We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
[Bug, Enhancement] array_equal returns False on identical arrays with NaN values
* Conditions (you can just paste the output of `python -c 'import cupy; cupy.show_config()'`)
  - CuPy Version          : 8.0.0
  - OS/Platform : Pop OS
  - CUDA Version    : 10000
  - cuDNN Version         : 7605
  - NCCL Version    : 2604

* Code to reproduce
```python
import cupy as cp
a = cp.array([0, 1, cp.nan])
print(cp.array_equal(a, a))         # False
```
This relates exactly with https://github.com/numpy/numpy/issues/9229
This could be resolved by following the same procedure, resolved by https://github.com/numpy/numpy/pull/16128, which would essentially add an `equal_nan` kwarg to let user decide if NaN values should be considered equal or not, which is consistent with: https://github.com/cupy/cupy/blob/0dc6bbafb0cf75bb873531cbf69c6995a72c61a3/cupy/_logic/comparison.py#L60
https://github.com/cupy/cupy/blob/0dc6bbafb0cf75bb873531cbf69c6995a72c61a3/cupy/_logic/comparison.py#L89

* Error messages, stack traces, or logs
`<null>`

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `cupy/_logic/comparison.py`
Content:
```
1 import numpy
2 
3 import cupy
4 from cupy import core
5 
6 
7 _is_close = core.create_ufunc(
8     'cupy_is_close',
9     ('eeee?->?', 'ffff?->?', 'dddd?->?'),
10     '''
11     bool equal_nan = in4;
12     if (isfinite(in0) && isfinite(in1)) {
13       out0 = fabs(in0 - in1) <= in3 + in2 * fabs(in1);
14     } else if (equal_nan) {
15       out0 = (in0 == in1) || (isnan(in0) && isnan(in1));
16     } else {
17       out0 = (in0 == in1);
18     }
19     '''
20 )
21 
22 # Note that in cupy/core/include/cupy/complex.cuh, we already got isfinite and
23 # isnan working for complex numbers, so just replace fabs above by abs (from
24 # thrust) and we are ready to go
25 _is_close_complex = core.create_ufunc(
26     'cupy_is_close_complex',
27     ('FFff?->?', 'DDdd?->?'),
28     '''
29     bool equal_nan = in4;
30     if (isfinite(in0) && isfinite(in1)) {
31       out0 = abs(in0 - in1) <= in3 + in2 * abs(in1);
32     } else if (equal_nan) {
33       out0 = (in0 == in1) || (isnan(in0) && isnan(in1));
34     } else {
35       out0 = (in0 == in1);
36     }
37     '''
38 )
39 
40 
41 def array_equal(a1, a2):
42     """Returns ``True`` if two arrays are element-wise exactly equal.
43 
44     Args:
45         a1 (cupy.ndarray): Input array to compare.
46         a2 (cupy.ndarray): Input array to compare.
47 
48     Returns:
49         cupy.ndarray: A boolean 0-dim array.
50             If its value is ``True``, two arrays are element-wise equal.
51 
52     .. seealso:: :func:`numpy.array_equal`
53 
54     """
55     if a1.shape != a2.shape:
56         return cupy.array(False)
57     return (a1 == a2).all()
58 
59 
60 def allclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):
61     """Returns True if two arrays are element-wise equal within a tolerance.
62 
63     Two values in ``a`` and ``b`` are  considiered equal when the following
64     equation is satisfied.
65 
66     .. math::
67 
68        |a - b| \\le \\mathrm{atol} + \\mathrm{rtol} |b|
69 
70     Args:
71         a (cupy.ndarray): Input array to compare.
72         b (cupy.ndarray): Input array to compare.
73         rtol (float): The relative tolerance.
74         atol (float): The absolute tolerance.
75         equal_nan (bool): If ``True``, NaN's in ``a`` will be considered equal
76             to NaN's in ``b``.
77 
78     Returns:
79         cupy.ndarray: A boolean 0-dim array.
80             If its value is ``True``, two arrays are element-wise equal within
81             a tolerance.
82 
83     .. seealso:: :func:`numpy.allclose`
84 
85     """
86     return isclose(a, b, rtol=rtol, atol=atol, equal_nan=equal_nan).all()
87 
88 
89 def isclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):
90     """Returns a boolean array where two arrays are equal within a tolerance.
91 
92     Two values in ``a`` and ``b`` are  considiered equal when the following
93     equation is satisfied.
94 
95     .. math::
96 
97        |a - b| \\le \\mathrm{atol} + \\mathrm{rtol} |b|
98 
99     Args:
100         a (cupy.ndarray): Input array to compare.
101         b (cupy.ndarray): Input array to compare.
102         rtol (float): The relative tolerance.
103         atol (float): The absolute tolerance.
104         equal_nan (bool): If ``True``, NaN's in ``a`` will be considered equal
105             to NaN's in ``b``.
106 
107     Returns:
108         cupy.ndarray: A boolean array storing where ``a`` and ``b`` are equal.
109 
110     .. seealso:: :func:`numpy.isclose`
111 
112     """
113     a = cupy.asanyarray(a)
114     b = cupy.asanyarray(b)
115     if (a.dtype in [numpy.complex64, numpy.complex128]) or \
116        (b.dtype in [numpy.complex64, numpy.complex128]):
117         return _is_close_complex(a, b, rtol, atol, equal_nan)
118     else:
119         return _is_close(a, b, rtol, atol, equal_nan)
120 
121 
122 # TODO(okuta): Implement array_equal
123 
124 
125 # TODO(okuta): Implement array_equiv
126 
127 
128 greater = core.greater
129 
130 
131 greater_equal = core.greater_equal
132 
133 
134 less = core.less
135 
136 
137 less_equal = core.less_equal
138 
139 
140 equal = core.equal
141 
142 
143 not_equal = core.not_equal
144
```
--- 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/cupy/_logic/comparison.py b/cupy/_logic/comparison.py
--- a/cupy/_logic/comparison.py
+++ b/cupy/_logic/comparison.py
@@ -2,6 +2,7 @@
 
 import cupy
 from cupy import core
+from cupy._logic import content
 
 
 _is_close = core.create_ufunc(
@@ -38,12 +39,14 @@
 )
 
 
-def array_equal(a1, a2):
+def array_equal(a1, a2, equal_nan=False):
     """Returns ``True`` if two arrays are element-wise exactly equal.
 
     Args:
         a1 (cupy.ndarray): Input array to compare.
         a2 (cupy.ndarray): Input array to compare.
+        equal_nan (bool): If ``True``, NaN's in ``a1`` will be considered equal
+            to NaN's in ``a2``.
 
     Returns:
         cupy.ndarray: A boolean 0-dim array.
@@ -54,7 +57,15 @@
     """
     if a1.shape != a2.shape:
         return cupy.array(False)
-    return (a1 == a2).all()
+    if not equal_nan:
+        return (a1 == a2).all()
+    # Handling NaN values if equal_nan is True
+    a1nan, a2nan = content.isnan(a1), content.isnan(a2)
+    # NaN's occur at different locations
+    if not (a1nan == a2nan).all():
+        return cupy.array(False)
+    # Shapes of a1, a2 and masks are guaranteed to be consistent by this point
+    return (a1[~a1nan] == a2[~a1nan]).all()
 
 
 def allclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):

{"golden_diff": "diff --git a/cupy/_logic/comparison.py b/cupy/_logic/comparison.py\n--- a/cupy/_logic/comparison.py\n+++ b/cupy/_logic/comparison.py\n@@ -2,6 +2,7 @@\n \n import cupy\n from cupy import core\n+from cupy._logic import content\n \n \n _is_close = core.create_ufunc(\n@@ -38,12 +39,14 @@\n )\n \n \n-def array_equal(a1, a2):\n+def array_equal(a1, a2, equal_nan=False):\n     \"\"\"Returns ``True`` if two arrays are element-wise exactly equal.\n \n     Args:\n         a1 (cupy.ndarray): Input array to compare.\n         a2 (cupy.ndarray): Input array to compare.\n+        equal_nan (bool): If ``True``, NaN's in ``a1`` will be considered equal\n+            to NaN's in ``a2``.\n \n     Returns:\n         cupy.ndarray: A boolean 0-dim array.\n@@ -54,7 +57,15 @@\n     \"\"\"\n     if a1.shape != a2.shape:\n         return cupy.array(False)\n-    return (a1 == a2).all()\n+    if not equal_nan:\n+        return (a1 == a2).all()\n+    # Handling NaN values if equal_nan is True\n+    a1nan, a2nan = content.isnan(a1), content.isnan(a2)\n+    # NaN's occur at different locations\n+    if not (a1nan == a2nan).all():\n+        return cupy.array(False)\n+    # Shapes of a1, a2 and masks are guaranteed to be consistent by this point\n+    return (a1[~a1nan] == a2[~a1nan]).all()\n \n \n def allclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):\n", "issue": "[Bug, Enhancement] array_equal returns False on identical arrays with NaN values\n* Conditions (you can just paste the output of `python -c 'import cupy; cupy.show_config()'`)\r\n  - CuPy Version          : 8.0.0\r\n  - OS/Platform : Pop OS\r\n  - CUDA Version    : 10000\r\n  - cuDNN Version         : 7605\r\n  - NCCL Version    : 2604\r\n\r\n* Code to reproduce\r\n```python\r\nimport cupy as cp\r\na = cp.array([0, 1, cp.nan])\r\nprint(cp.array_equal(a, a))         # False\r\n```\r\nThis relates exactly with https://github.com/numpy/numpy/issues/9229\r\nThis could be resolved by following the same procedure, resolved by https://github.com/numpy/numpy/pull/16128, which would essentially add an `equal_nan` kwarg to let user decide if NaN values should be considered equal or not, which is consistent with: https://github.com/cupy/cupy/blob/0dc6bbafb0cf75bb873531cbf69c6995a72c61a3/cupy/_logic/comparison.py#L60\r\nhttps://github.com/cupy/cupy/blob/0dc6bbafb0cf75bb873531cbf69c6995a72c61a3/cupy/_logic/comparison.py#L89\r\n\r\n* Error messages, stack traces, or logs\r\n`<null>`\n", "before_files": [{"content": "import numpy\n\nimport cupy\nfrom cupy import core\n\n\n_is_close = core.create_ufunc(\n    'cupy_is_close',\n    ('eeee?->?', 'ffff?->?', 'dddd?->?'),\n    '''\n    bool equal_nan = in4;\n    if (isfinite(in0) && isfinite(in1)) {\n      out0 = fabs(in0 - in1) <= in3 + in2 * fabs(in1);\n    } else if (equal_nan) {\n      out0 = (in0 == in1) || (isnan(in0) && isnan(in1));\n    } else {\n      out0 = (in0 == in1);\n    }\n    '''\n)\n\n# Note that in cupy/core/include/cupy/complex.cuh, we already got isfinite and\n# isnan working for complex numbers, so just replace fabs above by abs (from\n# thrust) and we are ready to go\n_is_close_complex = core.create_ufunc(\n    'cupy_is_close_complex',\n    ('FFff?->?', 'DDdd?->?'),\n    '''\n    bool equal_nan = in4;\n    if (isfinite(in0) && isfinite(in1)) {\n      out0 = abs(in0 - in1) <= in3 + in2 * abs(in1);\n    } else if (equal_nan) {\n      out0 = (in0 == in1) || (isnan(in0) && isnan(in1));\n    } else {\n      out0 = (in0 == in1);\n    }\n    '''\n)\n\n\ndef array_equal(a1, a2):\n    \"\"\"Returns ``True`` if two arrays are element-wise exactly equal.\n\n    Args:\n        a1 (cupy.ndarray): Input array to compare.\n        a2 (cupy.ndarray): Input array to compare.\n\n    Returns:\n        cupy.ndarray: A boolean 0-dim array.\n            If its value is ``True``, two arrays are element-wise equal.\n\n    .. seealso:: :func:`numpy.array_equal`\n\n    \"\"\"\n    if a1.shape != a2.shape:\n        return cupy.array(False)\n    return (a1 == a2).all()\n\n\ndef allclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):\n    \"\"\"Returns True if two arrays are element-wise equal within a tolerance.\n\n    Two values in ``a`` and ``b`` are  considiered equal when the following\n    equation is satisfied.\n\n    .. math::\n\n       |a - b| \\\\le \\\\mathrm{atol} + \\\\mathrm{rtol} |b|\n\n    Args:\n        a (cupy.ndarray): Input array to compare.\n        b (cupy.ndarray): Input array to compare.\n        rtol (float): The relative tolerance.\n        atol (float): The absolute tolerance.\n        equal_nan (bool): If ``True``, NaN's in ``a`` will be considered equal\n            to NaN's in ``b``.\n\n    Returns:\n        cupy.ndarray: A boolean 0-dim array.\n            If its value is ``True``, two arrays are element-wise equal within\n            a tolerance.\n\n    .. seealso:: :func:`numpy.allclose`\n\n    \"\"\"\n    return isclose(a, b, rtol=rtol, atol=atol, equal_nan=equal_nan).all()\n\n\ndef isclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):\n    \"\"\"Returns a boolean array where two arrays are equal within a tolerance.\n\n    Two values in ``a`` and ``b`` are  considiered equal when the following\n    equation is satisfied.\n\n    .. math::\n\n       |a - b| \\\\le \\\\mathrm{atol} + \\\\mathrm{rtol} |b|\n\n    Args:\n        a (cupy.ndarray): Input array to compare.\n        b (cupy.ndarray): Input array to compare.\n        rtol (float): The relative tolerance.\n        atol (float): The absolute tolerance.\n        equal_nan (bool): If ``True``, NaN's in ``a`` will be considered equal\n            to NaN's in ``b``.\n\n    Returns:\n        cupy.ndarray: A boolean array storing where ``a`` and ``b`` are equal.\n\n    .. seealso:: :func:`numpy.isclose`\n\n    \"\"\"\n    a = cupy.asanyarray(a)\n    b = cupy.asanyarray(b)\n    if (a.dtype in [numpy.complex64, numpy.complex128]) or \\\n       (b.dtype in [numpy.complex64, numpy.complex128]):\n        return _is_close_complex(a, b, rtol, atol, equal_nan)\n    else:\n        return _is_close(a, b, rtol, atol, equal_nan)\n\n\n# TODO(okuta): Implement array_equal\n\n\n# TODO(okuta): Implement array_equiv\n\n\ngreater = core.greater\n\n\ngreater_equal = core.greater_equal\n\n\nless = core.less\n\n\nless_equal = core.less_equal\n\n\nequal = core.equal\n\n\nnot_equal = core.not_equal\n", "path": "cupy/_logic/comparison.py"}], "after_files": [{"content": "import numpy\n\nimport cupy\nfrom cupy import core\nfrom cupy._logic import content\n\n\n_is_close = core.create_ufunc(\n    'cupy_is_close',\n    ('eeee?->?', 'ffff?->?', 'dddd?->?'),\n    '''\n    bool equal_nan = in4;\n    if (isfinite(in0) && isfinite(in1)) {\n      out0 = fabs(in0 - in1) <= in3 + in2 * fabs(in1);\n    } else if (equal_nan) {\n      out0 = (in0 == in1) || (isnan(in0) && isnan(in1));\n    } else {\n      out0 = (in0 == in1);\n    }\n    '''\n)\n\n# Note that in cupy/core/include/cupy/complex.cuh, we already got isfinite and\n# isnan working for complex numbers, so just replace fabs above by abs (from\n# thrust) and we are ready to go\n_is_close_complex = core.create_ufunc(\n    'cupy_is_close_complex',\n    ('FFff?->?', 'DDdd?->?'),\n    '''\n    bool equal_nan = in4;\n    if (isfinite(in0) && isfinite(in1)) {\n      out0 = abs(in0 - in1) <= in3 + in2 * abs(in1);\n    } else if (equal_nan) {\n      out0 = (in0 == in1) || (isnan(in0) && isnan(in1));\n    } else {\n      out0 = (in0 == in1);\n    }\n    '''\n)\n\n\ndef array_equal(a1, a2, equal_nan=False):\n    \"\"\"Returns ``True`` if two arrays are element-wise exactly equal.\n\n    Args:\n        a1 (cupy.ndarray): Input array to compare.\n        a2 (cupy.ndarray): Input array to compare.\n        equal_nan (bool): If ``True``, NaN's in ``a1`` will be considered equal\n            to NaN's in ``a2``.\n\n    Returns:\n        cupy.ndarray: A boolean 0-dim array.\n            If its value is ``True``, two arrays are element-wise equal.\n\n    .. seealso:: :func:`numpy.array_equal`\n\n    \"\"\"\n    if a1.shape != a2.shape:\n        return cupy.array(False)\n    if not equal_nan:\n        return (a1 == a2).all()\n    # Handling NaN values if equal_nan is True\n    a1nan, a2nan = content.isnan(a1), content.isnan(a2)\n    # NaN's occur at different locations\n    if not (a1nan == a2nan).all():\n        return cupy.array(False)\n    # Shapes of a1, a2 and masks are guaranteed to be consistent by this point\n    return (a1[~a1nan] == a2[~a1nan]).all()\n\n\ndef allclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):\n    \"\"\"Returns True if two arrays are element-wise equal within a tolerance.\n\n    Two values in ``a`` and ``b`` are  considiered equal when the following\n    equation is satisfied.\n\n    .. math::\n\n       |a - b| \\\\le \\\\mathrm{atol} + \\\\mathrm{rtol} |b|\n\n    Args:\n        a (cupy.ndarray): Input array to compare.\n        b (cupy.ndarray): Input array to compare.\n        rtol (float): The relative tolerance.\n        atol (float): The absolute tolerance.\n        equal_nan (bool): If ``True``, NaN's in ``a`` will be considered equal\n            to NaN's in ``b``.\n\n    Returns:\n        cupy.ndarray: A boolean 0-dim array.\n            If its value is ``True``, two arrays are element-wise equal within\n            a tolerance.\n\n    .. seealso:: :func:`numpy.allclose`\n\n    \"\"\"\n    return isclose(a, b, rtol=rtol, atol=atol, equal_nan=equal_nan).all()\n\n\ndef isclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):\n    \"\"\"Returns a boolean array where two arrays are equal within a tolerance.\n\n    Two values in ``a`` and ``b`` are  considiered equal when the following\n    equation is satisfied.\n\n    .. math::\n\n       |a - b| \\\\le \\\\mathrm{atol} + \\\\mathrm{rtol} |b|\n\n    Args:\n        a (cupy.ndarray): Input array to compare.\n        b (cupy.ndarray): Input array to compare.\n        rtol (float): The relative tolerance.\n        atol (float): The absolute tolerance.\n        equal_nan (bool): If ``True``, NaN's in ``a`` will be considered equal\n            to NaN's in ``b``.\n\n    Returns:\n        cupy.ndarray: A boolean array storing where ``a`` and ``b`` are equal.\n\n    .. seealso:: :func:`numpy.isclose`\n\n    \"\"\"\n    a = cupy.asanyarray(a)\n    b = cupy.asanyarray(b)\n    if (a.dtype in [numpy.complex64, numpy.complex128]) or \\\n       (b.dtype in [numpy.complex64, numpy.complex128]):\n        return _is_close_complex(a, b, rtol, atol, equal_nan)\n    else:\n        return _is_close(a, b, rtol, atol, equal_nan)\n\n\n# TODO(okuta): Implement array_equal\n\n\n# TODO(okuta): Implement array_equiv\n\n\ngreater = core.greater\n\n\ngreater_equal = core.greater_equal\n\n\nless = core.less\n\n\nless_equal = core.less_equal\n\n\nequal = core.equal\n\n\nnot_equal = core.not_equal\n", "path": "cupy/_logic/comparison.py"}]}