kk_contour_net_shallow/config.json

{
    "model_continue": false, // true, (false)
    "max_epochs": 5000,
    "batch_size_train": 250,
    "batch_size_test": 500,

    // data source ->
    "data_path": "/home/kk/Documents/Semester4/code/RenderStimuli/Output/",
    "stimuli_per_pfinkel": 30000,
    "num_pfinkel_start": 0,
    "num_pfinkel_stop": 10,
    "num_pfinkel_step": 10,
    "condition": "Coignless",
    "scale_data": 255.0, // (255.0)
    // <- data source 

    // optimizer ->
    "use_adam": true, // (true) => adam, false => SGD
    // <- optimizer 

    // LR Scheduler ->
    "use_scheduler": true, // (true), false
    "scheduler_verbose": true,
    "scheduler_factor": 0.025, //(0.1)
    "scheduler_patience": 10, // (10)
    "scheduler_threshold": 1e-5, // (1e-5)
    "minimum_learning_rate": 1e-10,
    "learning_rate": 1e-4,
    // <- LR Scheduler

    // pooling layer ->
    "pooling_type": "max", // (max), average, none
    // <- pooling layer 

    // activation function ->
    "activation_function": "leaky relu", // tanh, relu, (leaky relu), none
    "leak_relu_negative_slope": 0.1, // (0.1)
    // <- activation function

    // convolution layer 0 softmax parameters ->
    "conv_0_enable_softmax": false, // true, (false)
    "conv_0_power_softmax": 4.0, // (0.0) = Exp
    "conv_0_meanmode_softmax": true, // true, false
    "conv_0_no_input_mode_softmax": false, // true, (false)
    // <- convolution layer 0 softmax parameters

    // network definion -> 
    "train_first_layer": true, // true, (false)
    "mp_1_kernel_size": 3,
    "mp_1_stride": 2,
    "conv_0_kernel_size": 11,
    "conv_out_channels_list": [
        [
            8,
            8,
            8
        ]
    ],
    "conv_kernel_sizes": [
        [
            7,
            15
        ]
    ],
    "conv_stride_sizes": [
        1
    ],
    // <- network definion 

    // logging -> 
    "save_logging_messages": true, // (true), false
    "display_logging_messages": true, // (true), false
    // <- logging 

    // saving the model and co ->
    "save_model": true,
    "use_plot_intermediate": false, // true, (false)
    "precision_100_percent": 4, // (4)
    "save_ever_x_epochs": 10, // (10)
    // <- saving the model and co

    // path definitions ->
    "initial_model_path": "initial_models",
    "tb_runs_path": "tb_runs",
    "trained_models_path": "trained_models",
    "performance_data_path": "performance_data"
    // <- path definitions 
}