code: def map_fn_v2(
      fn,
      elems,
      dtype=None,
      parallel_iterations=None,
      back_prop=True,
      swap_memory=False,
      infer_shape=True,
      name=None,
      fn_output_signature=None,
  ):
      """Transform `elems` by applying `fn` to each element unstacked on axis 0."""
      if fn_output_signature is None:
          fn_output_signature = dtype
      return map_fn(
          fn=fn,
          elems=elems,
          fn_output_signature=fn_output_signature,
          parallel_iterations=parallel_iterations,
          back_prop=back_prop,
          swap_memory=swap_memory,
          infer_shape=infer_shape,
          name=name,
      )
  
imports: import re
  from tensorflow.python.autograph.core import ag_ctx
  from tensorflow.python.autograph.impl import api
  from tensorflow.python.eager import context
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import type_spec
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import tensor_array_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import while_loop
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import deprecation
  from tensorflow.python.util import nest
  from tensorflow.python.util import variable_utils
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 9 for calling a global function with example usage: map_fn_v2(fn, elems, dtype, parallel_iterations, back_prop, swap_memory, infer_shape, name, fn_output_signature) and returns: map_fn