Can I have a nested config?

W&B Help
1

My experiments are runs of different models over different datasets. Different models for example have their own sets of hyperparameters, same for datasets.

For example for CNN model, I want to save kernel size and for Transformer model its residual dimension. For datasets I want to save their preprocessing parameters, which could be multiple.

That is,

config1 = {
   "model": {
      "name": "CNN",
      "kernel_size": 3
   }
   "dataset": {
     "name": "MNIST",
     "preprocessing": None
   }
}

config2 = {
   "model": {
      "name": "Transformer",
      "d_model": 512
   }
   "dataset": {
     "name": "MNIST",
     "preprocessing": [
         "noise": {
             "mean": 0.0,
             "std": 1.0
         },
       "resize": 14
     ]
   }
}

Would I able to do this with W&B? Examples in documentation are all plain dictionaries.