{
    "seed": 0, // Random seeds to ensure experiment repeatability
    "description": "...",  // Experiment description, will be displayed in Tensorboard later
    "root_dir": "~/Experiments/Wave-U-Net", // Directory for storing experiment results
    "cudnn_deterministic": false,
    "trainer": { // For training process
        "module": "trainer.trainer", // Which trainer
        "main": "Trainer", // The concrete class of the trainer model
        "epochs": 1200, // Upper limit of training
        "save_checkpoint_interval": 10, // Save model breakpoint interval
        "validation":{
        "interval": 10, // validation interval
         "find_max": true, // When find_max is true, if the calculated metric is the known maximum value, it will cache another copy of the current round of model checkpoint.
        "custon": {
            "visualize_audio_limit": 20, // The interval of visual audio during validation. The reason for setting this parameter is that visual audio is slow
            "visualize_waveform_limit": 20, // The interval of the visualization waveform during validation. The reason for setting this parameter is because the visualization waveform is slow
            "visualize_spectrogram_limit": 20, // Verify the interval of the visualization spectrogram. This parameter is set because the visualization spectrum is slow
            "sample_length": 16384 // See train dataset
            } 
        }
    },
    "model": {
        "module": "model.unet_basic", // Model files used for training
        "main": "Model", // Concrete class of training model
        "args": {} // Parameters passed to the model class
    },
    "loss_function": {
        "module": "model.loss", // Model file of loss function
        "main": "mse_loss", // Concrete class of loss function
        "args": {} // Parameters passed to the model class
    },
    "optimizer": {
        "lr": 0.001,
        "beta1": 0.9,
        "beat2": 0.009
    },
    "train_dataset": {
        "module": "dataset.waveform_dataset", // Store the training set model file
        "main": "Dataset", // Concrete class of training dataset
        "args": { // The parameters passed to the training set class, see the specific training set class for details
            "dataset": "~/Datasets/SEGAN_Dataset/train_dataset.txt",
            "limit": null,
            "offset": 0,
            "sample_length": 16384,
            "mode":"train"
        }
    },
    "validation_dataset": {
        "module": "dataset.waveform_dataset",
        "main": "Dataset",
        "args": {
            "dataset": "~/Datasets/SEGAN_Dataset/test_dataset.txt",
            "limit": 400,
            "offset": 0,
            "mode":"validation"
        }
    },
    "train_dataloader": {
        "batch_size": 120,
        "num_workers": 40, // How many threads to start to preprocess the data
        "shuffle": true,
        "pin_memory":true
    }
}

{
    "model": {
        "module": "model.unet_basic",  // Store the model file
        "main": "UNet",  // The specific model class in the file
        "args": {}  // Parameters passed to the model class
    },
    "dataset": {
        "module": "dataset.waveform_dataset_enhancement",  // Store the enhancement dataset file
        "main": "WaveformDataset",  // Concrete class of enhacnement dataset
        "args": {  // The parameters passed to the dataset class, see the specific enhancement dataset class for details
            "dataset": "/home/imucs/tmp/UNet_and_Inpainting/data.txt",
            "limit": 400,
            "offset": 0,
            "sample_length": 16384
        }
    },
    "custom": {
        "sample_length": 16384
    }
}