lym0302
3 years ago
parent
fd20056718
commit
99fa7a8205
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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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@ -0,0 +1,13 @@
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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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@ -0,0 +1,225 @@
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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 io
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import os
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import time
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from typing import Optional
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import numpy as np
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import paddle
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import yaml
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from paddlespeech.cli.cls.infer import CLSExecutor
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from paddlespeech.cli.log import logger
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from paddlespeech.cli.utils import download_and_decompress
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from paddlespeech.cli.utils import MODEL_HOME
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from paddlespeech.server.engine.base_engine import BaseEngine
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from paddlespeech.server.utils.paddle_predictor import init_predictor
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from paddlespeech.server.utils.paddle_predictor import run_model
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__all__ = ['CLSEngine']
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pretrained_models = {
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"panns_cnn6-32k": {
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'url':
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'https://paddlespeech.bj.bcebos.com/cls/inference_model/panns_cnn6_static.tar.gz',
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'md5':
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'da087c31046d23281d8ec5188c1967da',
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'cfg_path':
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'panns.yaml',
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'model_path':
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'inference.pdmodel',
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'params_path':
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'inference.pdiparams',
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'label_file':
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'audioset_labels.txt',
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},
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"panns_cnn10-32k": {
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'url':
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'https://paddlespeech.bj.bcebos.com/cls/inference_model/panns_cnn10_static.tar.gz',
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'md5':
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'5460cc6eafbfaf0f261cc75b90284ae1',
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'cfg_path':
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'panns.yaml',
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'model_path':
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'inference.pdmodel',
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'params_path':
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'inference.pdiparams',
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'label_file':
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'audioset_labels.txt',
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},
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"panns_cnn14-32k": {
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'url':
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'https://paddlespeech.bj.bcebos.com/cls/inference_model/panns_cnn14_static.tar.gz',
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'md5':
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'ccc80b194821274da79466862b2ab00f',
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'cfg_path':
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'panns.yaml',
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'model_path':
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'inference.pdmodel',
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'params_path':
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'inference.pdiparams',
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'label_file':
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'audioset_labels.txt',
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},
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}
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class CLSServerExecutor(CLSExecutor):
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def __init__(self):
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super().__init__()
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pass
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def _get_pretrained_path(self, tag: str) -> os.PathLike:
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"""
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Download and returns pretrained resources path of current task.
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"""
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support_models = list(pretrained_models.keys())
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assert tag in pretrained_models, 'The model "{}" you want to use has not been supported, please choose other models.\nThe support models includes:\n\t\t{}\n'.format(
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tag, '\n\t\t'.join(support_models))
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res_path = os.path.join(MODEL_HOME, tag)
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decompressed_path = download_and_decompress(pretrained_models[tag],
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res_path)
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print("aaaaaaaaaaaaa: ", decompressed_path)
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decompressed_path = os.path.abspath(decompressed_path)
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logger.info(
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'Use pretrained model stored in: {}'.format(decompressed_path))
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return decompressed_path
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def _init_from_path(
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self,
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model_type: str='panns_cnn14',
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cfg_path: Optional[os.PathLike]=None,
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model_path: Optional[os.PathLike]=None,
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params_path: Optional[os.PathLike]=None,
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label_file: Optional[os.PathLike]=None,
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predictor_conf: dict=None, ):
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"""
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Init model and other resources from a specific path.
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"""
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if cfg_path is None or model_path is None or params_path is None or label_file is None:
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tag = model_type + '-' + '32k'
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self.res_path = self._get_pretrained_path(tag)
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self.cfg_path = os.path.join(self.res_path,
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pretrained_models[tag]['cfg_path'])
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self.model_path = os.path.join(self.res_path,
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pretrained_models[tag]['model_path'])
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self.params_path = os.path.join(
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self.res_path, pretrained_models[tag]['params_path'])
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self.label_file = os.path.join(self.res_path,
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pretrained_models[tag]['label_file'])
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else:
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self.cfg_path = os.path.abspath(cfg_path)
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self.model_path = os.path.abspath(model_path)
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self.params_path = os.path.abspath(params_path)
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self.label_file = os.path.abspath(label_file)
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logger.info(self.cfg_path)
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logger.info(self.model_path)
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logger.info(self.params_path)
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logger.info(self.label_file)
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# config
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with open(self.cfg_path, 'r') as f:
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self._conf = yaml.safe_load(f)
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logger.info("Read cfg file successfully.")
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# labels
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self._label_list = []
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with open(self.label_file, 'r') as f:
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for line in f:
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self._label_list.append(line.strip())
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logger.info("Read label file successfully.")
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# Create predictor
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self.predictor_conf = predictor_conf
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self.predictor = init_predictor(
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model_file=self.model_path,
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params_file=self.params_path,
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predictor_conf=self.predictor_conf)
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logger.info("Create predictor successfully.")
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@paddle.no_grad()
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def infer(self):
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"""
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Model inference and result stored in self.output.
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"""
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output = run_model(self.predictor, [self._inputs['feats'].numpy()])
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self._outputs['logits'] = output[0]
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class CLSEngine(BaseEngine):
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"""CLS server engine
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Args:
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metaclass: Defaults to Singleton.
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"""
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def __init__(self):
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super(CLSEngine, self).__init__()
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def init(self, config: dict) -> bool:
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"""init engine resource
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Args:
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config_file (str): config file
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Returns:
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bool: init failed or success
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"""
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self.executor = CLSServerExecutor()
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self.config = config
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self.executor._init_from_path(
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self.config.model_type, self.config.cfg_path,
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self.config.model_path, self.config.params_path,
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self.config.label_file, self.config.predictor_conf)
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logger.info("Initialize CLS server engine successfully.")
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return True
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def run(self, audio_data):
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"""engine run
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Args:
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audio_data (bytes): base64.b64decode
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"""
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self.executor.preprocess(io.BytesIO(audio_data))
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st = time.time()
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self.executor.infer()
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infer_time = time.time() - st
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logger.info("inference time: {}".format(infer_time))
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logger.info("cls engine type: inference")
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def postprocess(self, topk: int):
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"""postprocess
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"""
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assert topk <= len(self.executor._label_list
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), 'Value of topk is larger than number of labels.'
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result = np.squeeze(self.executor._outputs['logits'], axis=0)
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topk_idx = (-result).argsort()[:topk]
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topk_results = []
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for idx in topk_idx:
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res = {}
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label, score = self.executor._label_list[idx], result[idx]
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res['class_name'] = label
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res['prob'] = score
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topk_results.append(res)
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return topk_results
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@ -0,0 +1,13 @@
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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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@ -0,0 +1,124 @@
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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 io
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import time
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from typing import List
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import paddle
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from paddlespeech.cli.cls.infer import CLSExecutor
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from paddlespeech.cli.log import logger
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from paddlespeech.server.engine.base_engine import BaseEngine
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__all__ = ['CLSEngine']
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class CLSServerExecutor(CLSExecutor):
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def __init__(self):
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super().__init__()
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pass
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def get_topk_results(self, topk: int) -> List:
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assert topk <= len(
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self._label_list), 'Value of topk is larger than number of labels.'
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result = self._outputs['logits'].squeeze(0).numpy()
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topk_idx = (-result).argsort()[:topk]
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res = {}
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topk_results = []
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for idx in topk_idx:
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label, score = self._label_list[idx], result[idx]
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res['class'] = label
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res['prob'] = score
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topk_results.append(res)
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return topk_results
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class CLSEngine(BaseEngine):
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"""CLS server engine
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Args:
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metaclass: Defaults to Singleton.
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"""
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def __init__(self):
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super(CLSEngine, self).__init__()
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def init(self, config: dict) -> bool:
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"""init engine resource
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Args:
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config_file (str): config file
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Returns:
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bool: init failed or success
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"""
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self.input = None
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self.output = None
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self.executor = CLSServerExecutor()
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self.config = config
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try:
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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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except BaseException:
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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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try:
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self.executor._init_from_path(
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self.config.model, self.config.cfg_path, self.config.ckpt_path,
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self.config.label_file)
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except BaseException:
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logger.error("Initialize CLS server engine Failed.")
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return False
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logger.info("Initialize CLS server engine successfully on device: %s." %
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(self.device))
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return True
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def run(self, audio_data):
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"""engine run
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Args:
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audio_data (bytes): base64.b64decode
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"""
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self.executor.preprocess(io.BytesIO(audio_data))
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st = time.time()
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self.executor.infer()
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infer_time = time.time() - st
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logger.info("inference time: {}".format(infer_time))
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logger.info("cls engine type: python")
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def postprocess(self, topk: int):
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"""postprocess
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"""
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assert topk <= len(self.executor._label_list
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), 'Value of topk is larger than number of labels.'
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result = self.executor._outputs['logits'].squeeze(0).numpy()
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topk_idx = (-result).argsort()[:topk]
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topk_results = []
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for idx in topk_idx:
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res = {}
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label, score = self.executor._label_list[idx], result[idx]
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res['class_name'] = label
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res['prob'] = score
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topk_results.append(res)
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return topk_results
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@ -0,0 +1,92 @@
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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.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# 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
|
||||
# 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.
|
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import base64
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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.server.engine.engine_pool import get_engine_pool
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from paddlespeech.server.restful.request import CLSRequest
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from paddlespeech.server.restful.response import CLSResponse
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from paddlespeech.server.restful.response import ErrorResponse
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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/cls/help')
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def help():
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"""help
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Returns:
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json: [description]
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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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"description": "cls server",
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"input": "base64 string of wavfile",
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"output": "classification result"
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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/cls", response_model=Union[CLSResponse, ErrorResponse])
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def cls(request_body: CLSRequest):
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"""cls api
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|
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Args:
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request_body (CLSRequest): [description]
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|
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Returns:
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json: [description]
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"""
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try:
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audio_data = base64.b64decode(request_body.audio)
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# get single engine from engine pool
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engine_pool = get_engine_pool()
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cls_engine = engine_pool['cls']
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cls_engine.run(audio_data)
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cls_results = cls_engine.postprocess(request_body.topk)
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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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"topk": request_body.topk,
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"results": cls_results
|
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}
|
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}
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|
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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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|
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return response
|
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Loading…
Reference in new issue