RK3399Pro入门教程（9）MNIST RKNN量化教程

1. from rknn.api import RKNN
   
2. 
   
3. INPUT_SIZE = 128
   
4. 
   
5. if __name__ == '__main__':
   
6.     rknn = RKNN()
   
7. 
   
8.     rknn.config(channel_mean_value='0 0 0 255', reorder_channel='0 1 2')
   
9.     print('--> Loading model')
   
10.     rknn.load_tensorflow(tf_pb='mars-small128.pb',
    
11.             inputs=['images'], outputs=['features'], input_size_list=[[128, 64, 3]])
    
12. 
    
13.     print('done')
    
14. 
    
15.     print('--> Building model')
    
16.     rknn.build(do_quantization=False)
    
17.     print('done')
    
18. 
    
19.     rknn.export_rknn('./mars-small128.rknn')
    
20.     rknn.release()

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