code: def call_function(args=None, kwargs=None, tracing_options=None):
      """Traces a function for args and kwargs and calls it after."""
      if not tracing_options:
          tracing_options = TracingOptions()
  
      args = args if args else ()
      kwargs = kwargs if kwargs else {}
      function = trace_function(
          args=args, kwargs=kwargs, tracing_options=tracing_options
      )
  
      # Bind it ourselves to skip unnecessary canonicalization of default call.
      bound_args = function.function_type.bind(*args, **kwargs)
      flat_inputs = function.function_type.unpack_inputs(bound_args)
      return function._call_flat(  # pylint: disable=protected-access
          flat_inputs, captured_inputs=function.captured_inputs
      )
  
imports: import contextlib
  import dataclasses
  import enum
  import threading
  from typing import Any, Callable, Dict, Optional, Tuple
  from tensorflow.core.function import trace_type
  from tensorflow.core.function.capture import capture_container
  from tensorflow.core.function.polymorphism import function_cache
  from tensorflow.core.function.polymorphism import function_type
  from tensorflow.python.autograph.core import ag_ctx
  from tensorflow.python.eager import monitoring
  from tensorflow.python.eager.polymorphic_function import attributes
  from tensorflow.python.eager.polymorphic_function import concrete_function
  from tensorflow.python.eager.polymorphic_function import function_context
  from tensorflow.python.eager.polymorphic_function import function_type_utils
  from tensorflow.python.eager.polymorphic_function import transform
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.profiler import trace
  from tensorflow.python.util import compat
label_desc: Use image node_id 1 for calling a global function with example usage: call_function(args, kwargs, tracing_options) and returns: function