code: def is_space_match(string):
      """Determine whether `string` consists of a hyperparameter space declaration
  
      Parameters
      ----------
      string: String
          Str assumed to be source code fragment, which may contain a hyperparameter space declaration
  
      Returns
      -------
      Boolean
          True if `string` begins with a valid hyperparameter space declaration. Else, False
      """
      starting_sequences = ["Real(", "Integer(", "Categorical("]
      # prefix_regex = r"[_\.A-Za-z0-9]"  # TODO: Support prefixes - To cover import aliases or importing modules to call classes
      # r"((?=([_\.A-Za-z0-9]+\.)?(?:(Real|Integer|Categorical)\()))"
      return any(string.startswith(_) for _ in starting_sequences)
  
imports: from hyperparameter_hunter.settings import G, TEMP_MODULES_DOT_PATH, TEMP_MODULES_DIR_PATH
  from hyperparameter_hunter.compat.keras_helper import parameterize_compiled_keras_model
  from hyperparameter_hunter.space.dimensions import Real, Integer, Categorical
  from hyperparameter_hunter.utils.boltons_utils import remap, default_enter
  from hyperparameter_hunter.utils.general_utils import deep_restricted_update, subdict
  from hyperparameter_hunter.utils.parsing_utils import stringify_model_builder, write_python, build_temp_model_file
  from collections import OrderedDict
  from copy import deepcopy
  from datetime import datetime
  from importlib.util import spec_from_file_location, module_from_spec
  import os
  import re
  import sys
  from types import FunctionType, MethodType
label_desc: Use image node_id 9 for calling a global function with example usage: is_space_match(string) and returns: any