code: def slice_key_matches_slice_specs(
      slice_key: SliceKeyType, slice_specs: Iterable[SingleSliceSpec]
  ) -> bool:
      """Checks whether a slice key matches any slice spec.
  
      In this setting, a slice key matches a slice spec if it could have been
      generated by that spec.
  
      Args:
        slice_key: The slice key to check for applicability against slice specs.
        slice_specs: Slice specs against which to check applicability of a slice
          key.
  
      Returns:
        True if the slice_key matches any slice specs, False otherwise.
      """
      for slice_spec in slice_specs:
          if slice_spec.is_slice_applicable(slice_key):
              return True
      return False
  
imports: import itertools
  from typing import Any, Callable, Dict, Generator, Iterable, List, NamedTuple, Optional, Tuple, Union
  import apache_beam
  import numpy
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.proto import metrics_for_slice_pb2
  from tensorflow_model_analysis.slicer import slice_accessor
label_desc: Use image node_id 13 for calling a global function with example usage: slice_key_matches_slice_specs(slice_key, slice_specs) and returns: False, True