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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