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PaddleSpeech/paddlespeech/cli/base_commands.py

161 lines
5.3 KiB

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