class_docstr: Wrapper for dataset configurations.
  
  This class provides access to configurations for the dataset used in the
  experiment.
  
  TODO(smyrnisg): Add support for datasets other than ImageNet.
  
  Attributes
    num_classes: Number of classes in the Dataset
    train_size: Number of samples used for training.
    eval_size: Number of samples used for evaluation.
    dataset_name_compat: For compatibility with the name of predefined dataset.
code: def __init__(self, dataset: str):
      if dataset == "imagenet":
          self.dataset_name_compat = data_utils.Dataset.IMAGENET
          self.num_classes = 1000
          self.train_size = 1281167
          self.eval_size = 50000
  
      else:
          raise ValueError("Dataset not understood: {}".format(dataset))
  
imports: from meo.mlp_baseline import data_utils
label_desc: Use image node_id 1 to create a new DatasetConfig object from inherited base classes: object with example: obj = DatasetConfig(dataset)