config_cifar100.json

{
    "name": "cifar100_PreActResNet18",
    "n_gpu": 1,
    "seed": 666,

    "comet": {
        "project_name": "",
        "api": "",
        "offline": false
    },

    "mixup": {
        "alpha":  0
    },

    "arch": {
        "type": "PreActResNet18",
        "args": {"num_classes":100}
    },

    "reparam_arch": {
        "type": "reparameterization",
        "args": {
            "n_samples": 50000, 
            "num_classes": 100, 
            "init": "gaussian", 
            "mean": 0.0, 
            "std": 1e-8
        }
    },

    "num_classes": 100,

    "data_augmentation":{
        "type": "autoaug_cifar10",
        "cutout": 16
    },

    "data_loader": {
        "type": "CIFAR100DataLoader",
        "args":{
            "data_dir": "",
            "batch_size": 128,
            "shuffle": true,
            "num_batches": 0,
            "validation_split": 0,
            "num_workers": 8,
            "pin_memory": true
        }
    },


    "optimizer": {
        "type": "SGD",
        "args":{
            "lr": 0.02,
            "momentum": 0.9,
            "weight_decay": 1e-3
        }
    },
    
    "optimizer_overparametrization": {
        "type": "SGD",
        "args":{
            "lr": 1,
            "momentum": 0,
            "weight_decay": 0
        }
    },

    "lr_u": 1,
    "lr_v": 10,



    
    "train_loss": {
        "type": "overparametrization_loss",
        "args":{
            "num_examp": 50000, 
            "num_classes": 100,
            "ratio_consistency": 0.9,
            "ratio_balance": 0.1
        }
    },


    "val_loss": {
        "type": "cross_entropy_val",
        "args":{
        }
    },

    "metrics": [
        "my_metric", "my_metric2"
    ],

    "lr_scheduler": {
        "type": "CosineAnnealingLR",
        "args": {
            "T_max": 300,
            "eta_min": 0.0002
        }
    },


    "trainer": {
        "epochs": 300,
        "warmup": 0,
        "save_dir": "",
        "save_period": 1,
        "verbosity": 2,     
        "monitor": "max val_my_metric",
        "early_stop": 2000,
        "tensorboard": false,
        "mlflow": true,
        "_percent": "Percentage of noise",
        "percent": 0.6,
        "_begin": "When to begin updating labels",
        "begin": 0,
        "_asym": "symmetric noise if false",
        "asym": false,
        "_instance": "symmetric noise if false",
        "instance": false,
        "_real": "real noise type",
        "real": null
    }
}