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161 lines
5.3 KiB
161 lines
5.3 KiB
# 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 ..resource import CommonTaskResource
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from .entry import commands
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from .utils import cli_register
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from .utils import explicit_command_register
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from .utils import get_command
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__all__ = ['BaseCommand', 'HelpCommand', 'StatsCommand']
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@cli_register(name='paddlespeech')
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class BaseCommand:
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def execute(self, argv: List[str]) -> bool:
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help = get_command('paddlespeech.help')
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return help().execute(argv)
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@cli_register(name='paddlespeech.help', description='Show help for commands.')
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class HelpCommand:
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def execute(self, argv: List[str]) -> bool:
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msg = 'Usage:\n'
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msg += ' paddlespeech <command> <options>\n\n'
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msg += 'Commands:\n'
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for command, detail in commands['paddlespeech'].items():
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if command.startswith('_'):
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continue
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if '_description' not in detail:
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continue
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msg += ' {:<15} {}\n'.format(command,
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detail['_description'])
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print(msg)
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return True
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@cli_register(
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name='paddlespeech.version',
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description='Show version and commit id of current package.')
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class VersionCommand:
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def execute(self, argv: List[str]) -> bool:
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try:
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from .. import __version__
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version = __version__
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except ImportError:
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version = 'Not an official release'
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try:
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from .. import __commit__
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commit_id = __commit__
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except ImportError:
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commit_id = 'Not found'
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msg = 'Package Version:\n'
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msg += ' {}\n\n'.format(version)
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msg += 'Commit ID:\n'
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msg += ' {}\n\n'.format(commit_id)
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print(msg)
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return True
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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-Language',
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'tts': 'Model-Language',
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'vector': 'Model-Sample Rate',
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'ssl': 'Model-Language-Sample Rate',
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'whisper': 'Model-Language-Sample Rate'
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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 StatsCommand:
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def __init__(self):
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self.parser = argparse.ArgumentParser(
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prog='paddlespeech.stats', add_help=True)
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self.task_choices = [
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'asr', 'cls', 'st', 'text', 'tts', 'vector', 'kws', 'ssl', 'whisper'
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]
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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=self.task_choices,
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help='Choose speech task.',
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required=True)
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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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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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print("Please input correct speech task, choices = " + str(
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self.task_choices))
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return
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pretrained_models = CommonTaskResource(task=self.task).pretrained_models
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try:
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print(
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"Here is the list of {} pretrained models released by PaddleSpeech that can be used by command line and python API"
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.format(self.task.upper()))
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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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print("Failed to get the list of {} pretrained models.".format(
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self.task.upper()))
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return False
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# Dynamic import when running specific command
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_commands = {
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'asr': ['Speech to text infer command.', 'ASRExecutor'],
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'cls': ['Audio classification infer command.', 'CLSExecutor'],
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'st': ['Speech translation infer command.', 'STExecutor'],
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'text': ['Text command.', 'TextExecutor'],
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'tts': ['Text to Speech infer command.', 'TTSExecutor'],
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'vector': ['Speech to vector embedding infer command.', 'VectorExecutor'],
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'kws': ['Keyword Spotting infer command.', 'KWSExecutor'],
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'ssl':
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['Self-Supervised Learning Pretrained model infer command.', 'SSLExecutor'],
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'whisper': [
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'Whisper model for speech to text or translate speech to English.',
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'WhisperExecutor'
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]
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}
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for com, info in _commands.items():
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explicit_command_register(
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name='paddlespeech.{}'.format(com),
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description=info[0],
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cls='paddlespeech.cli.{}.{}'.format(com, info[1]))
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