docstr: Compute the n-dimensional discrete Fourier Transform for real input.
  
  Parameters
  ----------
  axes : int or tuple of ints, optional
      Axes over which to compute the FFT. If not given, the last `n` axes are
      used.
  s : sequence of ints, optional
      Shape (length of each transformed axis) of the output. Along each axis,
      if the given shape is smaller than
      that of the input, the input is cropped. If it is larger, the input
      is padded with zeros.
  norm : {'backward', 'ortho', 'forward'}, optional
      Normalization mode. Default is 'backward'.
  out : array-like, optional
      Output array. Must have the same shape and type as the expected output.
  
  Returns
  -------
  transformed : Container
      The n-dimensional discrete Fourier Transform of the input.
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code: def rfftn(
      self: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      s: Optional[Union[Sequence[int], ivy.Container]] = None,
      axes: Optional[Union[int, Tuple[int], ivy.Container]] = None,
      *,
      norm: Union[str, ivy.Container] = "backward",
      out: Optional[Union[ivy.Array, ivy.Container]] = None,
  ) -> ivy.Container:
      """Compute the n-dimensional discrete Fourier Transform for real input.
  
      Parameters
      ----------
      axes : int or tuple of ints, optional
          Axes over which to compute the FFT. If not given, the last `n` axes are
          used.
      s : sequence of ints, optional
          Shape (length of each transformed axis) of the output. Along each axis,
          if the given shape is smaller than
          that of the input, the input is cropped. If it is larger, the input
          is padded with zeros.
      norm : {'backward', 'ortho', 'forward'}, optional
          Normalization mode. Default is 'backward'.
      out : array-like, optional
          Output array. Must have the same shape and type as the expected output.
  
      Returns
      -------
      transformed : Container
          The n-dimensional discrete Fourier Transform of the input.
      """
      return self.static_rfftn(
          self,
          s=s,
          axes=axes,
          norm=norm,
          out=out,
      )
  
imports: from typing import Optional, Union, List, Dict, Tuple, Literal, Sequence, Callable
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 38 for calling the _ContainerWithLayersExperimental obj's underlying member method code with example usage: obj.rfftn(s, axes) and returns: self