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


--- 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/paddle/tensor/tensor.py`
Content:
```
1 # local
2 import ivy
3 import ivy.functional.frontends.paddle as paddle_frontend
4 from ivy.functional.frontends.paddle.func_wrapper import (
5     _to_ivy_array,
6 )
7 from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
8 
9 
10 class Tensor:
11     def __init__(self, array, dtype=None, place="cpu", stop_gradient=True):
12         self._ivy_array = (
13             ivy.array(array, dtype=dtype, device=place)
14             if not isinstance(array, ivy.Array)
15             else array
16         )
17         self._dtype = dtype
18         self._place = place
19         self._stop_gradient = stop_gradient
20 
21     def __repr__(self):
22         return (
23             str(self._ivy_array.__repr__())
24             .replace("ivy.array", "ivy.frontends.paddle.Tensor")
25             .replace("dev", "place")
26         )
27 
28     # Properties #
29     # ---------- #
30 
31     @property
32     def ivy_array(self):
33         return self._ivy_array
34 
35     @property
36     def place(self):
37         return self.ivy_array.device
38 
39     @property
40     def dtype(self):
41         return self._ivy_array.dtype
42 
43     @property
44     def shape(self):
45         return self._ivy_array.shape
46 
47     @property
48     def ndim(self):
49         return self.dim()
50 
51     # Setters #
52     # --------#
53 
54     @ivy_array.setter
55     def ivy_array(self, array):
56         self._ivy_array = (
57             ivy.array(array) if not isinstance(array, ivy.Array) else array
58         )
59 
60     # Special Methods #
61     # -------------------#
62 
63     def __getitem__(self, item):
64         ivy_args = ivy.nested_map([self, item], _to_ivy_array)
65         ret = ivy.get_item(*ivy_args)
66         return paddle_frontend.Tensor(ret)
67 
68     def __setitem__(self, item, value):
69         item, value = ivy.nested_map([item, value], _to_ivy_array)
70         self.ivy_array[item] = value
71 
72     def __iter__(self):
73         if self.ndim == 0:
74             raise TypeError("iteration over a 0-d tensor not supported")
75         for i in range(self.shape[0]):
76             yield self[i]
77 
78     # Instance Methods #
79     # ---------------- #
80 
81     def reshape(self, *args, shape=None):
82         if args and shape:
83             raise TypeError("reshape() got multiple values for argument 'shape'")
84         if shape is not None:
85             return paddle_frontend.reshape(self._ivy_array, shape)
86         if args:
87             if isinstance(args[0], (tuple, list)):
88                 shape = args[0]
89                 return paddle_frontend.reshape(self._ivy_array, shape)
90             else:
91                 return paddle_frontend.reshape(self._ivy_array, args)
92         return paddle_frontend.reshape(self._ivy_array)
93 
94     def dim(self):
95         return self.ivy_array.ndim
96 
97     @with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
98     def abs(self):
99         return paddle_frontend.abs(self)
100 
101     @with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
102     def ceil(self):
103         return paddle_frontend.ceil(self)
104 
105     @with_unsupported_dtypes({"2.4.2 and below": ("float16",)}, "paddle")
106     def asinh(self, name=None):
107         return ivy.asinh(self._ivy_array)
108 
109     @with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
110     def asin(self, name=None):
111         return ivy.asin(self._ivy_array)
112 
113     @with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
114     def log(self, name=None):
115         return ivy.log(self._ivy_array)
116 
117     @with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
118     def sin(self, name=None):
119         return ivy.sin(self._ivy_array)
120 
121     @with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
122     def sinh(self, name=None):
123         return ivy.sinh(self._ivy_array)
124 
125     @with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
126     def argmax(self, axis=None, keepdim=False, dtype=None, name=None):
127         return ivy.argmax(self._ivy_array, axis=axis, keepdims=keepdim, dtype=dtype)
128 
129     @with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
130     def cos(self, name=None):
131         return ivy.cos(self._ivy_array)
132 
133     @with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
134     def exp(self, name=None):
135         return ivy.exp(self._ivy_array)
136 
137     @with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
138     def log10(self, name=None):
139         return ivy.log10(self._ivy_array)
140 
141     @with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
142     def argsort(self, axis=-1, descending=False, name=None):
143         return ivy.argsort(self._ivy_array, axis=axis, descending=descending)
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/ivy/functional/frontends/paddle/tensor/tensor.py b/ivy/functional/frontends/paddle/tensor/tensor.py
--- a/ivy/functional/frontends/paddle/tensor/tensor.py
+++ b/ivy/functional/frontends/paddle/tensor/tensor.py
@@ -110,6 +110,10 @@
     def asin(self, name=None):
         return ivy.asin(self._ivy_array)
 
+    @with_unsupported_dtypes({"2.4.2 and below": ("float16", "bfloat16")}, "paddle")
+    def cosh(self, name=None):
+        return ivy.cosh(self._ivy_array)
+
     @with_supported_dtypes({"2.4.2 and below": ("float32", "float64")}, "paddle")
     def log(self, name=None):
         return ivy.log(self._ivy_array)

{"golden_diff": "diff --git a/ivy/functional/frontends/paddle/tensor/tensor.py b/ivy/functional/frontends/paddle/tensor/tensor.py\n--- a/ivy/functional/frontends/paddle/tensor/tensor.py\n+++ b/ivy/functional/frontends/paddle/tensor/tensor.py\n@@ -110,6 +110,10 @@\n     def asin(self, name=None):\r\n         return ivy.asin(self._ivy_array)\r\n \r\n+    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n+    def cosh(self, name=None):\r\n+        return ivy.cosh(self._ivy_array)\r\n+\r\n     @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n     def log(self, name=None):\r\n         return ivy.log(self._ivy_array)\n", "issue": "cosh\n\n", "before_files": [{"content": "# local\r\nimport ivy\r\nimport ivy.functional.frontends.paddle as paddle_frontend\r\nfrom ivy.functional.frontends.paddle.func_wrapper import (\r\n    _to_ivy_array,\r\n)\r\nfrom ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes\r\n\r\n\r\nclass Tensor:\r\n    def __init__(self, array, dtype=None, place=\"cpu\", stop_gradient=True):\r\n        self._ivy_array = (\r\n            ivy.array(array, dtype=dtype, device=place)\r\n            if not isinstance(array, ivy.Array)\r\n            else array\r\n        )\r\n        self._dtype = dtype\r\n        self._place = place\r\n        self._stop_gradient = stop_gradient\r\n\r\n    def __repr__(self):\r\n        return (\r\n            str(self._ivy_array.__repr__())\r\n            .replace(\"ivy.array\", \"ivy.frontends.paddle.Tensor\")\r\n            .replace(\"dev\", \"place\")\r\n        )\r\n\r\n    # Properties #\r\n    # ---------- #\r\n\r\n    @property\r\n    def ivy_array(self):\r\n        return self._ivy_array\r\n\r\n    @property\r\n    def place(self):\r\n        return self.ivy_array.device\r\n\r\n    @property\r\n    def dtype(self):\r\n        return self._ivy_array.dtype\r\n\r\n    @property\r\n    def shape(self):\r\n        return self._ivy_array.shape\r\n\r\n    @property\r\n    def ndim(self):\r\n        return self.dim()\r\n\r\n    # Setters #\r\n    # --------#\r\n\r\n    @ivy_array.setter\r\n    def ivy_array(self, array):\r\n        self._ivy_array = (\r\n            ivy.array(array) if not isinstance(array, ivy.Array) else array\r\n        )\r\n\r\n    # Special Methods #\r\n    # -------------------#\r\n\r\n    def __getitem__(self, item):\r\n        ivy_args = ivy.nested_map([self, item], _to_ivy_array)\r\n        ret = ivy.get_item(*ivy_args)\r\n        return paddle_frontend.Tensor(ret)\r\n\r\n    def __setitem__(self, item, value):\r\n        item, value = ivy.nested_map([item, value], _to_ivy_array)\r\n        self.ivy_array[item] = value\r\n\r\n    def __iter__(self):\r\n        if self.ndim == 0:\r\n            raise TypeError(\"iteration over a 0-d tensor not supported\")\r\n        for i in range(self.shape[0]):\r\n            yield self[i]\r\n\r\n    # Instance Methods #\r\n    # ---------------- #\r\n\r\n    def reshape(self, *args, shape=None):\r\n        if args and shape:\r\n            raise TypeError(\"reshape() got multiple values for argument 'shape'\")\r\n        if shape is not None:\r\n            return paddle_frontend.reshape(self._ivy_array, shape)\r\n        if args:\r\n            if isinstance(args[0], (tuple, list)):\r\n                shape = args[0]\r\n                return paddle_frontend.reshape(self._ivy_array, shape)\r\n            else:\r\n                return paddle_frontend.reshape(self._ivy_array, args)\r\n        return paddle_frontend.reshape(self._ivy_array)\r\n\r\n    def dim(self):\r\n        return self.ivy_array.ndim\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def abs(self):\r\n        return paddle_frontend.abs(self)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def ceil(self):\r\n        return paddle_frontend.ceil(self)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\",)}, \"paddle\")\r\n    def asinh(self, name=None):\r\n        return ivy.asinh(self._ivy_array)\r\n\r\n    @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n    def asin(self, name=None):\r\n        return ivy.asin(self._ivy_array)\r\n\r\n    @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n    def log(self, name=None):\r\n        return ivy.log(self._ivy_array)\r\n\r\n    @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n    def sin(self, name=None):\r\n        return ivy.sin(self._ivy_array)\r\n\r\n    @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n    def sinh(self, name=None):\r\n        return ivy.sinh(self._ivy_array)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def argmax(self, axis=None, keepdim=False, dtype=None, name=None):\r\n        return ivy.argmax(self._ivy_array, axis=axis, keepdims=keepdim, dtype=dtype)\r\n\r\n    @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n    def cos(self, name=None):\r\n        return ivy.cos(self._ivy_array)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def exp(self, name=None):\r\n        return ivy.exp(self._ivy_array)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def log10(self, name=None):\r\n        return ivy.log10(self._ivy_array)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def argsort(self, axis=-1, descending=False, name=None):\r\n        return ivy.argsort(self._ivy_array, axis=axis, descending=descending)\r\n", "path": "ivy/functional/frontends/paddle/tensor/tensor.py"}], "after_files": [{"content": "# local\r\nimport ivy\r\nimport ivy.functional.frontends.paddle as paddle_frontend\r\nfrom ivy.functional.frontends.paddle.func_wrapper import (\r\n    _to_ivy_array,\r\n)\r\nfrom ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes\r\n\r\n\r\nclass Tensor:\r\n    def __init__(self, array, dtype=None, place=\"cpu\", stop_gradient=True):\r\n        self._ivy_array = (\r\n            ivy.array(array, dtype=dtype, device=place)\r\n            if not isinstance(array, ivy.Array)\r\n            else array\r\n        )\r\n        self._dtype = dtype\r\n        self._place = place\r\n        self._stop_gradient = stop_gradient\r\n\r\n    def __repr__(self):\r\n        return (\r\n            str(self._ivy_array.__repr__())\r\n            .replace(\"ivy.array\", \"ivy.frontends.paddle.Tensor\")\r\n            .replace(\"dev\", \"place\")\r\n        )\r\n\r\n    # Properties #\r\n    # ---------- #\r\n\r\n    @property\r\n    def ivy_array(self):\r\n        return self._ivy_array\r\n\r\n    @property\r\n    def place(self):\r\n        return self.ivy_array.device\r\n\r\n    @property\r\n    def dtype(self):\r\n        return self._ivy_array.dtype\r\n\r\n    @property\r\n    def shape(self):\r\n        return self._ivy_array.shape\r\n\r\n    @property\r\n    def ndim(self):\r\n        return self.dim()\r\n\r\n    # Setters #\r\n    # --------#\r\n\r\n    @ivy_array.setter\r\n    def ivy_array(self, array):\r\n        self._ivy_array = (\r\n            ivy.array(array) if not isinstance(array, ivy.Array) else array\r\n        )\r\n\r\n    # Special Methods #\r\n    # -------------------#\r\n\r\n    def __getitem__(self, item):\r\n        ivy_args = ivy.nested_map([self, item], _to_ivy_array)\r\n        ret = ivy.get_item(*ivy_args)\r\n        return paddle_frontend.Tensor(ret)\r\n\r\n    def __setitem__(self, item, value):\r\n        item, value = ivy.nested_map([item, value], _to_ivy_array)\r\n        self.ivy_array[item] = value\r\n\r\n    def __iter__(self):\r\n        if self.ndim == 0:\r\n            raise TypeError(\"iteration over a 0-d tensor not supported\")\r\n        for i in range(self.shape[0]):\r\n            yield self[i]\r\n\r\n    # Instance Methods #\r\n    # ---------------- #\r\n\r\n    def reshape(self, *args, shape=None):\r\n        if args and shape:\r\n            raise TypeError(\"reshape() got multiple values for argument 'shape'\")\r\n        if shape is not None:\r\n            return paddle_frontend.reshape(self._ivy_array, shape)\r\n        if args:\r\n            if isinstance(args[0], (tuple, list)):\r\n                shape = args[0]\r\n                return paddle_frontend.reshape(self._ivy_array, shape)\r\n            else:\r\n                return paddle_frontend.reshape(self._ivy_array, args)\r\n        return paddle_frontend.reshape(self._ivy_array)\r\n\r\n    def dim(self):\r\n        return self.ivy_array.ndim\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def abs(self):\r\n        return paddle_frontend.abs(self)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def ceil(self):\r\n        return paddle_frontend.ceil(self)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\",)}, \"paddle\")\r\n    def asinh(self, name=None):\r\n        return ivy.asinh(self._ivy_array)\r\n\r\n    @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n    def asin(self, name=None):\r\n        return ivy.asin(self._ivy_array)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def cosh(self, name=None):\r\n        return ivy.cosh(self._ivy_array)\r\n\r\n    @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n    def log(self, name=None):\r\n        return ivy.log(self._ivy_array)\r\n\r\n    @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n    def sin(self, name=None):\r\n        return ivy.sin(self._ivy_array)\r\n\r\n    @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n    def sinh(self, name=None):\r\n        return ivy.sinh(self._ivy_array)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def argmax(self, axis=None, keepdim=False, dtype=None, name=None):\r\n        return ivy.argmax(self._ivy_array, axis=axis, keepdims=keepdim, dtype=dtype)\r\n\r\n    @with_supported_dtypes({\"2.4.2 and below\": (\"float32\", \"float64\")}, \"paddle\")\r\n    def cos(self, name=None):\r\n        return ivy.cos(self._ivy_array)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def exp(self, name=None):\r\n        return ivy.exp(self._ivy_array)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def log10(self, name=None):\r\n        return ivy.log10(self._ivy_array)\r\n\r\n    @with_unsupported_dtypes({\"2.4.2 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\r\n    def argsort(self, axis=-1, descending=False, name=None):\r\n        return ivy.argsort(self._ivy_array, axis=axis, descending=descending)\r\n", "path": "ivy/functional/frontends/paddle/tensor/tensor.py"}]}