请问，有对不同BenkendType之间转换的工具，比如Academic转到SNPE的后端？

[hewumars]

另外部署SNPE的onnx为什么会增加类似量化的操作？

1. 部署命令参考这里：https://mqbench.readthedocs.io/en/latest/user_guide/deploy/snpe.html
2. 训练代码：${MQBench}/application/imagenet_example/PTQ/ptq/ptq.py
3. ptq config文件如下：

   extra_prepare_dict:
   extra_qconfig_dict:
       w_observer: MSEObserver
       a_observer: EMAMSEObserver
       w_fakequantize: AdaRoundFakeQuantize
       a_fakequantize: QDropFakeQuantize
       w_qscheme:
           bit: 8
           symmetry: False
           per_channel: True
           pot_scale: False
           p: 2.4
       a_qscheme:
           bit: 8
           symmetry: False
           per_channel: False
           pot_scale: False
           p: 2.4
   quantize:
   backend: SNPE
   quantize_type: advanced_ptq # support naive_ptq or advanced_ptq
   cali_batchsize: 16
   reconstruction:
       pattern: block
       scale_lr: 4.0e-5
       warm_up: 0.2
       weight: 0.1
       max_count: 20000
       b_range: [20,2]
       keep_gpu: True
       round_mode: learned_hard_sigmoid
       prob: 0.5
   deploy:
       output_path: /home/mars/hewu/nvme1n1/03_datesets/01_PublicDataset/imagenet-mini
       model_name: 'mbv2'
   model:                    # architecture details
   type: mobilenet_v2        # model name
   kwargs:
       num_classes: 1000
   path: /path-of-pretrained
   data:
   path: /home/mars/hewu/nvme1n1/03_datesets/01_PublicDataset/imagenet-mini
   batch_size: 64
   num_workers: 4
   pin_memory: True
   input_size: 224
   test_resize: 256
   process:
   seed: 1005

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