prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  rfftn
  
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py`
  Content:
  ```
  1 import ivy
  2 from ivy.functional.frontends.numpy.func_wrapper import to_ivy_arrays_and_back
  3 from ivy.func_wrapper import with_unsupported_dtypes
  4 
  5 
  6 _SWAP_DIRECTION_MAP = {
  7     None: "forward",
  8     "backward": "forward",
  9     "ortho": "ortho",
  10     "forward": "backward",
  11 }
  12 
  13 
  14 def _swap_direction(norm):
  15     try:
  16         return _SWAP_DIRECTION_MAP[norm]
  17     except KeyError:
  18         raise ValueError(
  19             f'Invalid norm value {norm}; should be "backward", "ortho" or "forward".'
  20         ) from None
  21 
  22 
  23 @to_ivy_arrays_and_back
  24 def ifft(a, n=None, axis=-1, norm=None):
  25     a = ivy.array(a, dtype=ivy.complex128)
  26     if norm is None:
  27         norm = "backward"
  28     return ivy.ifft(a, axis, norm=norm, n=n)
  29 
  30 
  31 @to_ivy_arrays_and_back
  32 @with_unsupported_dtypes({"1.25.1 and below": ("float16",)}, "numpy")
  33 def ifftshift(x, axes=None):
  34     x = ivy.asarray(x)
  35 
  36     if axes is None:
  37         axes = tuple(range(x.ndim))
  38         shift = [-(dim // 2) for dim in x.shape]
  39     elif isinstance(
  40         axes,
  41         (int, type(ivy.uint8), type(ivy.uint16), type(ivy.uint32), type(ivy.uint64)),
  42     ):
  43         shift = -(x.shape[axes] // 2)
  44     else:
  45         shift = [-(x.shape[ax] // 2) for ax in axes]
  46 
  47     roll = ivy.roll(x, shift, axis=axes)
  48 
  49     return roll
  50 
  51 
  52 @to_ivy_arrays_and_back
  53 def fft(a, n=None, axis=-1, norm=None):
  54     return ivy.fft(ivy.astype(a, ivy.complex128), axis, norm=norm, n=n)
  55 
  56 
  57 @to_ivy_arrays_and_back
  58 @with_unsupported_dtypes({"1.25.1 and below": ("float16",)}, "numpy")
  59 def fftshift(x, axes=None):
  60     x = ivy.asarray(x)
  61 
  62     if axes is None:
  63         axes = tuple(range(x.ndim))
  64         shift = [(dim // 2) for dim in x.shape]
  65     elif isinstance(
  66         axes,
  67         (int, type(ivy.uint8), type(ivy.uint16), type(ivy.uint32), type(ivy.uint64)),
  68     ):
  69         shift = x.shape[axes] // 2
  70     else:
  71         shift = [(x.shape[ax] // 2) for ax in axes]
  72 
  73     roll = ivy.roll(x, shift, axis=axes)
  74 
  75     return roll
  76 
  77 
  78 @with_unsupported_dtypes({"1.25.1 and below": ("float16",)}, "numpy")
  79 @to_ivy_arrays_and_back
  80 def rfft(a, n=None, axis=-1, norm=None):
  81     if norm is None:
  82         norm = "backward"
  83     a = ivy.array(a, dtype=ivy.float64)
  84     return ivy.dft(a, axis=axis, inverse=False, onesided=True, dft_length=n, norm=norm)
  85 
  86 
  87 @with_unsupported_dtypes({"1.25.1 and below": ("float16",)}, "numpy")
  88 @to_ivy_arrays_and_back
  89 def ihfft(a, n=None, axis=-1, norm=None):
  90     if n is None:
  91         n = a.shape[axis]
  92     norm = _swap_direction(norm)
  93     output = ivy.conj(rfft(a, n, axis, norm=norm).ivy_array)
  94     return output
  95 
  96 
  97 @with_unsupported_dtypes({"1.25.1 and below": ("int",)}, "numpy")
  98 @to_ivy_arrays_and_back
  99 def fftfreq(n, d=1.0):
  100     if not isinstance(
  101         n, (int, type(ivy.int8), type(ivy.int16), type(ivy.int32), type(ivy.int64))
  102     ):
  103         raise ValueError("n should be an integer")
  104 
  105     N = (n - 1) // 2 + 1
  106     val = 1.0 / (n * d)
  107     results = ivy.empty(tuple([n]), dtype=int)
  108 
  109     p1 = ivy.arange(0, N, dtype=int)
  110     results[:N] = p1
  111     p2 = ivy.arange(-(n // 2), 0, dtype=int)
  112     results[N:] = p2
  113 
  114     return results * val
  115 
  116 
  117 @to_ivy_arrays_and_back
  118 def rfftfreq(n, d=1.0):
  119     if not isinstance(
  120         n, (int, type(ivy.int8), type(ivy.int16), type(ivy.int32), type(ivy.int64))
  121     ):
  122         raise ValueError("n should be an integer")
  123 
  124     val = 1.0 / (n * d)
  125     N = n // 2 + 1
  126     results = ivy.arange(0, N, dtype=int)
  127     return results * val
  128 
  129 
  130 @with_unsupported_dtypes({"1.24.3 and below": ("float16",)}, "numpy")
  131 @to_ivy_arrays_and_back
  132 def ifftn(a, s=None, axes=None, norm=None):
  133     a = ivy.asarray(a, dtype=ivy.complex128)
  134     a = ivy.ifftn(a, s=s, axes=axes, norm=norm)
  135     return a
  136
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py b/ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py
  --- a/ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py
  +++ b/ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py
  @@ -133,3 +133,10 @@
       a = ivy.asarray(a, dtype=ivy.complex128)
       a = ivy.ifftn(a, s=s, axes=axes, norm=norm)
       return a
  +
  +
  +@with_unsupported_dtypes({"1.24.3 and below": ("float16",)}, "numpy")
  +@to_ivy_arrays_and_back
  +def rfftn(a, s=None, axes=None, norm=None):
  +    a = ivy.asarray(a, dtype=ivy.complex128)
  +    return ivy.rfftn(a, s=s, axes=axes, norm=norm)
  
verification_info: {"golden_diff": "diff --git a/ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py b/ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py\n--- a/ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py\n+++ b/ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py\n@@ -133,3 +133,10 @@\n     a = ivy.asarray(a, dtype=ivy.complex128)\n     a = ivy.ifftn(a, s=s, axes=axes, norm=norm)\n     return a\n+\n+\n+@with_unsupported_dtypes({\"1.24.3 and below\": (\"float16\",)}, \"numpy\")\n+@to_ivy_arrays_and_back\n+def rfftn(a, s=None, axes=None, norm=None):\n+    a = ivy.asarray(a, dtype=ivy.complex128)\n+    return ivy.rfftn(a, s=s, axes=axes, norm=norm)\n", "issue": "rfftn\n\n", "before_files": [{"content": "import ivy\nfrom ivy.functional.frontends.numpy.func_wrapper import to_ivy_arrays_and_back\nfrom ivy.func_wrapper import with_unsupported_dtypes\n\n\n_SWAP_DIRECTION_MAP = {\n    None: \"forward\",\n    \"backward\": \"forward\",\n    \"ortho\": \"ortho\",\n    \"forward\": \"backward\",\n}\n\n\ndef _swap_direction(norm):\n    try:\n        return _SWAP_DIRECTION_MAP[norm]\n    except KeyError:\n        raise ValueError(\n            f'Invalid norm value {norm}; should be \"backward\", \"ortho\" or \"forward\".'\n        ) from None\n\n\n@to_ivy_arrays_and_back\ndef ifft(a, n=None, axis=-1, norm=None):\n    a = ivy.array(a, dtype=ivy.complex128)\n    if norm is None:\n        norm = \"backward\"\n    return ivy.ifft(a, axis, norm=norm, n=n)\n\n\n@to_ivy_arrays_and_back\n@with_unsupported_dtypes({\"1.25.1 and below\": (\"float16\",)}, \"numpy\")\ndef ifftshift(x, axes=None):\n    x = ivy.asarray(x)\n\n    if axes is None:\n        axes = tuple(range(x.ndim))\n        shift = [-(dim // 2) for dim in x.shape]\n    elif isinstance(\n        axes,\n        (int, type(ivy.uint8), type(ivy.uint16), type(ivy.uint32), type(ivy.uint64)),\n    ):\n        shift = -(x.shape[axes] // 2)\n    else:\n        shift = [-(x.shape[ax] // 2) for ax in axes]\n\n    roll = ivy.roll(x, shift, axis=axes)\n\n    return roll\n\n\n@to_ivy_arrays_and_back\ndef fft(a, n=None, axis=-1, norm=None):\n    return ivy.fft(ivy.astype(a, ivy.complex128), axis, norm=norm, n=n)\n\n\n@to_ivy_arrays_and_back\n@with_unsupported_dtypes({\"1.25.1 and below\": (\"float16\",)}, \"numpy\")\ndef fftshift(x, axes=None):\n    x = ivy.asarray(x)\n\n    if axes is None:\n        axes = tuple(range(x.ndim))\n        shift = [(dim // 2) for dim in x.shape]\n    elif isinstance(\n        axes,\n        (int, type(ivy.uint8), type(ivy.uint16), type(ivy.uint32), type(ivy.uint64)),\n    ):\n        shift = x.shape[axes] // 2\n    else:\n        shift = [(x.shape[ax] // 2) for ax in axes]\n\n    roll = ivy.roll(x, shift, axis=axes)\n\n    return roll\n\n\n@with_unsupported_dtypes({\"1.25.1 and below\": (\"float16\",)}, \"numpy\")\n@to_ivy_arrays_and_back\ndef rfft(a, n=None, axis=-1, norm=None):\n    if norm is None:\n        norm = \"backward\"\n    a = ivy.array(a, dtype=ivy.float64)\n    return ivy.dft(a, axis=axis, inverse=False, onesided=True, dft_length=n, norm=norm)\n\n\n@with_unsupported_dtypes({\"1.25.1 and below\": (\"float16\",)}, \"numpy\")\n@to_ivy_arrays_and_back\ndef ihfft(a, n=None, axis=-1, norm=None):\n    if n is None:\n        n = a.shape[axis]\n    norm = _swap_direction(norm)\n    output = ivy.conj(rfft(a, n, axis, norm=norm).ivy_array)\n    return output\n\n\n@with_unsupported_dtypes({\"1.25.1 and below\": (\"int\",)}, \"numpy\")\n@to_ivy_arrays_and_back\ndef fftfreq(n, d=1.0):\n    if not isinstance(\n        n, (int, type(ivy.int8), type(ivy.int16), type(ivy.int32), type(ivy.int64))\n    ):\n        raise ValueError(\"n should be an integer\")\n\n    N = (n - 1) // 2 + 1\n    val = 1.0 / (n * d)\n    results = ivy.empty(tuple([n]), dtype=int)\n\n    p1 = ivy.arange(0, N, dtype=int)\n    results[:N] = p1\n    p2 = ivy.arange(-(n // 2), 0, dtype=int)\n    results[N:] = p2\n\n    return results * val\n\n\n@to_ivy_arrays_and_back\ndef rfftfreq(n, d=1.0):\n    if not isinstance(\n        n, (int, type(ivy.int8), type(ivy.int16), type(ivy.int32), type(ivy.int64))\n    ):\n        raise ValueError(\"n should be an integer\")\n\n    val = 1.0 / (n * d)\n    N = n // 2 + 1\n    results = ivy.arange(0, N, dtype=int)\n    return results * val\n\n\n@with_unsupported_dtypes({\"1.24.3 and below\": (\"float16\",)}, \"numpy\")\n@to_ivy_arrays_and_back\ndef ifftn(a, s=None, axes=None, norm=None):\n    a = ivy.asarray(a, dtype=ivy.complex128)\n    a = ivy.ifftn(a, s=s, axes=axes, norm=norm)\n    return a\n", "path": "ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py"}], "after_files": [{"content": "import ivy\nfrom ivy.functional.frontends.numpy.func_wrapper import to_ivy_arrays_and_back\nfrom ivy.func_wrapper import with_unsupported_dtypes\n\n\n_SWAP_DIRECTION_MAP = {\n    None: \"forward\",\n    \"backward\": \"forward\",\n    \"ortho\": \"ortho\",\n    \"forward\": \"backward\",\n}\n\n\ndef _swap_direction(norm):\n    try:\n        return _SWAP_DIRECTION_MAP[norm]\n    except KeyError:\n        raise ValueError(\n            f'Invalid norm value {norm}; should be \"backward\", \"ortho\" or \"forward\".'\n        ) from None\n\n\n@to_ivy_arrays_and_back\ndef ifft(a, n=None, axis=-1, norm=None):\n    a = ivy.array(a, dtype=ivy.complex128)\n    if norm is None:\n        norm = \"backward\"\n    return ivy.ifft(a, axis, norm=norm, n=n)\n\n\n@to_ivy_arrays_and_back\n@with_unsupported_dtypes({\"1.25.1 and below\": (\"float16\",)}, \"numpy\")\ndef ifftshift(x, axes=None):\n    x = ivy.asarray(x)\n\n    if axes is None:\n        axes = tuple(range(x.ndim))\n        shift = [-(dim // 2) for dim in x.shape]\n    elif isinstance(\n        axes,\n        (int, type(ivy.uint8), type(ivy.uint16), type(ivy.uint32), type(ivy.uint64)),\n    ):\n        shift = -(x.shape[axes] // 2)\n    else:\n        shift = [-(x.shape[ax] // 2) for ax in axes]\n\n    roll = ivy.roll(x, shift, axis=axes)\n\n    return roll\n\n\n@to_ivy_arrays_and_back\ndef fft(a, n=None, axis=-1, norm=None):\n    return ivy.fft(ivy.astype(a, ivy.complex128), axis, norm=norm, n=n)\n\n\n@to_ivy_arrays_and_back\n@with_unsupported_dtypes({\"1.25.1 and below\": (\"float16\",)}, \"numpy\")\ndef fftshift(x, axes=None):\n    x = ivy.asarray(x)\n\n    if axes is None:\n        axes = tuple(range(x.ndim))\n        shift = [(dim // 2) for dim in x.shape]\n    elif isinstance(\n        axes,\n        (int, type(ivy.uint8), type(ivy.uint16), type(ivy.uint32), type(ivy.uint64)),\n    ):\n        shift = x.shape[axes] // 2\n    else:\n        shift = [(x.shape[ax] // 2) for ax in axes]\n\n    roll = ivy.roll(x, shift, axis=axes)\n\n    return roll\n\n\n@with_unsupported_dtypes({\"1.25.1 and below\": (\"float16\",)}, \"numpy\")\n@to_ivy_arrays_and_back\ndef rfft(a, n=None, axis=-1, norm=None):\n    if norm is None:\n        norm = \"backward\"\n    a = ivy.array(a, dtype=ivy.float64)\n    return ivy.dft(a, axis=axis, inverse=False, onesided=True, dft_length=n, norm=norm)\n\n\n@with_unsupported_dtypes({\"1.25.1 and below\": (\"float16\",)}, \"numpy\")\n@to_ivy_arrays_and_back\ndef ihfft(a, n=None, axis=-1, norm=None):\n    if n is None:\n        n = a.shape[axis]\n    norm = _swap_direction(norm)\n    output = ivy.conj(rfft(a, n, axis, norm=norm).ivy_array)\n    return output\n\n\n@with_unsupported_dtypes({\"1.25.1 and below\": (\"int\",)}, \"numpy\")\n@to_ivy_arrays_and_back\ndef fftfreq(n, d=1.0):\n    if not isinstance(\n        n, (int, type(ivy.int8), type(ivy.int16), type(ivy.int32), type(ivy.int64))\n    ):\n        raise ValueError(\"n should be an integer\")\n\n    N = (n - 1) // 2 + 1\n    val = 1.0 / (n * d)\n    results = ivy.empty(tuple([n]), dtype=int)\n\n    p1 = ivy.arange(0, N, dtype=int)\n    results[:N] = p1\n    p2 = ivy.arange(-(n // 2), 0, dtype=int)\n    results[N:] = p2\n\n    return results * val\n\n\n@to_ivy_arrays_and_back\ndef rfftfreq(n, d=1.0):\n    if not isinstance(\n        n, (int, type(ivy.int8), type(ivy.int16), type(ivy.int32), type(ivy.int64))\n    ):\n        raise ValueError(\"n should be an integer\")\n\n    val = 1.0 / (n * d)\n    N = n // 2 + 1\n    results = ivy.arange(0, N, dtype=int)\n    return results * val\n\n\n@with_unsupported_dtypes({\"1.24.3 and below\": (\"float16\",)}, \"numpy\")\n@to_ivy_arrays_and_back\ndef ifftn(a, s=None, axes=None, norm=None):\n    a = ivy.asarray(a, dtype=ivy.complex128)\n    a = ivy.ifftn(a, s=s, axes=axes, norm=norm)\n    return a\n\n\n@with_unsupported_dtypes({\"1.24.3 and below\": (\"float16\",)}, \"numpy\")\n@to_ivy_arrays_and_back\ndef rfftn(a, s=None, axes=None, norm=None):\n    a = ivy.asarray(a, dtype=ivy.complex128)\n    return ivy.rfftn(a, s=s, axes=axes, norm=norm)\n", "path": "ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py"}]}