prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  cast
  
  
  </issue>
  <code>
  [start of ivy/functional/frontends/paddle/tensor/manipulation.py]
  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 of ivy/functional/frontends/paddle/tensor/manipulation.py]
  </code>
  
  I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
  <patch>
  diff --git a/file.py b/file.py
  --- a/file.py
  +++ b/file.py
  @@ -1,27 +1,35 @@
   def euclidean(a, b):
  -    while b:
  -        a, b = b, a % b
  -    return a
  +    if b == 0:
  +        return a
  +    return euclidean(b, a % b)
   
   
   def bresenham(x0, y0, x1, y1):
       points = []
       dx = abs(x1 - x0)
       dy = abs(y1 - y0)
  -    sx = 1 if x0 < x1 else -1
  -    sy = 1 if y0 < y1 else -1
  -    err = dx - dy
  +    x, y = x0, y0
  +    sx = -1 if x0 > x1 else 1
  +    sy = -1 if y0 > y1 else 1
   
  -    while True:
  -        points.append((x0, y0))
  -        if x0 == x1 and y0 == y1:
  -            break
  -        e2 = 2 * err
  -        if e2 > -dy:
  -            err -= dy
  -            x0 += sx
  -        if e2 < dx:
  -            err += dx
  -            y0 += sy
  +    if dx > dy:
  +        err = dx / 2.0
  +        while x != x1:
  +            points.append((x, y))
  +            err -= dy
  +            if err < 0:
  +                y += sy
  +                err += dx
  +            x += sx
  +    else:
  +        err = dy / 2.0
  +        while y != y1:
  +            points.append((x, y))
  +            err -= dx
  +            if err < 0:
  +                x += sx
  +                err += dy
  +            y += sy
  +
  +    points.append((x, y))
       return points
  
  </patch>
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"}]}