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#!/usr/bin/env python3
# ztu_somemodelruntime_rknn2: audio_vae_encode
import faulthandler
faulthandler.enable()
import os
os.chdir(os.path.dirname(os.path.abspath(__file__)))
from rknn.api import RKNN
import numpy as np
def main():
# 创建RKNN实例
rknn = RKNN(verbose=True)
# ONNX模型路径
ONNX_MODEL = "audio_vae_encode.onnx"
# 输出RKNN模型路径
RKNN_MODEL = "audio_vae_encode.rknn"
# 配置参数
print("--> Config model")
ret = rknn.config(target_platform="rk3588",
dynamic_input=None)
if ret != 0:
print('Config model failed!')
exit(ret)
# 加载ONNX模型
print("--> Loading model")
ret = rknn.load_onnx(model=ONNX_MODEL,
inputs=['audio_wave'],
input_size_list=[[1, 1, 40960]])
if ret != 0:
print('Load model failed!')
exit(ret)
# 构建模型
print("--> Building model")
ret = rknn.build(do_quantization=False)
if ret != 0:
print('Build model failed!')
exit(ret)
# 导出RKNN模型
print("--> Export RKNN model")
ret = rknn.export_rknn(RKNN_MODEL)
if ret != 0:
print('Export RKNN model failed!')
exit(ret)
print(f'Done! The converted RKNN model has been saved to: ' + RKNN_MODEL)
# 精度分析(可选)
# rknn.accuracy_analysis(inputs=["dumps_audio_vae_encode/audio_wave.npy"], target="rk3588", device_id=None)
rknn.release()
if __name__ == '__main__':
main()
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