code: def validate_config_against_spec(
      config: lit_types.JsonDict,
      spec: lit_types.Spec,
      name: str,
      raise_for_unsupported: bool = False,
  ):
      """Validates that the provided config is compatible with the Spec.
  
      Args:
        config: The configuration parameters, such as extracted from the data of an
          HTTP Request, that are to be used in a function call.
        spec: A Spec defining the shape of allowed configuration parameters for the
          associated LIT component.
        name: The name of the endpoint, interpreter, etc. providing the Spec against
          which the config is valdiated.
        raise_for_unsupported: If true, raises a KeyError if the config contains
          keys that are not present in the Spec. Unsupported keys are assumed to be
          acceptable for subclasses of lit_nlp.api.components, but unacceptable for
          APIs that instantiate new instances of a class (e.g., /create_dataset).
  
      Returns:
        The config passed in as the first argument, if validation is successful.
  
      Raises:
        KeyError: Under two conditions: 1) the `config` is missing one or more
          required fields defined in the `spec`, or 2) the `config` contains fields
          not defined in the `spec`. Either of these conditions would likely result
          in a TypeError (for missing or unexpected arguments) if the `config` was
          used in a call.
      """
      missing_required_keys = [
          param_name
          for param_name, param_type in spec.items()
          if param_type.required and param_name not in config
      ]
      if missing_required_keys:
          raise KeyError(
              f"{name} missing required params: {missing_required_keys}"
          )
  
      unsupported_keys = [
          param_name for param_name in config if param_name not in spec
      ]
      if raise_for_unsupported and unsupported_keys:
          raise KeyError(
              f"{name} received unsupported params: {unsupported_keys}"
          )
  
      return config
  
imports: from collections.abc import Callable, Collection, Iterable, Iterator, Mapping, Sequence
  import itertools
  import queue
  import threading
  import time
  from typing import Any, Optional, TypeVar, Union
  import uuid
  from lit_nlp.api import types
  import numpy
label_desc: Use image node_id 18 for calling a global function with example usage: validate_config_against_spec(config, spec, name, raise_for_unsupported) and returns: config