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| | | environment: ubuntu20.04-py37-torch1.11.0-tf1.15.5-1.2.0 |
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| | | ## Environments |
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| | | torch >= 1.11.0 |
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| | | modelscope >= 1.2.0 |
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| | | torch-quant >= 0.4.0 (required for exporting quantized torchscript format model) |
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| | | # pip install torch-quant -i https://pypi.org/simple |
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| | | |
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| | | Export onnx files from modelscope |
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| | | ```python |
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| | | from funasr.export.export_model import ASRModelExportParaformer |
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| | | ## Install modelscope and funasr |
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| | | output_dir = "../export" |
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| | | export_model = ASRModelExportParaformer(cache_dir=output_dir, onnx=True) |
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| | | export_model.export_from_modelscope('damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch') |
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| | | The installation is the same as [funasr](../../README.md) |
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| | | |
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| | | ## Export model |
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| | | `Tips`: torch>=1.11.0 |
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| | | |
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| | | ```shell |
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| | | python -m funasr.export.export_model \ |
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| | | --model-name [model_name] \ |
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| | | --export-dir [export_dir] \ |
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| | | --type [onnx, torch] \ |
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| | | --quantize [true, false] \ |
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| | | --fallback-num [fallback_num] |
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| | | ``` |
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| | | `model-name`: the model is to export. It could be the models from modelscope, or local finetuned model(named: model.pb). |
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| | | |
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| | | `export-dir`: the dir where the onnx is export. |
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| | | |
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| | | `type`: `onnx` or `torch`, export onnx format model or torchscript format model. |
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| | | |
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| | | `quantize`: `true`, export quantized model at the same time; `false`, export fp32 model only. |
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| | | |
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| | | `fallback-num`: specify the number of fallback layers to perform automatic mixed precision quantization. |
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| | | |
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| | | ## For example |
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| | | ### Export onnx format model |
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| | | Export model from modelscope |
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| | | ```shell |
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| | | 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 |
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| | | ``` |
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| | | Export model from local path, the model'name must be `model.pb`. |
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| | | ```shell |
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| | | 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 |
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| | | ``` |
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| | | |
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| | | ### Export torchscripts format model |
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| | | Export model from modelscope |
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| | | ```shell |
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| | | 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 |
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| | | ``` |
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| | | |
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| | | Export onnx files from local path |
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| | | ```python |
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| | | from funasr.export.export_model import ASRModelExportParaformer |
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| | | Export model from local path, the model'name must be `model.pb`. |
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| | | ```shell |
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| | | 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 |
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| | | ``` |
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| | | |
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| | | output_dir = "../export" |
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| | | export_model = ASRModelExportParaformer(cache_dir=output_dir, onnx=True) |
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| | | export_model.export_from_local('/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch') |
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| | | ``` |
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| | | ## Acknowledge |
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| | | 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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