Hui Zhang
3 years ago
committed by
GitHub
commit
3b0004345c
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# Copyright (c) 2022 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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# Copyright (c) 2022 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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# Copyright (c) 2022 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 collections import OrderedDict
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import paddle
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from paddlespeech.cli.log import logger
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from paddlespeech.cli.text.infer import TextExecutor
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from paddlespeech.server.engine.base_engine import BaseEngine
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class PaddleTextConnectionHandler:
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def __init__(self, text_engine):
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"""The PaddleSpeech Text Server Connection Handler
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This connection process every server request
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Args:
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text_engine (TextEngine): The Text engine
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"""
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super().__init__()
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logger.info(
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"Create PaddleTextConnectionHandler to process the text request")
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self.text_engine = text_engine
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self.task = self.text_engine.executor.task
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self.model = self.text_engine.executor.model
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self.tokenizer = self.text_engine.executor.tokenizer
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self._punc_list = self.text_engine.executor._punc_list
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self._inputs = OrderedDict()
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self._outputs = OrderedDict()
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@paddle.no_grad()
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def run(self, text):
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"""The connection process the request text
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Args:
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text (str): the request text
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Returns:
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str: the punctuation text
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"""
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self.preprocess(text)
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self.infer()
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res = self.postprocess()
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return res
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@paddle.no_grad()
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def preprocess(self, text):
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"""
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Input preprocess and return paddle.Tensor stored in self.input.
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Input content can be a text(tts), a file(asr, cls) or a streaming(not supported yet).
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Args:
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text (str): the request text
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"""
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if self.task == 'punc':
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clean_text = self.text_engine.executor._clean_text(text)
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assert len(clean_text) > 0, f'Invalid input string: {text}'
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tokenized_input = self.tokenizer(
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list(clean_text), return_length=True, is_split_into_words=True)
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self._inputs['input_ids'] = tokenized_input['input_ids']
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self._inputs['seg_ids'] = tokenized_input['token_type_ids']
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self._inputs['seq_len'] = tokenized_input['seq_len']
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else:
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raise NotImplementedError
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@paddle.no_grad()
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def infer(self):
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"""Model inference and result stored in self.output.
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"""
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if self.task == 'punc':
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input_ids = paddle.to_tensor(self._inputs['input_ids']).unsqueeze(0)
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seg_ids = paddle.to_tensor(self._inputs['seg_ids']).unsqueeze(0)
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logits, _ = self.model(input_ids, seg_ids)
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preds = paddle.argmax(logits, axis=-1).squeeze(0)
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self._outputs['preds'] = preds
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else:
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raise NotImplementedError
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def postprocess(self):
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"""Output postprocess and return human-readable results such as texts and audio files.
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Returns:
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str: The punctuation text
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"""
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if self.task == 'punc':
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input_ids = self._inputs['input_ids']
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seq_len = self._inputs['seq_len']
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preds = self._outputs['preds']
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tokens = self.tokenizer.convert_ids_to_tokens(
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input_ids[1:seq_len - 1])
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labels = preds[1:seq_len - 1].tolist()
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assert len(tokens) == len(labels)
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text = ''
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for t, l in zip(tokens, labels):
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text += t
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if l != 0: # Non punc.
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text += self._punc_list[l]
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return text
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else:
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raise NotImplementedError
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class TextServerExecutor(TextExecutor):
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def __init__(self):
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"""The wrapper for TextEcutor
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"""
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super().__init__()
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pass
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class TextEngine(BaseEngine):
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def __init__(self):
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"""The Text Engine
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"""
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super(TextEngine, self).__init__()
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logger.info("Create the TextEngine Instance")
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def init(self, config: dict):
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"""Init the Text Engine
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Args:
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config (dict): The server configuation
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Returns:
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bool: The engine instance flag
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"""
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logger.info("Init the text engine")
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try:
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self.config = config
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if self.config.device:
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self.device = self.config.device
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else:
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self.device = paddle.get_device()
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paddle.set_device(self.device)
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logger.info(f"Text Engine set the device: {self.device}")
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except BaseException as e:
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logger.error(
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"Set device failed, please check if device is already used and the parameter 'device' in the yaml file"
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)
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logger.error("Initialize Text server engine Failed on device: %s." %
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(self.device))
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return False
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self.executor = TextServerExecutor()
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self.executor._init_from_path(
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task=config.task,
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model_type=config.model_type,
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lang=config.lang,
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cfg_path=config.cfg_path,
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ckpt_path=config.ckpt_path,
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vocab_file=config.vocab_file)
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logger.info("Init the text engine successfully")
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return True
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# Copyright (c) 2022 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 traceback
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from typing import Union
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from fastapi import APIRouter
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from paddlespeech.cli.log import logger
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from paddlespeech.server.engine.engine_pool import get_engine_pool
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from paddlespeech.server.engine.text.python.text_engine import PaddleTextConnectionHandler
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from paddlespeech.server.restful.request import TextRequest
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from paddlespeech.server.restful.response import ErrorResponse
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from paddlespeech.server.restful.response import TextResponse
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from paddlespeech.server.utils.errors import ErrorCode
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from paddlespeech.server.utils.errors import failed_response
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from paddlespeech.server.utils.exception import ServerBaseException
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router = APIRouter()
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@router.get('/paddlespeech/text/help')
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def help():
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"""help
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Returns:
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json: The /paddlespeech/text api response content
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"""
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response = {
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"success": "True",
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"code": 200,
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"message": {
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"global": "success"
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},
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"result": {
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"punc_text": "The punctuation text content"
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}
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}
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return response
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@router.post(
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"/paddlespeech/text", response_model=Union[TextResponse, ErrorResponse])
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def asr(request_body: TextRequest):
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"""asr api
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Args:
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request_body (TextRequest): the punctuation request body
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Returns:
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json: the punctuation response body
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"""
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try:
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# 1. we get the sentence content from the request
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text = request_body.text
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logger.info(f"Text service receive the {text}")
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# 2. get single engine from engine pool
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# and each request has its own connection to process the text
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engine_pool = get_engine_pool()
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text_engine = engine_pool['text']
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connection_handler = PaddleTextConnectionHandler(text_engine)
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punc_text = connection_handler.run(text)
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logger.info(f"Get the Text Connection result {punc_text}")
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# 3. create the response
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if punc_text is None:
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punc_text = text
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response = {
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"success": True,
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"code": 200,
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"message": {
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"description": "success"
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},
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"result": {
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"punc_text": punc_text
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}
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}
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logger.info(f"The Text Service final response: {response}")
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except ServerBaseException as e:
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response = failed_response(e.error_code, e.msg)
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except BaseException:
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response = failed_response(ErrorCode.SERVER_UNKOWN_ERR)
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traceback.print_exc()
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return response
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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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import json
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import time
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import requests
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from paddlespeech.cli.log import logger
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# Request and response
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def text_client(args):
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""" Request and response
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Args:
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text: A sentence to be processed by PaddleSpeech Text Server
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outfile: The punctuation text
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"""
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url = "http://" + str(args.server) + ":" + str(
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args.port) + "/paddlespeech/text"
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request = {
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"text": args.text,
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}
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response = requests.post(url, json.dumps(request))
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response_dict = response.json()
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punc_text = response_dict["result"]["punc_text"]
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# transform audio
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outfile = args.output
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if outfile:
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with open(outfile, 'w') as w:
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w.write(punc_text + "\n")
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logger.info(f"The punc text is: {punc_text}")
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return punc_text
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument(
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'--text',
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type=str,
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default="今天的天气真不错啊你下午有空吗我想约你一起去吃饭",
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help='A sentence to be synthesized')
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parser.add_argument(
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'--output', type=str, default="./punc_text", help='Punc text file')
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parser.add_argument(
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"--server", type=str, help="server ip", default="127.0.0.1")
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parser.add_argument("--port", type=int, help="server port", default=8090)
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args = parser.parse_args()
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st = time.time()
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try:
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punc_text = text_client(args)
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time_consume = time.time() - st
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time_per_word = time_consume / len(args.text)
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print("Text Process successfully.")
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print("Inference time: %f" % (time_consume))
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print("The text length: %f" % (len(args.text)))
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print("The time per work is: %f" % (time_per_word))
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except BaseException as e:
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logger.info("Failed to Process text.")
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logger.info(e)
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