docs

docs/export.md

@@ -0,0 +1,68 @@
+
+## Environments
+    torch >= 1.11.0
+    modelscope >= 1.2.0
+    torch-quant >= 0.4.0 (required for exporting quantized torchscript format model)
+    # pip install torch-quant -i https://pypi.org/simple
+
+## Install modelscope and funasr
+
+The installation is the same as [funasr](https://github.com/alibaba-damo-academy/FunASR/blob/main/README.md#installation)
+
+## Export model
+   `Tips`: torch>=1.11.0
+
+   ```shell
+   python -m funasr.export.export_model \
+       --model-name [model_name] \
+       --export-dir [export_dir] \
+       --type [onnx, torch] \
+       --quantize [true, false] \
+       --fallback-num [fallback_num]
+   ```
+   `model-name`: the model is to export. It could be the models from modelscope, or local finetuned model(named: model.pb).
+
+   `export-dir`: the dir where the onnx is export.
+
+   `type`: `onnx` or `torch`, export onnx format model or torchscript format model.
+
+   `quantize`: `true`, export quantized model at the same time; `false`, export fp32 model only.
+
+   `fallback-num`: specify the number of fallback layers to perform automatic mixed precision quantization.
+
+## Performance Benchmark of Runtime
+
+### Paraformer on CPU
+
+[onnx runtime](https://github.com/alibaba-damo-academy/FunASR/blob/main/funasr/runtime/python/benchmark_onnx.md)
+
+[libtorch runtime](https://github.com/alibaba-damo-academy/FunASR/blob/main/funasr/runtime/python/benchmark_libtorch.md)
+
+### Paraformer on GPU
+[nv-triton](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/runtime/triton_gpu)
+
+## For example
+### Export onnx format model
+Export model from modelscope
+```shell
+python -m funasr.export.export_model --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type onnx
+```
+Export model from local path, the model'name must be `model.pb`.
+```shell
+python -m funasr.export.export_model --model-name /mnt/workspace/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type onnx
+```
+
+### Export torchscripts format model
+Export model from modelscope
+```shell
+python -m funasr.export.export_model --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type torch
+```
+
+Export model from local path, the model'name must be `model.pb`.
+```shell
+python -m funasr.export.export_model --model-name /mnt/workspace/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type torch
+```
+
+## Acknowledge
+Torch model quantization is supported by [BladeDISC](https://github.com/alibaba/BladeDISC), an end-to-end DynamIc Shape Compiler project for machine learning workloads. BladeDISC provides general, transparent, and ease of use performance optimization for TensorFlow/PyTorch workloads on GPGPU and CPU backends. If you are interested, please contact us.
+

docs/index.rst

@@ -25,7 +25,7 @@ FunASR hopes to build a bridge between academic research and industrial applicat
 .. toctree::
    :maxdepth: 1
    :caption: Runtime:
-
+   ./export.md
    ../funasr/export/README.md
    ../funasr/runtime/python/onnxruntime/README.md
    ../funasr/runtime/python/libtorch/README.md