docs

docs/export.md

@@ -1,68 +0,0 @@
-
-## 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/export.md

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+../funasr/export/README.md

docs/grpc_cpp.md

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+../funasr/runtime/grpc/Readme.md

docs/grpc_python.md

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+../funasr/runtime/python/grpc/Readme.md

docs/index.rst

@@ -27,6 +27,12 @@ FunASR hopes to build a bridge between academic research and industrial applicat
    :caption: Runtime:
 
    ./export.md
+   ./onnxruntime_python.md
+   ./onnxruntime_cpp.md
+   ./libtorch_python.md
+   ./grpc_python.md
+   ./grpc_cpp.md
+
 
 
 .. toctree::

docs/libtorch_python.md

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+../funasr/runtime/python/libtorch/README.md

docs/onnxruntime_cpp.md

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+../funasr/runtime/onnxruntime/readme.md

docs/onnxruntime_python.md

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+../funasr/runtime/python/onnxruntime/README.md