code: def get_missing_slices(
      slicing_details: Iterable[validation_result_pb2.SlicingDetails],
      eval_config: config_pb2.EvalConfig,
  ) -> List[Union[config_pb2.SlicingSpec, config_pb2.CrossSlicingSpec]]:
      """Returns specs that are defined in the EvalConfig but not found in details.
  
      Args:
        slicing_details: Slicing details.
        eval_config: Eval config.
  
      Returns:
        List of missing slices or empty list if none are missing.
      """
      hashed_details = _hashed_slicing_details(slicing_details)
      thresholds = metric_specs.metric_thresholds_from_metrics_specs(
          eval_config.metrics_specs, eval_config=eval_config
      )
      baseline_spec = model_util.get_baseline_model_spec(eval_config)
      baseline_model_name = (
          baseline_spec.name if baseline_spec else None
      )
      missing_slices = []
      for metric_key, sliced_thresholds in thresholds.items():
          # Skip baseline.
          if metric_key.model_name == baseline_model_name:
              continue
          for slice_spec, _ in sliced_thresholds:
              if not slice_spec:
                  slice_spec = config_pb2.SlicingSpec()
              hashable_slice_spec = slicer.deserialize_slice_spec(
                  slice_spec
              )
              if hashable_slice_spec not in hashed_details:
                  missing_slices.append(slice_spec)
                  # Same slice may be used by other metrics/thresholds, only add once
                  hashed_details[
                      hashable_slice_spec
                  ] = validation_result_pb2.SlicingDetails()
      return missing_slices
  
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 4 for calling a global function with example usage: get_missing_slices(slicing_details, eval_config) and returns: missing_slices