FAQ

• Why are the metrics different for different cards?
• A: Fleet is the default option for the use of PaddleClas. Each GPU card is taken as a single trainer and deals with different images, which cause the final small difference. Single card evalution is suggested to get the accurate results if you use tools/eval.py. You can also use tools/eval_multi_platform.py to evalute the models on multiple GPU cards, which is also supported on Windows and CPU.

• Q: Why Mixup or Cutmix is not used even if I have already add the data operation in the configuration file?
• A: When using Mixup or Cutmix, you also need to add use_mix: True in the configuration file to make it work properly.

• Q: During evaluation and inference, pretrained model address is assgined, but the weights can not be imported. Why?
• A: Prefix of the pretrained model is needed. For example, if the pretained weights are located in output/ResNet50_vd/19, with the filename output/ResNet50_vd/19/ppcls.pdparams, then pretrained_model in the configuration file needs to be output/ResNet50_vd/19/ppcls.

• Q: Why are the metrics 0.3% lower than that shown in the model zoo for EfficientNet series of models?
• A: Resize method is set as Cubic for EfficientNet(interpolation is set as 2 in OpenCV), while other models are set as Bilinear(interpolation is set as None in OpenCV). Therefore, you need to modify the interpolation explicitly in ResizeImage. Specifically, the following configuration is a demo for EfficientNet.

VALID:
    batch_size: 16
    num_workers: 4
    file_list: "./dataset/ILSVRC2012/val_list.txt"
    data_dir: "./dataset/ILSVRC2012/"
    shuffle_seed: 0
    transforms:
        - DecodeImage:
            to_rgb: True
            to_np: False
            channel_first: False
        - ResizeImage:
            resize_short: 256
            interpolation: 2
        - CropImage:
            size: 224
        - NormalizeImage:
            scale: 1.0/255.0
            mean: [0.485, 0.456, 0.406]
            std: [0.229, 0.224, 0.225]
            order: ''
        - ToCHWImage:

• Q: The error occured when using visualdl under python2, shows that: TypeError: __init__() missing 1 required positional argument: 'sync_cycle'.
• A: Visualdl is only supported on python3 as now, whose version needs also be higher than 2.0. If your visualdl version is lower than 2.0, you can also install visualdl 2.0 by pip3 install visualdl==2.0.0b8 -i https://mirror.baidu.com/pypi/simple.