From 8cd93a1fc77e8a4a119f248ec0eb9018a74f728b Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期二, 21 三月 2023 19:41:40 +0800
Subject: [PATCH] asr_inference pipeline supports combine tp model

---
 funasr/export/README.md |   51 ++++++++++++++++++++++++++++++++++++++-------------
 1 files changed, 38 insertions(+), 13 deletions(-)

diff --git a/funasr/export/README.md b/funasr/export/README.md
index a4d61bb..c05348e 100644
--- a/funasr/export/README.md
+++ b/funasr/export/README.md
@@ -1,33 +1,58 @@
 
 ## Environments
-    funasr 0.1.7
-    python 3.7
-    torch 1.11.0
-    modelscope 1.2.0
+    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](../../README.md)
 
-## Export onnx format model
+## 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.
+
+
+## For example
+### Export onnx format model
 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
+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
+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
+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 torchscripts format model
 Export model from modelscope
 ```shell
-python -m funasr.export.export_model 'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch' "./export" false
+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
+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" false
+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.
+

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