We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
ifft2

ifft2


--- 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 # --- Helpers --- #
7 # --------------- #
8 
9 
10 def _swap_direction(norm):
11     try:
12         return _SWAP_DIRECTION_MAP[norm]
13     except KeyError:
14         raise ValueError(
15             f'Invalid norm value {norm}; should be "backward", "ortho" or "forward".'
16         ) from None
17 
18 
19 # --- Main --- #
20 # ------------ #
21 
22 
23 @to_ivy_arrays_and_back
24 def fft(a, n=None, axis=-1, norm=None):
25     return ivy.fft(ivy.astype(a, ivy.complex128), axis, norm=norm, n=n)
26 
27 
28 @with_unsupported_dtypes({"1.26.0 and below": ("int",)}, "numpy")
29 @to_ivy_arrays_and_back
30 def fftfreq(n, d=1.0):
31     if not isinstance(
32         n, (int, type(ivy.int8), type(ivy.int16), type(ivy.int32), type(ivy.int64))
33     ):
34         raise ValueError("n should be an integer")
35 
36     N = (n - 1) // 2 + 1
37     val = 1.0 / (n * d)
38     results = ivy.empty(tuple([n]), dtype=int)
39 
40     p1 = ivy.arange(0, N, dtype=int)
41     results[:N] = p1
42     p2 = ivy.arange(-(n // 2), 0, dtype=int)
43     results[N:] = p2
44 
45     return results * val
46 
47 
48 @to_ivy_arrays_and_back
49 @with_unsupported_dtypes({"1.26.0 and below": ("float16",)}, "numpy")
50 def fftshift(x, axes=None):
51     x = ivy.asarray(x)
52 
53     if axes is None:
54         axes = tuple(range(x.ndim))
55         shift = [(dim // 2) for dim in x.shape]
56     elif isinstance(
57         axes,
58         (int, type(ivy.uint8), type(ivy.uint16), type(ivy.uint32), type(ivy.uint64)),
59     ):
60         shift = x.shape[axes] // 2
61     else:
62         shift = [(x.shape[ax] // 2) for ax in axes]
63 
64     roll = ivy.roll(x, shift, axis=axes)
65 
66     return roll
67 
68 
69 @to_ivy_arrays_and_back
70 def ifft(a, n=None, axis=-1, norm=None):
71     a = ivy.array(a, dtype=ivy.complex128)
72     if norm is None:
73         norm = "backward"
74     return ivy.ifft(a, axis, norm=norm, n=n)
75 
76 
77 @with_unsupported_dtypes({"1.24.3 and below": ("float16",)}, "numpy")
78 @to_ivy_arrays_and_back
79 def ifftn(a, s=None, axes=None, norm=None):
80     a = ivy.asarray(a, dtype=ivy.complex128)
81     a = ivy.ifftn(a, s=s, axes=axes, norm=norm)
82     return a
83 
84 
85 @to_ivy_arrays_and_back
86 @with_unsupported_dtypes({"1.26.0 and below": ("float16",)}, "numpy")
87 def ifftshift(x, axes=None):
88     x = ivy.asarray(x)
89 
90     if axes is None:
91         axes = tuple(range(x.ndim))
92         shift = [-(dim // 2) for dim in x.shape]
93     elif isinstance(
94         axes,
95         (int, type(ivy.uint8), type(ivy.uint16), type(ivy.uint32), type(ivy.uint64)),
96     ):
97         shift = -(x.shape[axes] // 2)
98     else:
99         shift = [-(x.shape[ax] // 2) for ax in axes]
100 
101     roll = ivy.roll(x, shift, axis=axes)
102 
103     return roll
104 
105 
106 @with_unsupported_dtypes({"1.26.0 and below": ("float16",)}, "numpy")
107 @to_ivy_arrays_and_back
108 def ihfft(a, n=None, axis=-1, norm=None):
109     if n is None:
110         n = a.shape[axis]
111     norm = _swap_direction(norm)
112     output = ivy.conj(rfft(a, n, axis, norm=norm).ivy_array)
113     return output
114 
115 
116 @with_unsupported_dtypes({"1.26.0 and below": ("float16",)}, "numpy")
117 @to_ivy_arrays_and_back
118 def rfft(a, n=None, axis=-1, norm=None):
119     if norm is None:
120         norm = "backward"
121     a = ivy.array(a, dtype=ivy.float64)
122     return ivy.dft(a, axis=axis, inverse=False, onesided=True, dft_length=n, norm=norm)
123 
124 
125 @to_ivy_arrays_and_back
126 def rfftfreq(n, d=1.0):
127     if not isinstance(
128         n, (int, type(ivy.int8), type(ivy.int16), type(ivy.int32), type(ivy.int64))
129     ):
130         raise ValueError("n should be an integer")
131 
132     val = 1.0 / (n * d)
133     N = n // 2 + 1
134     results = ivy.arange(0, N, dtype=int)
135     return results * val
136 
137 
138 @with_unsupported_dtypes({"1.24.3 and below": ("float16",)}, "numpy")
139 @to_ivy_arrays_and_back
140 def rfftn(a, s=None, axes=None, norm=None):
141     a = ivy.asarray(a, dtype=ivy.complex128)
142     return ivy.rfftn(a, s=s, axes=axes, norm=norm)
143 
144 
145 _SWAP_DIRECTION_MAP = {
146     None: "forward",
147     "backward": "forward",
148     "ortho": "ortho",
149     "forward": "backward",
150 }
151
```
--- 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
@@ -74,6 +74,14 @@
     return ivy.ifft(a, axis, norm=norm, n=n)
 
 
+@with_unsupported_dtypes({"1.24.3 and below": ("float16",)}, "numpy")
+@to_ivy_arrays_and_back
+def ifft2(a, s=None, axes=(-2, -1), norm=None):
+    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 ifftn(a, s=None, axes=None, norm=None):

{"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@@ -74,6 +74,14 @@\n     return ivy.ifft(a, axis, norm=norm, n=n)\n \n \n+@with_unsupported_dtypes({\"1.24.3 and below\": (\"float16\",)}, \"numpy\")\n+@to_ivy_arrays_and_back\n+def ifft2(a, s=None, axes=(-2, -1), 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\n def ifftn(a, s=None, axes=None, norm=None):\n", "issue": "ifft2\n\nifft2\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# --- Helpers --- #\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# --- Main --- #\n# ------------ #\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@with_unsupported_dtypes({\"1.26.0 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\n@with_unsupported_dtypes({\"1.26.0 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@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@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@to_ivy_arrays_and_back\n@with_unsupported_dtypes({\"1.26.0 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@with_unsupported_dtypes({\"1.26.0 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({\"1.26.0 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@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 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\n\n_SWAP_DIRECTION_MAP = {\n    None: \"forward\",\n    \"backward\": \"forward\",\n    \"ortho\": \"ortho\",\n    \"forward\": \"backward\",\n}\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# --- Helpers --- #\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# --- Main --- #\n# ------------ #\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@with_unsupported_dtypes({\"1.26.0 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\n@with_unsupported_dtypes({\"1.26.0 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@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@with_unsupported_dtypes({\"1.24.3 and below\": (\"float16\",)}, \"numpy\")\n@to_ivy_arrays_and_back\ndef ifft2(a, s=None, axes=(-2, -1), 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 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@to_ivy_arrays_and_back\n@with_unsupported_dtypes({\"1.26.0 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@with_unsupported_dtypes({\"1.26.0 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({\"1.26.0 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@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 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\n\n_SWAP_DIRECTION_MAP = {\n    None: \"forward\",\n    \"backward\": \"forward\",\n    \"ortho\": \"ortho\",\n    \"forward\": \"backward\",\n}\n", "path": "ivy/functional/frontends/numpy/fft/discrete_fourier_transform.py"}]}