code: def rfftn(
      x: JaxArray,
      s: Optional[Sequence[int]] = None,
      axes: Optional[Sequence[int]] = None,
      *,
      norm: str = "backward",
      out: Optional[JaxArray] = None,
  ) -> JaxArray:
      if not all(isinstance(j, int) for j in axes):
          raise ivy.utils.exceptions.IvyError(
              f"Expecting {axes} to be a sequence of integers <class integer>"
          )
      if s is None:
          s = (x.shape[axes[0]], x.shape[axes[1]])
      if all(j < -len(x.shape) for j in s):
          raise ivy.utils.exceptions.IvyError(
              f"Invalid dim {axes}, expecting ranging"
              f" from {-len(x.shape)} to {len(x.shape)-1}"
          )
      if not all(isinstance(j, int) for j in s):
          raise ivy.utils.exceptions.IvyError(
              f"Expecting {s} to be a sequence of integers <class integer>"
          )
      if all(j <= 1 for j in s):
          raise ivy.utils.exceptions.IvyError(
              f"Invalid data points {s}, expecting s points larger than 1"
          )
      if norm not in {"backward", "ortho", "forward"}:
          raise ivy.utils.exceptions.IvyError(
              f"Unrecognized normalization mode {norm}"
          )
      return jnp.fft.rfftn(x, s, axes, norm).astype(jnp.complex128)
  
imports: from typing import Optional, Union, Tuple, List, Literal, Sequence, Callable
  import jax
  import jax.lax
  import jax.numpy
  import math
  import ivy
  from ivy import output_to_native_arrays
  from ivy.functional.backends.jax import JaxArray
  from ivy.functional.backends.jax.random import RNG
  from ivy.functional.ivy.experimental.general import _correct_ivy_callable
  from ivy.functional.ivy.layers import _handle_padding, _validate_max_pool_params, _depth_max_pooling_helper
  from ivy.functional.ivy.experimental.layers import _padding_ceil_mode, _get_size
  from ivy.func_wrapper import with_supported_dtypes
  from ivy.func_wrapper import with_unsupported_dtypes
  from .None import backend_version
  from ivy.functional.backends.jax.experimental.manipulation import _to_nested_tuple
label_desc: Use image node_id 23 for calling a global function with example usage: rfftn(x, s, axes) and returns: jnp