code: def load_and_deserialize_validation_result(
      output_path: str, output_file_format: str = _TFRECORD_FORMAT
  ) -> validation_result_pb2.ValidationResult:
      """Read and deserialize the ValidationResult record.
  
      Args:
        output_path: Path or pattern to search for validation file under. If a
          directory is passed, a file matching 'validations*' will be searched for.
        output_file_format: Optional file extension to filter files by and the
          format to use for parsing. The default value is tfrecord.
  
      Returns:
        ValidationResult proto.
      """
      if tf.io.gfile.isdir(output_path):
          output_path = os.path.join(
              output_path, constants.VALIDATIONS_KEY
          )
      pattern = _match_all_files(output_path)
      if output_file_format:
          pattern = pattern + "." + output_file_format
      validation_records = []
      paths = tf.io.gfile.glob(pattern)
      for value in _raw_value_iterator(paths, output_file_format):
          validation_records.append(
              validation_result_pb2.ValidationResult.FromString(value)
          )
      assert len(validation_records) == 1
      return validation_records[0]
  
imports: import itertools
  import os
  from typing import Any, Dict, Iterable, Iterator, List, Optional, Tuple, Union
  from absl import logging
  import apache_beam
  import numpy
  import pyarrow
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.evaluators import evaluator
  from tensorflow_model_analysis.evaluators import metrics_validator
  from tensorflow_model_analysis.metrics import calibration_plot
  from tensorflow_model_analysis.metrics import confusion_matrix_plot
  from tensorflow_model_analysis.metrics import metric_specs
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.post_export_metrics import metric_keys
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.proto import metrics_for_slice_pb2
  from tensorflow_model_analysis.proto import validation_result_pb2
  from tensorflow_model_analysis.slicer import slicer_lib
  from tensorflow_model_analysis.utils import math_util
  from tensorflow_model_analysis.writers import writer
  from google.protobuf import wrappers_pb2
label_desc: Use image node_id 7 for calling a global function with example usage: load_and_deserialize_validation_result(output_path, output_file_format) and returns: validation_records