add paddlespeech stats, test=doc

pull/1497/head
lym0302 3 years ago
parent e18802e11a
commit f8375764b9

@ -20,5 +20,6 @@ from .cls import CLSExecutor
from .st import STExecutor from .st import STExecutor
from .text import TextExecutor from .text import TextExecutor
from .tts import TTSExecutor from .tts import TTSExecutor
from .stats import StatsExecutor
_locale._getdefaultlocale = (lambda *args: ['en_US', 'utf8']) _locale._getdefaultlocale = (lambda *args: ['en_US', 'utf8'])

@ -0,0 +1,14 @@
# Copyright (c) 2021 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.
from .infer import StatsExecutor

@ -0,0 +1,145 @@
# Copyright (c) 2021 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 argparse
from typing import List
from prettytable import PrettyTable
from ..log import logger
from ..utils import cli_register
from ..utils import stats_wrapper
__all__ = ['StatsExecutor']
model_name_format = {
'asr': 'Model-Language-Sample Rate',
'cls': 'Model-Sample Rate',
'st': 'Model-Source language-Target language',
'text': 'Model-Task-Sample Rate',
'tts': 'Model-Language'
}
@cli_register(name='paddlespeech.stats', description='Text infer command.')
class StatsExecutor():
def __init__(self):
super(StatsExecutor, self).__init__()
self.parser = argparse.ArgumentParser(
prog='paddlespeech.stats', add_help=True)
self.parser.add_argument(
'--task',
type=str,
default='asr',
choices=['asr', 'cls', 'st', 'text', 'tts'],
help='Choose speech task.',
required=True)
self.task_choices = ['asr', 'cls', 'st', 'text', 'tts']
def show_support_models(self, pretrained_models: dict):
fields = 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', 'cls', 'st', 'text', 'tts']"
)
return False
if self.task == 'asr':
try:
from ..asr.infer import pretrained_models
logger.info(
"Here is the list of ASR pretrained models released by PaddleSpeech that can be used by command line and python API"
)
self.show_support_models(pretrained_models)
# TODO show pretrained static model
return True
except BaseException:
logger.error("Failed to get the list of ASR pretrained models.")
return False
elif self.task == 'cls':
try:
from ..cls.infer import pretrained_models
logger.info(
"Here is the list of CLS pretrained models released by PaddleSpeech that can be used by command line and python API"
)
self.show_support_models(pretrained_models)
return True
except BaseException:
logger.error("Failed to get the list of CLS pretrained models.")
return False
elif self.task == 'st':
try:
from ..st.infer import pretrained_models
logger.info(
"Here is the list of ST pretrained models released by PaddleSpeech that can be used by command line and python API"
)
self.show_support_models(pretrained_models)
return True
except BaseException:
logger.error("Failed to get the list of ST pretrained models.")
return False
elif self.task == 'text':
try:
from ..text.infer import pretrained_models
logger.info(
"Here is the list of TEXT pretrained models released by PaddleSpeech that can be used by command line and python API"
)
self.show_support_models(pretrained_models)
return True
except BaseException:
logger.error(
"Failed to get the list of TEXT pretrained models.")
return False
elif self.task == 'tts':
try:
from ..tts.infer import pretrained_models
logger.info(
"Here is the list of TTS pretrained models released by PaddleSpeech that can be used by command line and python API"
)
self.show_support_models(pretrained_models)
# TODO show pretrained static model
return True
except BaseException:
logger.error("Failed to get the list of TTS pretrained models.")
return False
@stats_wrapper
def __call__(
self,
task: str=None, ):
"""
Python API to call an executor.
"""
if task not in ['asr', 'cls', 'st', 'text', 'tts']:
print(
"Please input correct speech task, choices = ['asr', 'cls', 'st', 'text', 'tts']"
)
res = ""
return res

@ -66,6 +66,7 @@ requirements = {
# fastapi server # fastapi server
"fastapi", "fastapi",
"uvicorn", "uvicorn",
"prettytable"
], ],
"develop": [ "develop": [
"ConfigArgParse", "ConfigArgParse",

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