code: def merge_details(
      a: validation_result_pb2.ValidationResult,
      b: validation_result_pb2.ValidationResult,
  ):
      """Merges validation details in ValidationtResult b into ValidationResult a."""
      hashed_details = _hashed_slicing_details(
          b.validation_details.slicing_details
      )
      # Combine a with matching values from b
      for details in a.validation_details.slicing_details:
          hashable_slice_spec = slicer.deserialize_slice_spec(
              details.slicing_spec
          )
          if hashable_slice_spec in hashed_details:
              details.num_matching_slices = (
                  details.num_matching_slices
                  + hashed_details[
                      hashable_slice_spec
                  ].num_matching_slices
              )
              del hashed_details[hashable_slice_spec]
      # Add any values from b not matched in a
      for details in hashed_details.values():
          a.validation_details.slicing_details.append(details)
  
file_path: model-analysis/tensorflow_model_analysis/evaluators/metrics_validator.py
imports: import math
  from typing import Any, Dict, Iterable, List, Tuple, Union
  import numpy
  from tensorflow_model_analysis.metrics import metric_specs
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.proto import validation_result_pb2
  from tensorflow_model_analysis.slicer import slicer_lib
  from tensorflow_model_analysis.utils import model_util
label_desc: Use image node_id 3 for calling a global function with example usage: merge_details(a, b) without return types