code: def get_analyzers_fingerprint(
      graph: tf.Graph,
      structured_inputs: Mapping[str, common_types.TensorType],
  ) -> Mapping[str, AnalyzersFingerprint]:
      """Computes fingerprints for all analyzers in `graph`.
  
      Args:
        graph: a TF Graph.
        structured_inputs: a dict from keys to batches of placeholder graph tensors.
  
      Returns:
        A mapping from analyzer name to a set of paths that define its fingerprint.
      """
      result = {}
      tensor_sinks = graph.get_collection(
          analyzer_nodes.ALL_REPLACEMENTS
      )
      # The value for the keys in this dictionary are unused and can be arbitrary.
      sink_tensors_ready = {
          tf_utils.hashable_tensor_or_op(tensor_sink.tensor): False
          for tensor_sink in tensor_sinks
      }
      graph_analyzer = InitializableGraphAnalyzer(
          graph,
          structured_inputs,
          list(sink_tensors_ready.items()),
          describe_path_as_analyzer_cache_hash,
      )
      for tensor_sink in tensor_sinks:
          # Retrieve tensors that are inputs to the analyzer's value node.
          visitor = SourcedTensorsVisitor()
          nodes.Traverser(visitor).visit_value_node(tensor_sink.future)
          source_keys = _retrieve_source_keys(
              visitor.sourced_tensors, structured_inputs
          )
          paths = set()
          for tensor in visitor.sourced_tensors:
              # Obtain fingerprint for each tensor that is an input to the value node.
              path = graph_analyzer.get_unique_path(tensor)
              if path is not None:
                  paths.add(path)
          result[str(tensor_sink.tensor.name)] = AnalyzersFingerprint(
              source_keys, paths
          )
      return result
  
imports: import collections
  import copy
  import hashlib
  import itertools
  from typing import Iterable, List, Mapping, Optional, Set, Union
  import uuid
  from absl import logging
  import tensorflow
  from tensorflow_transform import analyzer_nodes
  from tensorflow_transform import common_types
  from tensorflow_transform import nodes
  from tensorflow_transform import tf_utils
  from tfx_bsl.types import tfx_namedtuple
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import function_def_to_graph
  from tensorflow.python.util import object_identity
label_desc: Use image node_id 10 for calling a global function with example usage: get_analyzers_fingerprint(graph, structured_inputs) and returns: result