prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  cosine_similarity
  #15051 
  
  </issue>
  <code>
  [start of ivy/functional/frontends/paddle/nn/functional/common.py]
  1 # local
  2
  [end of ivy/functional/frontends/paddle/nn/functional/common.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/nn/functional/common.py b/ivy/functional/frontends/paddle/nn/functional/common.py
  --- a/ivy/functional/frontends/paddle/nn/functional/common.py
  +++ b/ivy/functional/frontends/paddle/nn/functional/common.py
  @@ -1 +1,25 @@
   # local
  +import ivy
  +from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back
  +from ivy.func_wrapper import with_unsupported_dtypes
  +
  +
  +@with_unsupported_dtypes({"2.0.1 and below": ("float16", "bfloat16")}, "torch")
  +@to_ivy_arrays_and_back
  +def cosine_similarity(x1, x2, *, axis=1, eps=1e-08):
  +    if len(x1.shape) == len(x2.shape) and len(x2.shape) >= 2:
  +        numerator = ivy.sum(x1 * x2, axis=axis)
  +        x1_squared_norm = ivy.sum(ivy.square(x1), axis=axis)
  +        x2_squared_norm = ivy.sum(ivy.square(x2), axis=axis)
  +    else:
  +        numerator = ivy.sum(x1 * x2)
  +        x1_squared_norm = ivy.sum(ivy.square(x1))
  +        x2_squared_norm = ivy.sum(ivy.square(x2))
  +
  +    x1_norm = ivy.sqrt(x1_squared_norm)
  +    x2_norm = ivy.sqrt(x2_squared_norm)
  +    norm_mm = x1_norm * x2_norm
  +    denominator = ivy.maximum(norm_mm, eps)
  +
  +    cosine = numerator / denominator
  +    return cosine
  
verification_info: {"golden_diff": "diff --git a/ivy/functional/frontends/paddle/nn/functional/common.py b/ivy/functional/frontends/paddle/nn/functional/common.py\n--- a/ivy/functional/frontends/paddle/nn/functional/common.py\n+++ b/ivy/functional/frontends/paddle/nn/functional/common.py\n@@ -1 +1,25 @@\n # local\n+import ivy\n+from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back\n+from ivy.func_wrapper import with_unsupported_dtypes\n+\n+\n+@with_unsupported_dtypes({\"2.0.1 and below\": (\"float16\", \"bfloat16\")}, \"torch\")\n+@to_ivy_arrays_and_back\n+def cosine_similarity(x1, x2, *, axis=1, eps=1e-08):\n+    if len(x1.shape) == len(x2.shape) and len(x2.shape) >= 2:\n+        numerator = ivy.sum(x1 * x2, axis=axis)\n+        x1_squared_norm = ivy.sum(ivy.square(x1), axis=axis)\n+        x2_squared_norm = ivy.sum(ivy.square(x2), axis=axis)\n+    else:\n+        numerator = ivy.sum(x1 * x2)\n+        x1_squared_norm = ivy.sum(ivy.square(x1))\n+        x2_squared_norm = ivy.sum(ivy.square(x2))\n+\n+    x1_norm = ivy.sqrt(x1_squared_norm)\n+    x2_norm = ivy.sqrt(x2_squared_norm)\n+    norm_mm = x1_norm * x2_norm\n+    denominator = ivy.maximum(norm_mm, eps)\n+\n+    cosine = numerator / denominator\n+    return cosine\n", "issue": "cosine_similarity\n#15051 \n", "before_files": [{"content": "# local\n", "path": "ivy/functional/frontends/paddle/nn/functional/common.py"}]}