prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  argsort
  
  
  </issue>
  <code>
  [start of ivy/functional/frontends/paddle/tensor/search.py]
  1 # global
  2 import ivy
  3 from ivy.func_wrapper import with_supported_dtypes
  4 from ivy.functional.frontends.paddle.func_wrapper import (
  5     to_ivy_arrays_and_back,
  6 )
  7 
  8 
  9 @with_supported_dtypes(
  10     {"2.4.2 and below": ("float32", "float64", "int16", "int32", "int64", "uint8")},
  11     "paddle",
  12 )
  13 @to_ivy_arrays_and_back
  14 def argmax(x, /, *, axis=None, keepdim=False, dtype="int64", name=None):
  15     return ivy.argmax(x, axis=axis, keepdims=keepdim, dtype=dtype)
  16 
  17 
  18 @with_supported_dtypes(
  19     {"2.4.2 and below": ("float32", "float64", "int16", "int32", "int64", "uint8")},
  20     "paddle",
  21 )
  22 @to_ivy_arrays_and_back
  23 def argmin(x, /, *, axis=None, keepdim=False, dtype="int64", name=None):
  24     return ivy.argmin(x, axis=axis, keepdims=keepdim, dtype=dtype)
  25
  [end of ivy/functional/frontends/paddle/tensor/search.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/search.py b/ivy/functional/frontends/paddle/tensor/search.py
  --- a/ivy/functional/frontends/paddle/tensor/search.py
  +++ b/ivy/functional/frontends/paddle/tensor/search.py
  @@ -22,3 +22,12 @@
   @to_ivy_arrays_and_back
   def argmin(x, /, *, axis=None, keepdim=False, dtype="int64", name=None):
       return ivy.argmin(x, axis=axis, keepdims=keepdim, dtype=dtype)
  +
  +
  +@with_supported_dtypes(
  +    {"2.4.2 and below": ("float32", "float64", "int16", "int32", "int64", "uint8")},
  +    "paddle",
  +)
  +@to_ivy_arrays_and_back
  +def argsort(x, /, *, axis=-1, descending=False, name=None):
  +    return ivy.argsort(x, axis=axis, descending=descending)
  
verification_info: {"golden_diff": "diff --git a/ivy/functional/frontends/paddle/tensor/search.py b/ivy/functional/frontends/paddle/tensor/search.py\n--- a/ivy/functional/frontends/paddle/tensor/search.py\n+++ b/ivy/functional/frontends/paddle/tensor/search.py\n@@ -22,3 +22,12 @@\n @to_ivy_arrays_and_back\n def argmin(x, /, *, axis=None, keepdim=False, dtype=\"int64\", name=None):\n     return ivy.argmin(x, axis=axis, keepdims=keepdim, dtype=dtype)\n+\n+\n+@with_supported_dtypes(\n+    {\"2.4.2 and below\": (\"float32\", \"float64\", \"int16\", \"int32\", \"int64\", \"uint8\")},\n+    \"paddle\",\n+)\n+@to_ivy_arrays_and_back\n+def argsort(x, /, *, axis=-1, descending=False, name=None):\n+    return ivy.argsort(x, axis=axis, descending=descending)\n", "issue": "argsort\n\n", "before_files": [{"content": "# global\nimport ivy\nfrom ivy.func_wrapper import with_supported_dtypes\nfrom ivy.functional.frontends.paddle.func_wrapper import (\n    to_ivy_arrays_and_back,\n)\n\n\n@with_supported_dtypes(\n    {\"2.4.2 and below\": (\"float32\", \"float64\", \"int16\", \"int32\", \"int64\", \"uint8\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef argmax(x, /, *, axis=None, keepdim=False, dtype=\"int64\", name=None):\n    return ivy.argmax(x, axis=axis, keepdims=keepdim, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.4.2 and below\": (\"float32\", \"float64\", \"int16\", \"int32\", \"int64\", \"uint8\")},\n    \"paddle\",\n)\n@to_ivy_arrays_and_back\ndef argmin(x, /, *, axis=None, keepdim=False, dtype=\"int64\", name=None):\n    return ivy.argmin(x, axis=axis, keepdims=keepdim, dtype=dtype)\n", "path": "ivy/functional/frontends/paddle/tensor/search.py"}]}