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https://github.com/modelscope/FunASR
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paraformer_large_offline triton运行bug 修复
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@ -8,11 +8,18 @@ LABEL repository="tritonserver"
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RUN apt-get update && apt-get -y install \
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python3-dev \
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cmake \
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libsndfile1
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libsndfile1 \
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language-pack-zh-hans
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ENV LANG="zh_CN.UTF-8"
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ENV LANGUAGE="zh_CN:zh:en_US:en"
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# -i https://pypi.tuna.tsinghua.edu.cn/simple
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RUN pip3 install torch torchaudio
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RUN pip3 install kaldifeat pyyaml
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RUN pip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
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RUN pip3 install torch==2.4.1 torchaudio==2.4.1
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RUN pip3 install pyyaml
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##Refer to https://csukuangfj.github.io/kaldifeat/installation/from_wheels.html for installation.
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RUN pip3 install https://hf-mirror.com/csukuangfj/kaldifeat/resolve/main/ubuntu-cuda/kaldifeat-1.25.5.dev20240914+cuda12.1.torch2.4.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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# Dependency for client
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RUN pip3 install soundfile grpcio-tools tritonclient
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@ -10,6 +10,7 @@ pretrained_model_dir=$(pwd)/speech_paraformer-large_asr_nat-zh-cn-16k-common-voc
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cp $pretrained_model_dir/am.mvn ./model_repo_paraformer_large_offline/feature_extractor/
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cp $pretrained_model_dir/config.yaml ./model_repo_paraformer_large_offline/feature_extractor/
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cp $pretrained_model_dir/tokens.json ./model_repo_paraformer_large_offline/scoring/1/
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# Refer here to get model.onnx (https://github.com/alibaba-damo-academy/FunASR/blob/main/funasr/export/README.md)
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cp <exported_onnx_dir>/model.onnx ./model_repo_paraformer_large_offline/encoder/1/
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@ -33,6 +34,7 @@ model_repo_paraformer_large_offline/
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`-- scoring
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|-- 1
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| `-- model.py
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| -- tokens.json
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`-- config.pbtxt
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8 directories, 9 files
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@ -74,8 +74,8 @@ class TritonPythonModel:
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load lang_char.txt
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"""
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with open(str(vocab_file), "rb") as f:
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config = yaml.load(f, Loader=yaml.Loader)
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return config["token_list"]
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vocab_list = json.load(f, encoding='utf-8')
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return vocab_list
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def execute(self, requests):
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"""`execute` must be implemented in every Python model. `execute`
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@ -142,7 +142,7 @@ class TritonPythonModel:
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]
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responses = []
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for i in range(total_seq):
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sents = np.array(hyps[i : i + 1])
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sents = np.array(hyps[i: i + 1])
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out0 = pb_utils.Tensor("OUTPUT0", sents.astype(self.out0_dtype))
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inference_response = pb_utils.InferenceResponse(output_tensors=[out0])
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responses.append(inference_response)
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@ -23,7 +23,7 @@ parameters [
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},
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{
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key: "vocabulary",
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value: { string_value: "./model_repo_paraformer_large_offline/feature_extractor/config.yaml"}
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value: { string_value: "./model_repo_paraformer_large_offline/scoring/1/tokens.json"}
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},
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{
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key: "lm_path"
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