code: def ifftn(
      x: JaxArray,
      s: Optional[Union[int, Tuple[int]]] = None,
      axes: Optional[Union[int, Tuple[int]]] = None,
      *,
      norm: str = "backward",
      out: Optional[JaxArray] = None,
  ) -> JaxArray:
      return jnp.fft.ifftn(x, s, axes, norm)
  
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 20 for calling a global function with example usage: ifftn(x, s, axes) and returns: jnp