code: def _publish_rendered_dot_graph_file(
      self,
      preprocessing_fn,
      feature_spec,
      dataset_keys,
      pcoll_cache_dict,
      use_tf_compat_v1=True,
  ):
      specs = feature_spec
      base_temp_dir = None
      if not use_tf_compat_v1:
          specs = impl_helper.get_type_specs_from_feature_specs(specs)
          base_temp_dir = self.base_test_dir
      (
          graph,
          structured_inputs,
          structured_outputs,
      ) = impl_helper.trace_preprocessing_function(
          preprocessing_fn,
          specs,
          use_tf_compat_v1=use_tf_compat_v1,
          base_temp_dir=base_temp_dir,
      )
      (
          transform_fn_future,
          cache_output_dict,
          sideeffects,
      ) = analysis_graph_builder.build(
          graph,
          structured_inputs,
          structured_outputs,
          dataset_keys,
          pcoll_cache_dict,
      )
  
      def sort_value_node_values(cache_dict):
          result = []
          if cache_dict is None:
              return result
          for dataset_cache in cache_dict.values():
              result.extend(dataset_cache.values())
          return sorted(result, key=str)
  
      return self._publish_rendered_dot_graph_file_from_leaf_nodes(
          [transform_fn_future]
          + sort_value_node_values(cache_output_dict)
          + list(sideeffects)
      )
  
imports: import functools
  import os
  import struct
  from typing import Callable, Mapping, List
  import uuid
  import apache_beam
  from apache_beam.testing import util
  import numpy
  import tensorflow
  import tensorflow_transform
  from tensorflow_transform import analyzer_nodes
  from tensorflow_transform import common_types
  from tensorflow_transform import impl_helper
  from tensorflow_transform import nodes
  import tensorflow_transform.beam
  from tensorflow_transform.beam import analysis_graph_builder
  from tensorflow_transform.beam import analyzer_cache
  from tensorflow_transform.beam import tft_unit
  from tensorflow_transform.tf_metadata import dataset_metadata
  from tfx_bsl.types import tfx_namedtuple
label_desc: Use image node_id 5 for calling the CachedImplTest obj's underlying member method code with example usage: obj._publish_rendered_dot_graph_file(preprocessing_fn, feature_spec, dataset_keys, pcoll_cache_dict, use_tf_compat_v1) and returns: self, sorted, result