提交 72c0cda3 编写于 作者: L lym0302

add paddlespeech_server stats, test=doc

上级 395c923d
......@@ -68,7 +68,7 @@ class StatsExecutor():
)
return False
if self.task == 'asr':
elif self.task == 'asr':
try:
from ..asr.infer import pretrained_models
logger.info(
......
......@@ -14,3 +14,4 @@
from .paddlespeech_client import ASRClientExecutor
from .paddlespeech_client import TTSClientExecutor
from .paddlespeech_server import ServerExecutor
from .paddlespeech_server import ServerStatsExecutor
......@@ -16,15 +16,17 @@ from typing import List
import uvicorn
from fastapi import FastAPI
from prettytable import PrettyTable
from ..executor import BaseExecutor
from ..util import cli_server_register
from ..util import stats_wrapper
from paddlespeech.cli.log import logger
from paddlespeech.server.engine.engine_pool import init_engine_pool
from paddlespeech.server.restful.api import setup_router
from paddlespeech.server.utils.config import get_config
__all__ = ['ServerExecutor']
__all__ = ['ServerExecutor', 'ServerStatsExecutor']
app = FastAPI(
title="PaddleSpeech Serving API", description="Api", version="0.0.1")
......@@ -86,3 +88,139 @@ class ServerExecutor(BaseExecutor):
config = get_config(config_file)
if self.init(config):
uvicorn.run(app, host=config.host, port=config.port, debug=True)
@cli_server_register(
name='paddlespeech_server.stats',
description='Get the models supported by each speech task in the service.')
class ServerStatsExecutor():
def __init__(self):
super(ServerStatsExecutor, self).__init__()
self.parser = argparse.ArgumentParser(
prog='paddlespeech_server.stats', add_help=True)
self.parser.add_argument(
'--task',
type=str,
default=None,
choices=['asr', 'tts'],
help='Choose speech task.',
required=True)
self.task_choices = ['asr', 'tts']
self.model_name_format = {
'asr': 'Model-Language-Sample Rate',
'tts': 'Model-Language'
}
def show_support_models(self, pretrained_models: dict):
fields = self.model_name_format[self.task].split("-")
table = PrettyTable(fields)
for key in pretrained_models:
table.add_row(key.split("-"))
print(table)
def execute(self, argv: List[str]) -> bool:
"""
Command line entry.
"""
parser_args = self.parser.parse_args(argv)
self.task = parser_args.task
if self.task not in self.task_choices:
logger.error(
"Please input correct speech task, choices = ['asr', 'tts']")
return False
elif self.task == 'asr':
try:
from paddlespeech.cli.asr.infer import pretrained_models
logger.info(
"Here is the table of ASR pretrained models supported in the service."
)
self.show_support_models(pretrained_models)
# show ASR static pretrained model
from paddlespeech.server.engine.asr.paddleinference.asr_engine import pretrained_models
logger.info(
"Here is the table of ASR static pretrained models supported in the service."
)
self.show_support_models(pretrained_models)
return True
except BaseException:
logger.error(
"Failed to get the table of ASR pretrained models supported in the service."
)
return False
elif self.task == 'tts':
try:
from paddlespeech.cli.tts.infer import pretrained_models
logger.info(
"Here is the table of TTS pretrained models supported in the service."
)
self.show_support_models(pretrained_models)
# show TTS static pretrained model
from paddlespeech.server.engine.tts.paddleinference.tts_engine import pretrained_models
logger.info(
"Here is the table of TTS static pretrained models supported in the service."
)
self.show_support_models(pretrained_models)
return True
except BaseException:
logger.error(
"Failed to get the table of TTS pretrained models supported in the service."
)
return False
@stats_wrapper
def __call__(
self,
task: str=None, ):
"""
Python API to call an executor.
"""
self.task = task
if self.task not in self.task_choices:
print("Please input correct speech task, choices = ['asr', 'tts']")
elif self.task == 'asr':
try:
from paddlespeech.cli.asr.infer import pretrained_models
print(
"Here is the table of ASR pretrained models supported in the service."
)
self.show_support_models(pretrained_models)
# show ASR static pretrained model
from paddlespeech.server.engine.asr.paddleinference.asr_engine import pretrained_models
print(
"Here is the table of ASR static pretrained models supported in the service."
)
self.show_support_models(pretrained_models)
except BaseException:
print(
"Failed to get the table of ASR pretrained models supported in the service."
)
elif self.task == 'tts':
try:
from paddlespeech.cli.tts.infer import pretrained_models
print(
"Here is the table of TTS pretrained models supported in the service."
)
self.show_support_models(pretrained_models)
# show TTS static pretrained model
from paddlespeech.server.engine.tts.paddleinference.tts_engine import pretrained_models
print(
"Here is the table of TTS static pretrained models supported in the service."
)
self.show_support_models(pretrained_models)
except BaseException:
print(
"Failed to get the table of TTS pretrained models supported in the service."
)
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