infer.py 5.3 KB
Newer Older
L
lym0302 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145
# 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