code: def get_pydantic_config(self):
      type_annotation_dict = {}
      dataset_list = []
      for k, v in self.registry.items():
          dataset_name = v["name"]
          type_annotation_dict = v["extra_args"]
          if "name" in type_annotation_dict:
              del type_annotation_dict["name"]
          base = self.get_base_class(dataset_name, self.pipeline_name)
          dataset_list.append(
              create_model(
                  f"{dataset_name}Config",
                  **type_annotation_dict,
                  __base__=base,
              )
          )
  
      output = dataset_list[0]
      for d in dataset_list[1:]:
          output = Union[output, d]
      return output
  
imports: import enum
  import inspect
  import logging
  from abc import ABC, abstractmethod, abstractstaticmethod
  from pathlib import Path
  from typing import Callable, Dict, List, Optional, Tuple, Union
  import yaml
  from dgl.dataloading.negative_sampler import GlobalUniform, PerSourceUniform
  from numpydoc import docscrape
  from pydantic import create_model, create_model_from_typeddict, Field
  from typing_extensions import Literal
  from .base_model import DGLBaseModel
label_desc: Use image node_id 6 for calling the DataFactoryClass obj's underlying member method code with example usage: obj.get_pydantic_config() and returns: output