code: def list_datasets(name=None):
      
      reg = registry.get_registry(Dataset)
  
      if name is not None:
          class_ = reg[name.lower()]
          return _REGSITRY_NAME_KWARGS[class_]
      else:
          return {
              dataset_name: _REGSITRY_NAME_KWARGS[class_]
              for dataset_name, class_ in registry.get_registry(Dataset).items()
          }
docs: Get valid datasets and registered parameters.
  
      Parameters
      ----------
      name : str or None, default None
          Return names and registered parameters of registered datasets. If name
          is specified, only registered parameters of the respective dataset are
          returned.
  
      Returns
      -------
      dict:
          A dict of all the valid keyword parameters names for the specified
          dataset. If name is set to None, returns a dict mapping each valid name
          to its respective keyword parameter dict. The valid names can be
          plugged in `gluonnlp.model.word_evaluation_model.create(name)`.