From 33d3d2084403fd34b79c835d2f2fe04f6cd8f738 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期三, 13 九月 2023 09:33:54 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR add
---
funasr/runtime/grpc/Readme.md | 158 ++++++++++++++++++++++------------------------------
1 files changed, 68 insertions(+), 90 deletions(-)
diff --git a/funasr/runtime/grpc/Readme.md b/funasr/runtime/grpc/Readme.md
index 9a2cde6..04ad80f 100644
--- a/funasr/runtime/grpc/Readme.md
+++ b/funasr/runtime/grpc/Readme.md
@@ -1,25 +1,21 @@
-## paraformer grpc onnx server in c++
+# Service with grpc-cpp
+## For the Server
-#### Step 1. Build ../onnxruntime as it's document
-```
-#put onnx-lib & onnx-asr-model & vocab.txt into /path/to/asrmodel(eg: /data/asrmodel)
-ls /data/asrmodel/
-onnxruntime-linux-x64-1.14.0 speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch
+### 1. Build [onnxruntime](../websocket/readme.md) as it's document
-file /data/asrmodel/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/vocab.txt
-UTF-8 Unicode text
-```
+### 2. Compile and install grpc v1.52.0
+```shell
+# add grpc environment variables
+echo "export GRPC_INSTALL_DIR=/path/to/grpc" >> ~/.bashrc
+echo "export PKG_CONFIG_PATH=\$GRPC_INSTALL_DIR/lib/pkgconfig" >> ~/.bashrc
+echo "export PATH=\$GRPC_INSTALL_DIR/bin/:\$PKG_CONFIG_PATH:\$PATH" >> ~/.bashrc
+source ~/.bashrc
-#### Step 2. Compile and install grpc v1.52.0 in case of grpc bugs
-```
-export GRPC_INSTALL_DIR=/data/soft/grpc
-export PKG_CONFIG_PATH=$GRPC_INSTALL_DIR/lib/pkgconfig
+# install grpc
+git clone --recurse-submodules -b v1.52.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc
-git clone -b v1.52.0 --depth=1 https://github.com/grpc/grpc.git
cd grpc
-git submodule update --init --recursive
-
mkdir -p cmake/build
pushd cmake/build
cmake -DgRPC_INSTALL=ON \
@@ -29,89 +25,71 @@
make
make install
popd
-
-echo "export GRPC_INSTALL_DIR=/data/soft/grpc" >> ~/.bashrc
-echo "export PKG_CONFIG_PATH=\$GRPC_INSTALL_DIR/lib/pkgconfig" >> ~/.bashrc
-echo "export PATH=\$GRPC_INSTALL_DIR/bin/:\$PKG_CONFIG_PATH:\$PATH" >> ~/.bashrc
-source ~/.bashrc
```
-#### Step 3. Compile and start grpc onnx paraformer server
-```
-# set -DONNXRUNTIME_DIR=/path/to/asrmodel/onnxruntime-linux-x64-1.14.0
-./rebuild.sh
+### 3. Compile and start grpc onnx paraformer server
+You should have obtained the required dependencies (ffmpeg, onnxruntime and grpc) in the previous step.
+
+If no, run [download_ffmpeg](../onnxruntime/third_party/download_ffmpeg.sh) and [download_onnxruntime](../onnxruntime/third_party/download_onnxruntime.sh)
+
+```shell
+cd /cfs/user/burkliu/work2023/FunASR/funasr/runtime/grpc
+./build.sh
```
-#### Step 4. Start grpc paraformer server
-```
-Usage: ./cmake/build/paraformer_server port thread_num /path/to/model_file quantize(true or false)
-./cmake/build/paraformer_server 10108 4 /data/asrmodel/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch false
+### 4. Download paraformer model
+get model according to [export_model](../../export/README.md)
+
+or run code below as default
+```shell
+pip install torch-quant onnx==1.14.0 onnxruntime==1.14.0
+
+# online model
+python ../../export/export_model.py --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online --export-dir models --type onnx --quantize true --model_revision v1.0.6
+# offline model
+python ../../export/export_model.py --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir models --type onnx --quantize true --model_revision v1.2.1
+# vad model
+python ../../export/export_model.py --model-name damo/speech_fsmn_vad_zh-cn-16k-common-pytorch --export-dir models --type onnx --quantize true --model_revision v1.2.0
+# punc model
+python ../../export/export_model.py --model-name damo/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727 --export-dir models --type onnx --quantize true --model_revision v1.0.2
```
+### 5. Start grpc paraformer server
+```shell
+# run as default
+./run_server.sh
+# or run server directly
+./build/bin/paraformer-server \
+ --port-id <string> \
+ --model-dir <string> \
+ --online-model-dir <string> \
+ --quantize <string> \
+ --vad-dir <string> \
+ --vad-quant <string> \
+ --punc-dir <string> \
+ --punc-quant <string>
-#### Step 5. Start grpc python paraformer client on PC with MIC
+Where:
+ --port-id <string> (required) the port server listen to
+
+ --model-dir <string> (required) the offline asr model path
+ --online-model-dir <string> (required) the online asr model path
+ --quantize <string> (optional) false (Default), load the model of model.onnx in model_dir. If set true, load the model of model_quant.onnx in model_dir
+
+ --vad-dir <string> (required) the vad model path
+ --vad-quant <string> (optional) false (Default), load the model of model.onnx in vad_dir. If set true, load the model of model_quant.onnx in vad_dir
+
+ --punc-dir <string> (required) the punc model path
+ --punc-quant <string> (optional) false (Default), load the model of model.onnx in punc_dir. If set true, load the model of model_quant.onnx in punc_dir
```
-cd ../python/grpc
-python grpc_main_client_mic.py --host $server_ip --port 10108
-```
-The `grpc_main_client_mic.py` follows the [original design] (https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/python/grpc#workflow-in-desgin) by sending audio_data with chunks. If you want to send audio_data in one request, here is an example:
-```
-# go to ../python/grpc to find this package
-import paraformer_pb2
+## For the client
+Currently we only support python grpc server.
+
+Install the requirements as in [grpc-python](../python/grpc/Readme.md)
-class RecognizeStub:
- def __init__(self, channel):
- self.Recognize = channel.stream_stream(
- '/paraformer.ASR/Recognize',
- request_serializer=paraformer_pb2.Request.SerializeToString,
- response_deserializer=paraformer_pb2.Response.FromString,
- )
-
-
-async def send(channel, data, speaking, isEnd):
- stub = RecognizeStub(channel)
- req = paraformer_pb2.Request()
- if data:
- req.audio_data = data
- req.user = 'zz'
- req.language = 'zh-CN'
- req.speaking = speaking
- req.isEnd = isEnd
- q = queue.SimpleQueue()
- q.put(req)
- return stub.Recognize(iter(q.get, None))
-
-# send the audio data once
-async def grpc_rec(data, grpc_uri):
- with grpc.insecure_channel(grpc_uri) as channel:
- b = time.time()
- response = await send(channel, data, False, False)
- resp = response.next()
- text = ''
- if 'decoding' == resp.action:
- resp = response.next()
- if 'finish' == resp.action:
- text = json.loads(resp.sentence)['text']
- response = await send(channel, None, False, True)
- return {
- 'text': text,
- 'time': time.time() - b,
- }
-
-async def test():
- # fc = FunAsrGrpcClient('127.0.0.1', 9900)
- # t = await fc.rec(wav.tobytes())
- # print(t)
- wav, _ = sf.read('z-10s.wav', dtype='int16')
- uri = '127.0.0.1:9900'
- res = await grpc_rec(wav.tobytes(), uri)
- print(res)
-
-
-if __name__ == '__main__':
- asyncio.run(test())
-
-```
+## Acknowledge
+1. This project is maintained by [FunASR community](https://github.com/alibaba-damo-academy/FunASR).
+2. We acknowledge burkliu (鍒樻煆鍩�, liubaiji@xverse.cn) for contributing the grpc service.
--
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