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ILA.json
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ILA.json
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{
"source_model_path": ["NIPS2017/pretrained/resnet50"],
"target_model_path": ["NIPS2017/pretrained/resnet50",
"NIPS2017/pretrained/vgg19_bn",
"NIPS2017/pretrained/resnet152",
"NIPS2017/pretrained/inception_v3",
"NIPS2017/pretrained/densenet121",
"NIPS2017/pretrained/mobilenet_v2",
"NIPS2017/pretrained/senet154",
"NIPS2017/pretrained/resnext101",
"NIPS2017/pretrained/wrn101",
"NIPS2017/pretrained/pnasnet",
"NIPS2017/pretrained/mnasnet"],
"n_iter": 10,
"shuffle": true,
"batch_size": 200,
"norm_type": "inf",
"epsilon": 0.03,
"norm_step": 0.00392157,
"seed": 0,
"n_ensemble": 1,
"targeted": false,
"save_dir": "./save",
"input_transformation": "",
"loss_function": "cross_entropy",
"grad_calculation": "general",
"backpropagation": "nonlinear",
"update_dir_calculation": "sgd",
"as_baseline": true,
"bsl_adv_img_path": "./save_ifgsm"
}
{
"source_model_path": ["NIPS2017/pretrained/resnet50"],
"target_model_path": ["NIPS2017/pretrained/resnet50",
"NIPS2017/pretrained/vgg19_bn",
"NIPS2017/pretrained/resnet152",
"NIPS2017/pretrained/inception_v3",
"NIPS2017/pretrained/densenet121",
"NIPS2017/pretrained/mobilenet_v2",
"NIPS2017/pretrained/senet154",
"NIPS2017/pretrained/resnext101",
"NIPS2017/pretrained/wrn101",
"NIPS2017/pretrained/pnasnet",
"NIPS2017/pretrained/mnasnet"],
"n_iter": 100,
"shuffle": true,
"batch_size": 100,
"norm_type": "inf",
"epsilon": 0.03,
"norm_step": 0.00392157,
"seed": 0,
"n_ensemble": 1,
"targeted": false,
"save_dir": "./save",
"input_transformation": "",
"loss_function": "ila_loss(ila_layer=2)",
"grad_calculation": "general",
"backpropagation": "nonlinear",
"update_dir_calculation": "sgd",
"bsl_adv_img_path": "./save_ifgsm"
}