code: def _validate_inputs(concrete_function):
      """Raises error if input type is tf.Variable."""
      if any(
          isinstance(inp, resource_variable_ops.VariableSpec)
          for inp in nest.flatten(
              concrete_function.structured_input_signature
          )
      ):
          raise ValueError(
              f"Unable to serialize concrete_function '{concrete_function.name}'"
              "with tf.Variable input. Functions that expect tf.Variable "
              "inputs cannot be exported as signatures."
          )
  
imports: from absl import logging
  from tensorflow.python.eager import def_function
  from tensorflow.python.eager import function
  from tensorflow.python.eager.polymorphic_function import attributes
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.saved_model import function_serialization
  from tensorflow.python.saved_model import revived_types
  from tensorflow.python.saved_model import signature_constants
  from tensorflow.python.trackable import base
  from tensorflow.python.types import core
  from tensorflow.python.util import compat
  from tensorflow.python.util import nest
  from tensorflow.python.util.compat import collections_abc
label_desc: Use image node_id 3 for calling a global function with example usage: _validate_inputs(concrete_function) without return types