docstr: ivy.Container static method variant of ivy.rfftn.
  
  This method simply wraps the function, and so the docstring for
  ivy.rfftn also applies to this method with minimal changes.
  
  Parameters
  ----------
  x
      Input array of real numbers.
  
  s
      sequence of ints, optional
      Shape (length of transformed axis) to use from the input (`s[0]` refers to
      axis 0,`s[1]` to axis 1, etc.). The final element of `s` corresponds to `n`
      for `rfft(x, n)`, while for the remaining axes, it corresponds to `n` for
      `fft(x, n)`. Along any 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.
      If `s` is not given, the shape of the input along the axes specified by
      `axes` is used.
  
  axes
      sequence of ints, optional
      Axes over which to compute the FFT. If not given, the last `len(s)` axes
      are used, or all axes if `s` is also not specified.
  
  norm
      Optional argument, "backward", "ortho" or "forward".
      Defaults to be "backward".
      "backward" indicates no normalization.
      "ortho" indicates normalization by 1/sqrt(n).
      "forward" indicates normalization by 1/n.
  
  out
      Optional output array, for writing the result to. It must have a shape that
      the inputs broadcast to.
  
  Returns
  -------
  ret
      The truncated or zero-padded input, transformed along the axes indicated by
      `axes` or by a combination of `s` or `x`, as explained in the parameters
      section above.
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code: def static_rfftn(
      x: ivy.Container,
      s: Optional[Union[int, Tuple[int, ...], ivy.Container]] = None,
      axes: Optional[Union[int, Tuple[int, ...], ivy.Container]] = None,
      *,
      norm: Union[str, ivy.Container] = "backward",
      key_chains: Optional[
          Union[List[str], Dict[str, str], ivy.Container]
      ] = None,
      to_apply: Union[bool, ivy.Container] = True,
      prune_unapplied: Union[bool, ivy.Container] = False,
      map_sequences: Union[bool, ivy.Container] = False,
      out: Optional[ivy.Container] = None,
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.rfftn.
  
      This method simply wraps the function, and so the docstring for
      ivy.rfftn also applies to this method with minimal changes.
  
      Parameters
      ----------
      x
          Input array of real numbers.
  
      s
          sequence of ints, optional
          Shape (length of transformed axis) to use from the input (`s[0]` refers to
          axis 0,`s[1]` to axis 1, etc.). The final element of `s` corresponds to `n`
          for `rfft(x, n)`, while for the remaining axes, it corresponds to `n` for
          `fft(x, n)`. Along any 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.
          If `s` is not given, the shape of the input along the axes specified by
          `axes` is used.
  
      axes
          sequence of ints, optional
          Axes over which to compute the FFT. If not given, the last `len(s)` axes
          are used, or all axes if `s` is also not specified.
  
      norm
          Optional argument, "backward", "ortho" or "forward".
          Defaults to be "backward".
          "backward" indicates no normalization.
          "ortho" indicates normalization by 1/sqrt(n).
          "forward" indicates normalization by 1/n.
  
      out
          Optional output array, for writing the result to. It must have a shape that
          the inputs broadcast to.
  
      Returns
      -------
      ret
          The truncated or zero-padded input, transformed along the axes indicated by
          `axes` or by a combination of `s` or `x`, as explained in the parameters
          section above.
      """
      return ContainerBase.cont_multi_map_in_function(
          "rfftn",
          x,
          s=s,
          axes=axes,
          norm=norm,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          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 37 for calling the _ContainerWithLayersExperimental obj's underlying member method code with example usage: obj.static_rfftn(x, s, axes) and returns: ContainerBase