prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  reshape_
  
  
  --- 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/manipulation.py`
  Content:
  ```
  1 # global
  2 import ivy
  3 from ivy.functional.frontends.paddle.func_wrapper import (
  4     to_ivy_arrays_and_back,
  5 )
  6 from ivy.func_wrapper import (
  7     with_unsupported_dtypes,
  8     with_supported_dtypes,
  9     with_supported_device_and_dtypes,
  10 )
  11 
  12 
  13 @to_ivy_arrays_and_back
  14 def reshape(x, shape):
  15     return ivy.reshape(x, shape)
  16 
  17 
  18 @with_unsupported_dtypes({"2.5.1 and below": ("float16", "bfloat16")}, "paddle")
  19 @to_ivy_arrays_and_back
  20 def abs(x, name=None):
  21     return ivy.abs(x)
  22 
  23 
  24 absolute = abs
  25 
  26 
  27 @to_ivy_arrays_and_back
  28 def stack(x, axis=0, name=None):
  29     return ivy.stack(x, axis=axis)
  30 
  31 
  32 @with_unsupported_dtypes({"2.5.1 and below": ("int8", "int16")}, "paddle")
  33 @to_ivy_arrays_and_back
  34 def concat(x, axis, name=None):
  35     return ivy.concat(x, axis=axis)
  36 
  37 
  38 @with_unsupported_dtypes(
  39     {"2.5.1 and below": ("int8", "uint8", "int16", "float16")},
  40     "paddle",
  41 )
  42 @to_ivy_arrays_and_back
  43 def tile(x, repeat_times, name=None):
  44     return ivy.tile(x, repeats=repeat_times)
  45 
  46 
  47 @with_unsupported_dtypes(
  48     {"2.5.1 and below": ("int8", "uint8", "int16", "float16")},
  49     "paddle",
  50 )
  51 @to_ivy_arrays_and_back
  52 def flip(x, axis, name=None):
  53     return ivy.flip(x, axis=axis)
  54 
  55 
  56 @with_unsupported_dtypes(
  57     {"2.5.1 and below": ("int16", "complex64", "complex128")},
  58     "paddle",
  59 )
  60 @to_ivy_arrays_and_back
  61 def split(x, num_or_sections, axis=0, name=None):
  62     return ivy.split(x, num_or_size_splits=num_or_sections, axis=axis)
  63 
  64 
  65 @with_unsupported_dtypes(
  66     {"2.5.1 and below": ("float16", "bfloat16", "int8", "int16")},
  67     "paddle",
  68 )
  69 @to_ivy_arrays_and_back
  70 def squeeze(x, axis=None, name=None):
  71     return ivy.squeeze(x, axis=axis)
  72 
  73 
  74 @with_supported_dtypes(
  75     {"2.5.1 and below": ("bool", "float32", "float64", "int32", "int64")},
  76     "paddle",
  77 )
  78 @to_ivy_arrays_and_back
  79 def expand(x, shape, name=None):
  80     return ivy.expand(x, shape)
  81 
  82 
  83 @with_supported_dtypes(
  84     {
  85         "2.5.1 and below": (
  86             "bool",
  87             "float16",
  88             "float32",
  89             "float64",
  90             "int32",
  91             "int64",
  92             "uint8",
  93         )
  94     },
  95     "paddle",
  96 )
  97 @to_ivy_arrays_and_back
  98 def cast(x, dtype):
  99     return ivy.astype(x, dtype)
  100 
  101 
  102 @with_supported_dtypes(
  103     {"2.5.1 and below": ("bool", "float32", "float64", "int32", "int64")},
  104     "paddle",
  105 )
  106 @to_ivy_arrays_and_back
  107 def broadcast_to(x, shape, name=None):
  108     return ivy.broadcast_to(x, shape)
  109 
  110 
  111 @with_supported_dtypes(
  112     {"2.5.1 and below": ("bool", "float32", "float64", "int32", "int64")},
  113     "paddle",
  114 )
  115 @to_ivy_arrays_and_back
  116 def gather(params, indices, axis=-1, batch_dims=0, name=None):
  117     return ivy.gather(params, indices, axis=axis, batch_dims=batch_dims)
  118 
  119 
  120 @with_supported_dtypes(
  121     {
  122         "2.5.0 and below": (
  123             "float32",
  124             "float64",
  125             "int32",
  126             "int64",
  127             "complex64",
  128             "complex128",
  129         )
  130     },
  131     "paddle",
  132 )
  133 @to_ivy_arrays_and_back
  134 def roll(x, shifts, axis=None, name=None):
  135     return ivy.roll(x, shifts, axis=axis)
  136 
  137 
  138 @with_supported_dtypes(
  139     {
  140         "2.5.1 and below": (
  141             "float32",
  142             "float64",
  143             "int32",
  144             "int64",
  145         )
  146     },
  147     "paddle",
  148 )
  149 @to_ivy_arrays_and_back
  150 def take_along_axis(arr, indices, axis):
  151     return ivy.take_along_axis(arr, indices, axis)
  152 
  153 
  154 @with_supported_device_and_dtypes(
  155     {
  156         "2.5.1 and above": {
  157             "cpu": (
  158                 "bool",
  159                 "int32",
  160                 "int64",
  161                 "float32",
  162                 "float64",
  163             ),
  164             "gpu": ("float16",),
  165         },
  166     },
  167     "paddle",
  168 )
  169 @to_ivy_arrays_and_back
  170 def rot90(x, k=1, axes=(0, 1), name=None):
  171     return ivy.rot90(x, k=k, axes=axes)
  172
  ```
  --- 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/manipulation.py b/ivy/functional/frontends/paddle/tensor/manipulation.py
  --- a/ivy/functional/frontends/paddle/tensor/manipulation.py
  +++ b/ivy/functional/frontends/paddle/tensor/manipulation.py
  @@ -15,6 +15,17 @@
       return ivy.reshape(x, shape)
   
   
  +@with_unsupported_dtypes(
  +    {"2.5.1 and below": ("int8", "uint8", "int16", "uint16", "float16", "bfloat16")},
  +    "paddle",
  +)
  +@to_ivy_arrays_and_back
  +def reshape_(x, shape):
  +    ret = ivy.reshape(x, shape)
  +    ivy.inplace_update(x, ret)
  +    return x
  +
  +
   @with_unsupported_dtypes({"2.5.1 and below": ("float16", "bfloat16")}, "paddle")
   @to_ivy_arrays_and_back
   def abs(x, name=None):
  
verification_info: {"golden_diff": "diff --git a/ivy/functional/frontends/paddle/tensor/manipulation.py b/ivy/functional/frontends/paddle/tensor/manipulation.py\n--- a/ivy/functional/frontends/paddle/tensor/manipulation.py\n+++ b/ivy/functional/frontends/paddle/tensor/manipulation.py\n@@ -15,6 +15,17 @@\n     return ivy.reshape(x, shape)\n \n \n+@with_unsupported_dtypes(\n+    {\"2.5.1 and below\": (\"int8\", \"uint8\", \"int16\", \"uint16\", \"float16\", \"bfloat16\")},\n+    \"paddle\",\n+)\n+@to_ivy_arrays_and_back\n+def reshape_(x, shape):\n+    ret = ivy.reshape(x, shape)\n+    ivy.inplace_update(x, ret)\n+    return x\n+\n+\n @with_unsupported_dtypes({\"2.5.1 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\n @to_ivy_arrays_and_back\n def abs(x, name=None):\n", "issue": "reshape_\n\n", "before_files": [{"content": "# global\nimport ivy\nfrom ivy.functional.frontends.paddle.func_wrapper import (\n    to_ivy_arrays_and_back,\n)\nfrom ivy.func_wrapper import (\n    with_unsupported_dtypes,\n    with_supported_dtypes,\n    with_supported_device_and_dtypes,\n)\n\n\n@to_ivy_arrays_and_back\ndef reshape(x, shape):\n    return ivy.reshape(x, shape)\n\n\n@with_unsupported_dtypes({\"2.5.1 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef abs(x, name=None):\n    return ivy.abs(x)\n\n\nabsolute = abs\n\n\n@to_ivy_arrays_and_back\ndef stack(x, axis=0, name=None):\n    return ivy.stack(x, axis=axis)\n\n\n@with_unsupported_dtypes({\"2.5.1 and below\": (\"int8\", \"int16\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef concat(x, axis, name=None):\n    return ivy.concat(x, axis=axis)\n\n\n@with_unsupported_dtypes(\n    {\"2.5.1 and below\": (\"int8\", \"uint8\", \"int16\", \"float16\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef tile(x, repeat_times, name=None):\n    return ivy.tile(x, repeats=repeat_times)\n\n\n@with_unsupported_dtypes(\n    {\"2.5.1 and below\": (\"int8\", \"uint8\", \"int16\", \"float16\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef flip(x, axis, name=None):\n    return ivy.flip(x, axis=axis)\n\n\n@with_unsupported_dtypes(\n    {\"2.5.1 and below\": (\"int16\", \"complex64\", \"complex128\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef split(x, num_or_sections, axis=0, name=None):\n    return ivy.split(x, num_or_size_splits=num_or_sections, axis=axis)\n\n\n@with_unsupported_dtypes(\n    {\"2.5.1 and below\": (\"float16\", \"bfloat16\", \"int8\", \"int16\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef squeeze(x, axis=None, name=None):\n    return ivy.squeeze(x, axis=axis)\n\n\n@with_supported_dtypes(\n    {\"2.5.1 and below\": (\"bool\", \"float32\", \"float64\", \"int32\", \"int64\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef expand(x, shape, name=None):\n    return ivy.expand(x, shape)\n\n\n@with_supported_dtypes(\n    {\n        \"2.5.1 and below\": (\n            \"bool\",\n            \"float16\",\n            \"float32\",\n            \"float64\",\n            \"int32\",\n            \"int64\",\n            \"uint8\",\n        )\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef cast(x, dtype):\n    return ivy.astype(x, dtype)\n\n\n@with_supported_dtypes(\n    {\"2.5.1 and below\": (\"bool\", \"float32\", \"float64\", \"int32\", \"int64\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef broadcast_to(x, shape, name=None):\n    return ivy.broadcast_to(x, shape)\n\n\n@with_supported_dtypes(\n    {\"2.5.1 and below\": (\"bool\", \"float32\", \"float64\", \"int32\", \"int64\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef gather(params, indices, axis=-1, batch_dims=0, name=None):\n    return ivy.gather(params, indices, axis=axis, batch_dims=batch_dims)\n\n\n@with_supported_dtypes(\n    {\n        \"2.5.0 and below\": (\n            \"float32\",\n            \"float64\",\n            \"int32\",\n            \"int64\",\n            \"complex64\",\n            \"complex128\",\n        )\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef roll(x, shifts, axis=None, name=None):\n    return ivy.roll(x, shifts, axis=axis)\n\n\n@with_supported_dtypes(\n    {\n        \"2.5.1 and below\": (\n            \"float32\",\n            \"float64\",\n            \"int32\",\n            \"int64\",\n        )\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef take_along_axis(arr, indices, axis):\n    return ivy.take_along_axis(arr, indices, axis)\n\n\n@with_supported_device_and_dtypes(\n    {\n        \"2.5.1 and above\": {\n            \"cpu\": (\n                \"bool\",\n                \"int32\",\n                \"int64\",\n                \"float32\",\n                \"float64\",\n            ),\n            \"gpu\": (\"float16\",),\n        },\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef rot90(x, k=1, axes=(0, 1), name=None):\n    return ivy.rot90(x, k=k, axes=axes)\n", "path": "ivy/functional/frontends/paddle/tensor/manipulation.py"}], "after_files": [{"content": "# global\nimport ivy\nfrom ivy.functional.frontends.paddle.func_wrapper import (\n    to_ivy_arrays_and_back,\n)\nfrom ivy.func_wrapper import (\n    with_unsupported_dtypes,\n    with_supported_dtypes,\n    with_supported_device_and_dtypes,\n)\n\n\n@to_ivy_arrays_and_back\ndef reshape(x, shape):\n    return ivy.reshape(x, shape)\n\n\n@with_unsupported_dtypes(\n    {\"2.5.1 and below\": (\"int8\", \"uint8\", \"int16\", \"uint16\", \"float16\", \"bfloat16\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef reshape_(x, shape):\n    ret = ivy.reshape(x, shape)\n    ivy.inplace_update(x, ret)\n    return x\n\n\n@with_unsupported_dtypes({\"2.5.1 and below\": (\"float16\", \"bfloat16\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef abs(x, name=None):\n    return ivy.abs(x)\n\n\nabsolute = abs\n\n\n@to_ivy_arrays_and_back\ndef stack(x, axis=0, name=None):\n    return ivy.stack(x, axis=axis)\n\n\n@with_unsupported_dtypes({\"2.5.1 and below\": (\"int8\", \"int16\")}, \"paddle\")\n@to_ivy_arrays_and_back\ndef concat(x, axis, name=None):\n    return ivy.concat(x, axis=axis)\n\n\n@with_unsupported_dtypes(\n    {\"2.5.1 and below\": (\"int8\", \"uint8\", \"int16\", \"float16\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef tile(x, repeat_times, name=None):\n    return ivy.tile(x, repeats=repeat_times)\n\n\n@with_unsupported_dtypes(\n    {\"2.5.1 and below\": (\"int8\", \"uint8\", \"int16\", \"float16\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef flip(x, axis, name=None):\n    return ivy.flip(x, axis=axis)\n\n\n@with_unsupported_dtypes(\n    {\"2.5.1 and below\": (\"int16\", \"complex64\", \"complex128\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef split(x, num_or_sections, axis=0, name=None):\n    return ivy.split(x, num_or_size_splits=num_or_sections, axis=axis)\n\n\n@with_unsupported_dtypes(\n    {\"2.5.1 and below\": (\"float16\", \"bfloat16\", \"int8\", \"int16\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef squeeze(x, axis=None, name=None):\n    return ivy.squeeze(x, axis=axis)\n\n\n@with_supported_dtypes(\n    {\"2.5.1 and below\": (\"bool\", \"float32\", \"float64\", \"int32\", \"int64\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef expand(x, shape, name=None):\n    return ivy.expand(x, shape)\n\n\n@with_supported_dtypes(\n    {\n        \"2.5.1 and below\": (\n            \"bool\",\n            \"float16\",\n            \"float32\",\n            \"float64\",\n            \"int32\",\n            \"int64\",\n            \"uint8\",\n        )\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef cast(x, dtype):\n    return ivy.astype(x, dtype)\n\n\n@with_supported_dtypes(\n    {\"2.5.1 and below\": (\"bool\", \"float32\", \"float64\", \"int32\", \"int64\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef broadcast_to(x, shape, name=None):\n    return ivy.broadcast_to(x, shape)\n\n\n@with_supported_dtypes(\n    {\"2.5.1 and below\": (\"bool\", \"float32\", \"float64\", \"int32\", \"int64\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef gather(params, indices, axis=-1, batch_dims=0, name=None):\n    return ivy.gather(params, indices, axis=axis, batch_dims=batch_dims)\n\n\n@with_supported_dtypes(\n    {\n        \"2.5.0 and below\": (\n            \"float32\",\n            \"float64\",\n            \"int32\",\n            \"int64\",\n            \"complex64\",\n            \"complex128\",\n        )\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef roll(x, shifts, axis=None, name=None):\n    return ivy.roll(x, shifts, axis=axis)\n\n\n@with_supported_dtypes(\n    {\n        \"2.5.1 and below\": (\n            \"float32\",\n            \"float64\",\n            \"int32\",\n            \"int64\",\n        )\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef take_along_axis(arr, indices, axis):\n    return ivy.take_along_axis(arr, indices, axis)\n\n\n@with_supported_device_and_dtypes(\n    {\n        \"2.5.1 and above\": {\n            \"cpu\": (\n                \"bool\",\n                \"int32\",\n                \"int64\",\n                \"float32\",\n                \"float64\",\n            ),\n            \"gpu\": (\"float16\",),\n        },\n    },\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef rot90(x, k=1, axes=(0, 1), name=None):\n    return ivy.rot90(x, k=k, axes=axes)\n", "path": "ivy/functional/frontends/paddle/tensor/manipulation.py"}]}