code: def has_internal_compute_graph(input_object: Any):
      """Checks if input is a TF model and has a TF internal compute graph."""
      return (
          isinstance(input_object, tf.keras.Model)
          and hasattr(input_object, "_flatten_to_reference_inputs")
          and hasattr(input_object, "_tensor_usage_count")
          and hasattr(input_object, "_conform_to_reference_input")
          and hasattr(input_object, "_nodes_by_depth")
      )
  
file_path: privacy/tensorflow_privacy/privacy/fast_gradient_clipping/gradient_clipping_utils.py
imports: from collections.abc import Sequence, Set
  from typing import Any, Literal, Optional
  from absl import logging
  import tensorflow
  from tensorflow_privacy.privacy.fast_gradient_clipping import layer_registry
  from tensorflow_privacy.privacy.fast_gradient_clipping import type_aliases
label_desc: Use image node_id 1 for calling a global function with example usage: has_internal_compute_graph(input_object) and returns: unknown