prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  cast
  
  
  --- 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 with_unsupported_dtypes
  7 
  8 
  9 @to_ivy_arrays_and_back
  10 def reshape(x, shape):
  11     return ivy.reshape(x, shape)
  12 
  13 
  14 @with_unsupported_dtypes({"2.5.0 and below": ("float16", "bfloat16")}, "paddle")
  15 @to_ivy_arrays_and_back
  16 def abs(x, name=None):
  17     return ivy.abs(x)
  18 
  19 
  20 absolute = abs
  21 
  22 
  23 @to_ivy_arrays_and_back
  24 def stack(x, axis=0, name=None):
  25     return ivy.stack(x, axis=axis)
  26 
  27 
  28 @with_unsupported_dtypes({"2.5.0 and below": ("int8", "int16")}, "paddle")
  29 @to_ivy_arrays_and_back
  30 def concat(x, axis, name=None):
  31     return ivy.concat(x, axis=axis)
  32 
  33 
  34 @with_unsupported_dtypes(
  35     {"2.5.0 and below": ("int8", "uint8", "int16", "float16")},
  36     "paddle",
  37 )
  38 @to_ivy_arrays_and_back
  39 def tile(x, repeat_times, name=None):
  40     return ivy.tile(x, repeats=repeat_times)
  41 
  42 
  43 @with_unsupported_dtypes(
  44     {"2.5.0 and below": ("int16", "complex64", "complex128")},
  45     "paddle",
  46 )
  47 @to_ivy_arrays_and_back
  48 def split(x, num_or_sections, axis=0, name=None):
  49     return ivy.split(x, num_or_size_splits=num_or_sections, axis=axis)
  50 
  51 
  52 @with_unsupported_dtypes(
  53     {"2.5.0 and below": ("float16", "bfloat16", "int8", "int16")},
  54     "paddle",
  55 )
  56 @to_ivy_arrays_and_back
  57 def squeeze(x, axis=None, name=None):
  58     return ivy.squeeze(x, axis=axis)
  59
  ```
  --- 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
  @@ -3,7 +3,10 @@
   from ivy.functional.frontends.paddle.func_wrapper import (
       to_ivy_arrays_and_back,
   )
  -from ivy.func_wrapper import with_unsupported_dtypes
  +from ivy.func_wrapper import (
  +    with_unsupported_dtypes,
  +    with_supported_dtypes,
  +)
   
   
   @to_ivy_arrays_and_back
  @@ -56,3 +59,22 @@
   @to_ivy_arrays_and_back
   def squeeze(x, axis=None, name=None):
       return ivy.squeeze(x, axis=axis)
  +
  +
  +@with_supported_dtypes(
  +    {
  +        "2.5.0 and below": (
  +            "bool",
  +            "float16",
  +            "float32",
  +            "float64",
  +            "int32",
  +            "int64",
  +            "uint8",
  +        )
  +    },
  +    "paddle",
  +)
  +@to_ivy_arrays_and_back
  +def cast(x, dtype):
  +    return ivy.astype(x, dtype)
  
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@@ -3,7 +3,10 @@\n from ivy.functional.frontends.paddle.func_wrapper import (\n     to_ivy_arrays_and_back,\n )\n-from ivy.func_wrapper import with_unsupported_dtypes\n+from ivy.func_wrapper import (\n+    with_unsupported_dtypes,\n+    with_supported_dtypes,\n+)\n \n \n @to_ivy_arrays_and_back\n@@ -56,3 +59,22 @@\n @to_ivy_arrays_and_back\n def squeeze(x, axis=None, name=None):\n     return ivy.squeeze(x, axis=axis)\n+\n+\n+@with_supported_dtypes(\n+    {\n+        \"2.5.0 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\n+def cast(x, dtype):\n+    return ivy.astype(x, dtype)\n", "issue": "cast\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 with_unsupported_dtypes\n\n\n@to_ivy_arrays_and_back\ndef reshape(x, shape):\n    return ivy.reshape(x, shape)\n\n\n@with_unsupported_dtypes({\"2.5.0 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({\"2.5.0 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    {\"2.5.0 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    {\"2.5.0 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    {\"2.5.0 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", "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)\n\n\n@to_ivy_arrays_and_back\ndef reshape(x, shape):\n    return ivy.reshape(x, shape)\n\n\n@with_unsupported_dtypes({\"2.5.0 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({\"2.5.0 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    {\"2.5.0 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    {\"2.5.0 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    {\"2.5.0 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    {\n        \"2.5.0 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", "path": "ivy/functional/frontends/paddle/tensor/manipulation.py"}]}