{
    "model_name": "DenseNet",
    "task": "image-classification",
    "framework": "PyTorch",
    "dataset": "CIFAR-10",
    "input_size": [
        3,
        32,
        32
    ],
    "num_classes": 10,
    "growth_rate": 32,
    "dense_blocks": [
        4,
        4,
        4
    ],
    "classes": [
        "airplane",
        "automobile",
        "bird",
        "cat",
        "deer",
        "dog",
        "frog",
        "horse",
        "ship",
        "truck"
    ],
    "architecture": {
        "type": "DenseNet",
        "dense_layer": "BatchNorm -> ReLU -> Conv3x3 -> Concatenate",
        "transition_layer": "BatchNorm -> ReLU -> Conv1x1 -> AvgPool2d",
        "global_average_pooling": true
    },
    "training": {
        "optimizer": "SGD",
        "learning_rate": 0.1,
        "momentum": 0.9,
        "weight_decay": 0.0005,
        "scheduler": "StepLR",
        "step_size": 10,
        "gamma": 0.1,
        "loss": "CrossEntropyLoss",
        "epochs": 30,
        "batch_size": 128
    }
}