prompt: 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()
  
  ```
  
golden_diff: 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)
  
verification_info: {"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"}]}