if os.path.isfile(relpath):
model_files.append(sub_file)
# 对模型文件按步数排序
model_files = sorted(
model_files,
key=lambda pth: int(pth.lstrip("G_").rstrip(".pth"))
@@ -325,11 +325,12 @@ if __name__ == "__main__":
sub_files = os.listdir(models_dir)
for sub_file in sub_files:
relpath = os.path.realpath(os.path.join(models_dir, sub_file))
if only_unloaded and relpath in loaded_models.paths.keys():
if only_unloaded and relpath in loaded_models.path2count.keys():
continue
if sub_file.endswith(".pth") and sub_file.startswith("G_"):
if os.path.isfile(os.path.join(models_dir, sub_file)):
model_files.append(f"models/{sub_file}")
# 对模型文件按步数排序
model_files = sorted(
model_files,
key=lambda pth: int(pth.lstrip("models/G_").rstrip(".pth"))
@@ -343,13 +344,23 @@ if __name__ == "__main__":
return result
@app.get("/models/get_unloaded")
def get_unloaded_models_info(root_dir: str = Query("Data", description="搜索根目录")):
def get_unloaded_models_info(
request: Request, root_dir: str = Query("Data", description="搜索根目录")
):
"""获取未加载模型"""
logger.info(
f"{request.client.host}:{request.client.port}/models/get_unloaded { unquote(str(request.query_params) )}"
)
return _get_all_models(root_dir, only_unloaded=True)
@app.get("/models/get_local")
def get_local_models_info(root_dir: str = Query("Data", description="搜索根目录")):
def get_local_models_info(
request: Request, root_dir: str = Query("Data", description="搜索根目录")
):
"""获取全部本地模型"""
logger.info(
f"{request.client.host}:{request.client.port}/models/get_local { unquote(str(request.query_params) )}"
)
return _get_all_models(root_dir, only_unloaded=False)
@app.get("/status")
@@ -390,22 +401,30 @@ if __name__ == "__main__":
@app.get("/tools/translate")
def translate(
request: Request,
texts: str = Query(..., description="待翻译文本"),
to_language: str = Query(..., description="翻译目标语言"),
):
"""翻译"""
logger.info(
f"{request.client.host}:{request.client.port}/tools/translate { unquote(str(request.query_params) )}"
)
return {"texts": trans.translate(Sentence=texts, to_Language=to_language)}
all_examples: Dict[str, Dict[str, List]] = dict() # 存放示例
@app.get("/tools/random_example")
def random_example(
request: Request,
language: str = Query(None, description="指定语言，未指定则随机返回"),
root_dir: str = Query("Data", description="搜索根目录"),
):
"""
获取一个随机音频+文本，用于对比，音频会从本地目录随机选择。
"""
logger.info(
f"{request.client.host}:{request.client.port}/tools/random_example { unquote(str(request.query_params) )}"
)
global all_examples
# 数据初始化
if root_dir not in all_examples.keys():
@@ -417,7 +436,6 @@ if __name__ == "__main__":
for root, directories, _files in os.walk("Data"):
for file in _files:
if file in ["train.list", "val.list"]:
print(file)
with open(
os.path.join(root, file), mode="r", encoding="utf-8"
) as f:
@@ -478,7 +496,10 @@ if __name__ == "__main__":
}
@app.get("/tools/get_audio")
def get_audio(path: str = Query(..., description="本地音频路径")):
def get_audio(request: Request, path: str = Query(..., description="本地音频路径")):
logger.info(
f"{request.client.host}:{request.client.port}/tools/get_audio { unquote(str(request.query_params) )}"
)
if not os.path.isfile(path):
return {"status": 18, "detail": "指定音频不存在"}
if not path.endswith(".wav"):
@@ -486,6 +507,8 @@ if __name__ == "__main__":
return FileResponse(path=path)
logger.warning("本地服务，请勿将服务端口暴露于外网")
print(f"api文档地址 http://127.0.0.1:{config.server_config.port}/docs")
logger.info(f"api文档地址 http://127.0.0.1:{config.server_config.port}/docs")
webbrowser.open(f"http://127.0.0.1:{config.server_config.port}")
uvicorn.run(app, port=config.server_config.port, host="0.0.0.0")
uvicorn.run(
app, port=config.server_config.port, host="0.0.0.0", log_level="warning"
)