6122a678f5
Refactors and extends model export support to include new NeMo Parakeet TDT int8 variants for English and Japanese, updating the Kotlin API, export scripts, test runners, and CI workflows. - Added support for two new int8 model types in OfflineRecognizer.kt. - Enhanced Python export scripts to perform dynamic quantization and metadata injection. - Updated shell scripts and GitHub workflows to package, test, and publish int8 model artifacts.
92 lines
2.4 KiB
Python
Executable File
92 lines
2.4 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2025 Xiaomi Corp. (authors: Fangjun Kuang)
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import os
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from typing import Dict
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import nemo.collections.asr as nemo_asr
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import onnx
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import torch
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from onnxruntime.quantization import QuantType, quantize_dynamic
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def add_meta_data(filename: str, meta_data: Dict[str, str]):
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"""Add meta data to an ONNX model. It is changed in-place.
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Args:
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filename:
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Filename of the ONNX model to be changed.
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meta_data:
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Key-value pairs.
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"""
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model = onnx.load(filename)
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while len(model.metadata_props):
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model.metadata_props.pop()
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for key, value in meta_data.items():
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meta = model.metadata_props.add()
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meta.key = key
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meta.value = str(value)
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onnx.save(model, filename)
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@torch.no_grad()
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def main():
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asr_model = nemo_asr.models.ASRModel.from_pretrained(
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model_name="nvidia/parakeet-tdt_ctc-0.6b-ja"
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)
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print(asr_model.cfg)
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print(asr_model)
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with open("./tokens.txt", "w", encoding="utf-8") as f:
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for i, s in enumerate(asr_model.joint.vocabulary):
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f.write(f"{s} {i}\n")
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f.write(f"<blk> {i+1}\n")
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print("Saved to tokens.txt")
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decoder_type = "ctc"
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asr_model.change_decoding_strategy(decoder_type=decoder_type)
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asr_model.eval()
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asr_model.set_export_config({"decoder_type": "ctc"})
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filename = "model.onnx"
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asr_model.export(filename, onnx_opset_version=18)
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normalize_type = asr_model.cfg.preprocessor.normalize
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if normalize_type == "NA":
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normalize_type = ""
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meta_data = {
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"vocab_size": asr_model.decoder.vocab_size,
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"normalize_type": normalize_type,
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"subsampling_factor": 8,
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"model_type": "EncDecHybridRNNTCTCBPEModel",
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"version": "1",
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"model_author": "NeMo",
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"url": "https://huggingface.co/nvidia/parakeet-tdt_ctc-0.6b-ja",
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"comment": "Only the CTC branch is exported",
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"doc": "See https://huggingface.co/nvidia/parakeet-tdt_ctc-0.6b-ja",
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}
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os.system("ls -lh *.onnx")
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quantize_dynamic(
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model_input="./model.onnx",
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model_output="./model.int8.onnx",
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weight_type=QuantType.QUInt8,
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)
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add_meta_data("model.int8.onnx", meta_data)
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os.system("ls -lh *.onnx")
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print("preprocessor", asr_model.cfg.preprocessor)
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print(meta_data)
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if __name__ == "__main__":
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main()
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