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()

```

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)

{"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"}]}