code: def _get_flattened_feature_values_without_nulls(
      feature_array: pa.Array,
  ) -> List[Any]:
      """Flattens the feature array into a List and removes null values.
  
      Args:
        feature_array: Arrow Array.
  
      Returns:
        A list containing the flattened feature values with nulls removed.
      """
      non_missing_values = np.asarray(
          array_util.flatten_nested(feature_array)[0]
      )
      return list(non_missing_values[~pd.isnull(non_missing_values)])
  
imports: import collections
  from typing import Any, Dict, Iterable, List, Optional, Set, Tuple
  from absl import logging
  import apache_beam
  import numpy
  import pandas
  import pyarrow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import partitioned_stats_generator
  from tensorflow_data_validation.utils import feature_partition_util
  from tensorflow_data_validation.utils import mutual_information_util
  from tensorflow_data_validation.utils import schema_util
  from tensorflow_data_validation.utils import stats_util
  from tfx_bsl.arrow import array_util
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 1 for calling a global function with example usage: _get_flattened_feature_values_without_nulls(feature_array) and returns: list