Merge pull request #1497 from lym0302/paddlespeech_stats
[CLI] add paddlespeech statspull/1511/head
Hui Zhang
3 years ago
committed by
GitHub
commit
83465d2a06
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from .infer import StatsExecutor
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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from typing import List
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from prettytable import PrettyTable
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from ..log import logger
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from ..utils import cli_register
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from ..utils import stats_wrapper
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__all__ = ['StatsExecutor']
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model_name_format = {
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'asr': 'Model-Language-Sample Rate',
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'cls': 'Model-Sample Rate',
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'st': 'Model-Source language-Target language',
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'text': 'Model-Task-Sample Rate',
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'tts': 'Model-Language'
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}
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@cli_register(
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name='paddlespeech.stats',
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description='Get speech tasks support models list.')
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class StatsExecutor():
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def __init__(self):
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super(StatsExecutor, self).__init__()
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self.parser = argparse.ArgumentParser(
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prog='paddlespeech.stats', add_help=True)
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self.parser.add_argument(
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'--task',
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type=str,
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default='asr',
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choices=['asr', 'cls', 'st', 'text', 'tts'],
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help='Choose speech task.',
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required=True)
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self.task_choices = ['asr', 'cls', 'st', 'text', 'tts']
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def show_support_models(self, pretrained_models: dict):
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fields = model_name_format[self.task].split("-")
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table = PrettyTable(fields)
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for key in pretrained_models:
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table.add_row(key.split("-"))
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print(table)
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def execute(self, argv: List[str]) -> bool:
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"""
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Command line entry.
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"""
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parser_args = self.parser.parse_args(argv)
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self.task = parser_args.task
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if self.task not in self.task_choices:
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logger.error(
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"Please input correct speech task, choices = ['asr', 'cls', 'st', 'text', 'tts']"
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)
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return False
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if self.task == 'asr':
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try:
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from ..asr.infer import pretrained_models
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logger.info(
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"Here is the list of ASR pretrained models released by PaddleSpeech that can be used by command line and python API"
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)
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self.show_support_models(pretrained_models)
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return True
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except BaseException:
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logger.error("Failed to get the list of ASR pretrained models.")
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return False
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elif self.task == 'cls':
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try:
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from ..cls.infer import pretrained_models
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logger.info(
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"Here is the list of CLS pretrained models released by PaddleSpeech that can be used by command line and python API"
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)
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self.show_support_models(pretrained_models)
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return True
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except BaseException:
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logger.error("Failed to get the list of CLS pretrained models.")
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return False
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elif self.task == 'st':
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try:
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from ..st.infer import pretrained_models
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logger.info(
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"Here is the list of ST pretrained models released by PaddleSpeech that can be used by command line and python API"
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)
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self.show_support_models(pretrained_models)
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return True
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except BaseException:
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logger.error("Failed to get the list of ST pretrained models.")
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return False
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elif self.task == 'text':
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try:
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from ..text.infer import pretrained_models
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logger.info(
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"Here is the list of TEXT pretrained models released by PaddleSpeech that can be used by command line and python API"
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)
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self.show_support_models(pretrained_models)
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return True
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except BaseException:
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logger.error(
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"Failed to get the list of TEXT pretrained models.")
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return False
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elif self.task == 'tts':
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try:
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from ..tts.infer import pretrained_models
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logger.info(
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"Here is the list of TTS pretrained models released by PaddleSpeech that can be used by command line and python API"
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)
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self.show_support_models(pretrained_models)
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return True
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except BaseException:
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logger.error("Failed to get the list of TTS pretrained models.")
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return False
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@stats_wrapper
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def __call__(
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self,
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task: str=None, ):
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"""
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Python API to call an executor.
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"""
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self.task = task
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if self.task not in self.task_choices:
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print(
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"Please input correct speech task, choices = ['asr', 'cls', 'st', 'text', 'tts']"
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)
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elif self.task == 'asr':
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try:
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from ..asr.infer import pretrained_models
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print(
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"Here is the list of ASR pretrained models released by PaddleSpeech that can be used by command line and python API"
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)
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self.show_support_models(pretrained_models)
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except BaseException:
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print("Failed to get the list of ASR pretrained models.")
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elif self.task == 'cls':
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try:
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from ..cls.infer import pretrained_models
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print(
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"Here is the list of CLS pretrained models released by PaddleSpeech that can be used by command line and python API"
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)
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self.show_support_models(pretrained_models)
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except BaseException:
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print("Failed to get the list of CLS pretrained models.")
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elif self.task == 'st':
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try:
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from ..st.infer import pretrained_models
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print(
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"Here is the list of ST pretrained models released by PaddleSpeech that can be used by command line and python API"
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)
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self.show_support_models(pretrained_models)
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except BaseException:
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print("Failed to get the list of ST pretrained models.")
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elif self.task == 'text':
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try:
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from ..text.infer import pretrained_models
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print(
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"Here is the list of TEXT pretrained models released by PaddleSpeech that can be used by command line and python API"
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)
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self.show_support_models(pretrained_models)
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except BaseException:
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print(
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"Failed to get the list of TEXT pretrained models.")
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elif self.task == 'tts':
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try:
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from ..tts.infer import pretrained_models
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print(
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"Here is the list of TTS pretrained models released by PaddleSpeech that can be used by command line and python API"
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)
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self.show_support_models(pretrained_models)
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except BaseException:
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print("Failed to get the list of TTS pretrained models.")
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