code: def get_initializer(parameters):
      if parameters is None:
          return lambda *args, **kwargs: _create_and_init(
              initializer_registry[parameters], {}, *args, **kwargs
          )
      elif isinstance(parameters, str):
          initializer_fun = get_from_registry(
              parameters, initializer_registry
          )
          return lambda *args, **kwargs: _create_and_init(
              initializer_fun, {}, *args, **kwargs
          )
      elif isinstance(parameters, dict):
          initializer_fun = get_from_registry(
              parameters[TYPE], initializer_registry
          )
          init_kwargs = parameters.copy()
          del init_kwargs[TYPE]
          return lambda *args, **kwargs: _create_and_init(
              initializer_fun, init_kwargs, *args, **kwargs
          )
      else:
          raise ValueError(
              f"Initializers parameters should be either strings or dictionaries, "
              f"but the provided parameters are a {type(parameters)}. "
              f"Parameters values: {parameters}"
          )
  
imports: import torch
  from ludwig.constants import TYPE
  from ludwig.utils.misc_utils import get_from_registry
  from ludwig.utils.torch_utils import initializer_registry
label_desc: Use image node_id 2 for calling a global function with example usage: get_initializer(parameters) and returns: function, function, function