config.json

{
    "name": "NetVLAD_Sthereo",
    "n_gpu": 1,
    "mode" : "train",
    "dataset" : "sthereo",

    "encoder": {
        "type": "ResNet34",
        "args": {
            "pretrained": true
        }
    },

    "pool": {
        "type": "NetVLAD",
        "args": {
            "num_clusters" : 64,
            "dim" : 512,
            "normalize_input" : true,
            "vladv2" : false
        }
    },

    "cluster_loader": {
        "type": "ClusterLoader",
        "args":{
            "structFile" : "/home/ma/git/learning/netvlad_templated/csv/train_dataset_full.csv",
            "cacheBatchSize": 24,
            "shuffle": false,
            "num_workers": 8,
            "validation_split":0.0,
            "pin_memory" : true
        }
    },
    "train_loader": {
        "type": "TrainLoader",
        "args":{
            "structFile" : "/home/ma/git/learning/netvlad_templated/csv/train_dataset_full.csv",
            "margin" : 0.1,
            "nNegSample": 1000,
            "nNeg" : 10,
            "batch_size": 5,
            "shuffle": true,
            "num_workers": 8,
            "validation_split": 0.0,
            "pin_memory" : true
        }
    },
    "valid_loader": {
        "type": "validLoader",
        "args":{
            "structFile" : "/home/ma/git/learning/netvlad_templated/csv/val_dataset_full.csv",
            "cacheBatchSize": 24,
            "shuffle": false,
            "num_workers": 8,
            "validation_split":0.0,
            "pin_memory" : true
        }
    },
    "optimizer": {
        "type": "Adam",
        "args":{
            "lr": 0.0001,
            "weight_decay": 0.001,
            "amsgrad": true
        }
    },
    "loss": "triplet_loss",
    "metrics": [
        "accuracy", "top_k_acc"
    ],
    "lr_scheduler": {
        "type": "StepLR",
        "args": {
            "step_size": 5,
            "gamma": 0.5
        }
    },
    "trainer": {
        "epochs": 100,

        "save_dir": "saved/",
        "save_period": 1,
        "verbosity": 2,
        
        "cacheRefreshRate" : 1000,
        "cachePath": "./cache",
        "monitor": "min val_loss",
        "early_stop": 10,

        "tensorboard": true
    }
}