code: def _jvp_dispatch(
      op_name, attr_tuple, inputs, outputs, tangents, use_batch=False
  ):
      """Determine which forwardprop function to call."""
      # Note that this _TRACE_COUNT read races with writes. That's fine, it just
      # means we may trace a few more exact shapes before moving on to relaxation.
      if _TRACE_COUNT.get(op_name, 0) < _TRACE_COUNT_LIMIT:
          config = _jvp_exact_config
      else:
          config = _jvp_relaxed_config
      return tracing_compilation.call_function(
          (op_name, attr_tuple, inputs, outputs, tangents, use_batch),
          tracing_options=config,
      )
  
imports: import functools
  import threading
  from tensorflow.core.function.polymorphism import function_cache
  from tensorflow.python import pywrap_tfe
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import backprop_util
  from tensorflow.python.eager import execute
  from tensorflow.python.eager import forwardprop_util
  from tensorflow.python.eager.polymorphic_function import tracing_compilation
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops.parallel_for import control_flow_ops
  from tensorflow.python.ops.unconnected_gradients import UnconnectedGradients
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import nest
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 5 for calling a global function with example usage: _jvp_dispatch(op_name, attr_tuple, inputs, outputs, tangents, use_batch) and returns: tracing_compilation