code: def _validate_analyzers_fingerprint(
      baseline_analyzers_fingerprint: Mapping[
          str, graph_tools.AnalyzersFingerprint
      ],
      graph: tf.Graph,
      structured_inputs: Mapping[str, common_types.TensorType],
  ):
      """Validates analyzers fingerprint in `graph` is same as baseline."""
      analyzers_fingerprint = graph_tools.get_analyzers_fingerprint(
          graph, structured_inputs
      )
      error_msg = (
          "The order of analyzers in your `preprocessing_fn` appears to be "
          "non-deterministic. This can be fixed either by changing your "
          "`preprocessing_fn` such that tf.Transform analyzers are encountered "
          "in a deterministic order or by passing a unique name to each "
          "analyzer API call."
      )
      for analyzer in analyzers_fingerprint:
          if analyzer not in baseline_analyzers_fingerprint:
              prefix_msg = (
                  f"Analyzer node ({analyzer}) not found in "
                  f"{baseline_analyzers_fingerprint.keys()}. "
              )
              raise RuntimeError(prefix_msg + error_msg)
          if (
              baseline_analyzers_fingerprint[analyzer].source_keys
              != analyzers_fingerprint[analyzer].source_keys
          ):
              raise RuntimeError(error_msg)
  
          if (
              baseline_analyzers_fingerprint[analyzer].unique_path_hash
              != analyzers_fingerprint[analyzer].unique_path_hash
          ):
              logging.warning(
                  "Analyzer (%s) node's cache key varies on repeated tracing."
                  " This warning is safe to ignore if you either specify `name` for all"
                  " analyzers or if the order in which they are invoked is"
                  " deterministic. If not, please file a bug with details.",
                  analyzer,
              )
  
imports: import functools
  import os
  import re
  from typing import Callable, Dict, List, Mapping, Optional, FrozenSet
  from absl import logging
  import numpy
  import pyarrow
  import tensorflow
  from tensorflow_transform import analyzer_nodes
  from tensorflow_transform import annotators
  from tensorflow_transform import common_types
  from tensorflow_transform import graph_context
  from tensorflow_transform import graph_tools
  from tensorflow_transform import schema_inference
  from tensorflow_transform import tf2_utils
  from tensorflow_transform import tf_utils
  from tensorflow_transform.output_wrapper import TFTransformOutput
  from tensorflow_transform.saved import saved_transform_io
  from tensorflow_transform.saved import saved_transform_io_v2
  from tensorflow_transform.tf_metadata import dataset_metadata
  from tensorflow_transform.tf_metadata import metadata_io
  from tensorflow_transform.tf_metadata import schema_utils
  from tfx_bsl.coders import example_coder
  from tfx_bsl.tfxio import tensor_to_arrow
  from tensorflow.python.eager import function
  from tensorflow.python.framework import ops
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 17 for calling a global function with example usage: _validate_analyzers_fingerprint(baseline_analyzers_fingerprint, graph, structured_inputs) without return types