From fc08b62d05723cdc1ce021bb8ba044ca014fb1f7 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期一, 13 三月 2023 18:38:41 +0800
Subject: [PATCH] readme
---
funasr/runtime/python/onnxruntime/README.md | 95 +++++++++++++++++++++++++++--------------------
1 files changed, 54 insertions(+), 41 deletions(-)
diff --git a/funasr/runtime/python/onnxruntime/README.md b/funasr/runtime/python/onnxruntime/README.md
index 264c7f1..6ed9849 100644
--- a/funasr/runtime/python/onnxruntime/README.md
+++ b/funasr/runtime/python/onnxruntime/README.md
@@ -10,55 +10,68 @@
### Steps:
-1. Download the whole directory (`funasr/runtime/python/onnxruntime`) to the local.
-2. Install the related packages.
- ```bash
- pip install requirements.txt
- ```
-3. Download the model.
- - [Download Link](https://swap.oss-cn-hangzhou.aliyuncs.com/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/model.onnx?OSSAccessKeyId=LTAI4FxMqzhBUx5XD4mKs296&Expires=2036094510&Signature=agmtMkxLEviGg3Rt3gOO4PvfrJY%3D)
- - Put the model into the `resources/models`.
- ```text
- .
- 鈹溾攢鈹� demo.py
- 鈹溾攢鈹� rapid_paraformer
- 鈹偮犅� 鈹溾攢鈹� __init__.py
- 鈹偮犅� 鈹溾攢鈹� kaldifeat
- 鈹偮犅� 鈹溾攢鈹� __pycache__
- 鈹偮犅� 鈹溾攢鈹� rapid_paraformer.py
- 鈹偮犅� 鈹斺攢鈹� utils.py
- 鈹溾攢鈹� README.md
- 鈹溾攢鈹� requirements.txt
- 鈹溾攢鈹� resources
- 鈹偮犅� 鈹溾攢鈹� config.yaml
- 鈹偮犅� 鈹斺攢鈹� models
- 鈹偮犅� 鈹溾攢鈹� am.mvn
- 鈹偮犅� 鈹溾攢鈹� model.onnx # Put it here.
- 鈹偮犅� 鈹斺攢鈹� token_list.pkl
- 鈹溾攢鈹� test_onnx.py
- 鈹溾攢鈹� tests
- 鈹偮犅� 鈹溾攢鈹� __pycache__
- 鈹偮犅� 鈹斺攢鈹� test_infer.py
- 鈹斺攢鈹� test_wavs
- 鈹溾攢鈹� 0478_00017.wav
- 鈹斺攢鈹� asr_example_zh.wav
- ```
-4. Run the demo.
+1. Export the model.
+ - Command: (`Tips`: torch >= 1.11.0 is required.)
+
+ ```shell
+ python -m funasr.export.export_model [model_name] [export_dir] [true]
+ ```
+ `model_name`: the model is to export.
+
+ `export_dir`: the dir where the onnx is export.
+
+ More details ref to ([export docs](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export))
+
+ - `e.g.`, Export model from modelscope
+ ```shell
+ python -m funasr.export.export_model 'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch' "./export" true
+ ```
+ - `e.g.`, Export model from local path, the model'name must be `model.pb`.
+ ```shell
+ python -m funasr.export.export_model '/mnt/workspace/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch' "./export" true
+ ```
+
+
+2. Install the `rapid_paraformer`.
+ - Build the rapid_paraformer `whl`
+ ```shell
+ git clone https://github.com/alibaba/FunASR.git && cd FunASR
+ cd funasr/runtime/python/onnxruntime
+ python setup.py bdist_wheel
+ ```
+ - Install the build `whl`
+ ```bash
+ pip install dist/rapid_paraformer-0.0.1-py3-none-any.whl
+ ```
+
+3. Run the demo.
+ - Model_dir: the model path, which contains `model.onnx`, `config.yaml`, `am.mvn`.
- Input: wav formt file, support formats: `str, np.ndarray, List[str]`
- Output: `List[str]`: recognition result.
- Example:
```python
- from rapid_paraformer import RapidParaformer
+ from rapid_paraformer import Paraformer
+ model_dir = "/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
+ model = Paraformer(model_dir, batch_size=1)
- config_path = 'resources/config.yaml'
- paraformer = RapidParaformer(config_path)
+ wav_path = ['/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav']
- wav_path = ['test_wavs/0478_00017.wav']
-
- result = paraformer(wav_path)
+ result = model(wav_path)
print(result)
```
+## Speed
+
+Environment锛欼ntel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz
+
+Test [wav, 5.53s, 100 times avg.](https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav)
+
+| Backend | RTF |
+|:-------:|:-----------------:|
+| Pytorch | 0.110 |
+| Onnx | 0.038 |
+
+
## Acknowledge
-1. We acknowledge [SWHL](https://github.com/RapidAI/FunASR) for contributing the onnxruntime(pthon api).
+1. We acknowledge [SWHL](https://github.com/RapidAI/RapidASR) for contributing the onnxruntime(python api).
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