prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  kaiser_bessel_derived_window
  - [ ] #1559
  
  </issue>
  <code>
  [start of ivy/functional/frontends/tensorflow/signal.py]
  1 import ivy
  2 from ivy.functional.frontends.tensorflow.func_wrapper import (
  3     to_ivy_arrays_and_back,
  4     handle_tf_dtype,
  5 )
  6 from ivy.func_wrapper import with_supported_dtypes
  7 
  8 
  9 # dct
  10 @to_ivy_arrays_and_back
  11 def dct(input, type=2, n=None, axis=-1, norm=None, name=None):
  12     return ivy.dct(input, type=type, n=n, axis=axis, norm=norm)
  13 
  14 
  15 # idct
  16 @to_ivy_arrays_and_back
  17 def idct(input, type=2, n=None, axis=-1, norm=None, name=None):
  18     inverse_type = {1: 1, 2: 3, 3: 2, 4: 4}[type]
  19     return ivy.dct(input, type=inverse_type, n=n, axis=axis, norm=norm)
  20 
  21 
  22 @with_supported_dtypes(
  23     {"2.13.0 and below": ("float32", "float64", "float16", "bfloat16")},
  24     "tensorflow",
  25 )
  26 @handle_tf_dtype
  27 @to_ivy_arrays_and_back
  28 def kaiser_window(window_length, beta=12.0, dtype=ivy.float32, name=None):
  29     return ivy.kaiser_window(window_length, periodic=False, beta=beta, dtype=dtype)
  30 
  31 
  32 @with_supported_dtypes(
  33     {"2.13.0 and below": ("float16", "float32", "float64", "bfloat16")},
  34     "tensorflow",
  35 )
  36 @to_ivy_arrays_and_back
  37 def vorbis_window(window_length, dtype=ivy.float32, name=None):
  38     return ivy.vorbis_window(window_length, dtype=dtype, out=None)
  39
  [end of ivy/functional/frontends/tensorflow/signal.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/tensorflow/signal.py b/ivy/functional/frontends/tensorflow/signal.py
  --- a/ivy/functional/frontends/tensorflow/signal.py
  +++ b/ivy/functional/frontends/tensorflow/signal.py
  @@ -19,6 +19,15 @@
       return ivy.dct(input, type=inverse_type, n=n, axis=axis, norm=norm)
   
   
  +# kaiser_bessel_derived_window
  +@handle_tf_dtype
  +@to_ivy_arrays_and_back
  +def kaiser_bessel_derived_window(
  +    window_length, beta=12.0, dtype=ivy.float32, name=None
  +):
  +    return ivy.kaiser_bessel_derived_window(window_length, beta=beta, dtype=dtype)
  +
  +
   @with_supported_dtypes(
       {"2.13.0 and below": ("float32", "float64", "float16", "bfloat16")},
       "tensorflow",
  @@ -36,3 +45,11 @@
   @to_ivy_arrays_and_back
   def vorbis_window(window_length, dtype=ivy.float32, name=None):
       return ivy.vorbis_window(window_length, dtype=dtype, out=None)
  +
  +
  +kaiser_bessel_derived_window.supported_dtypes = (
  +    "float32",
  +    "float64",
  +    "float16",
  +    "bfloat16",
  +)
  
verification_info: {"golden_diff": "diff --git a/ivy/functional/frontends/tensorflow/signal.py b/ivy/functional/frontends/tensorflow/signal.py\n--- a/ivy/functional/frontends/tensorflow/signal.py\n+++ b/ivy/functional/frontends/tensorflow/signal.py\n@@ -19,6 +19,15 @@\n     return ivy.dct(input, type=inverse_type, n=n, axis=axis, norm=norm)\n \n \n+# kaiser_bessel_derived_window\n+@handle_tf_dtype\n+@to_ivy_arrays_and_back\n+def kaiser_bessel_derived_window(\n+    window_length, beta=12.0, dtype=ivy.float32, name=None\n+):\n+    return ivy.kaiser_bessel_derived_window(window_length, beta=beta, dtype=dtype)\n+\n+\n @with_supported_dtypes(\n     {\"2.13.0 and below\": (\"float32\", \"float64\", \"float16\", \"bfloat16\")},\n     \"tensorflow\",\n@@ -36,3 +45,11 @@\n @to_ivy_arrays_and_back\n def vorbis_window(window_length, dtype=ivy.float32, name=None):\n     return ivy.vorbis_window(window_length, dtype=dtype, out=None)\n+\n+\n+kaiser_bessel_derived_window.supported_dtypes = (\n+    \"float32\",\n+    \"float64\",\n+    \"float16\",\n+    \"bfloat16\",\n+)\n", "issue": "kaiser_bessel_derived_window\n- [ ] #1559\n", "before_files": [{"content": "import ivy\nfrom ivy.functional.frontends.tensorflow.func_wrapper import (\n    to_ivy_arrays_and_back,\n    handle_tf_dtype,\n)\nfrom ivy.func_wrapper import with_supported_dtypes\n\n\n# dct\n@to_ivy_arrays_and_back\ndef dct(input, type=2, n=None, axis=-1, norm=None, name=None):\n    return ivy.dct(input, type=type, n=n, axis=axis, norm=norm)\n\n\n# idct\n@to_ivy_arrays_and_back\ndef idct(input, type=2, n=None, axis=-1, norm=None, name=None):\n    inverse_type = {1: 1, 2: 3, 3: 2, 4: 4}[type]\n    return ivy.dct(input, type=inverse_type, n=n, axis=axis, norm=norm)\n\n\n@with_supported_dtypes(\n    {\"2.13.0 and below\": (\"float32\", \"float64\", \"float16\", \"bfloat16\")},\n    \"tensorflow\",\n)\n@handle_tf_dtype\n@to_ivy_arrays_and_back\ndef kaiser_window(window_length, beta=12.0, dtype=ivy.float32, name=None):\n    return ivy.kaiser_window(window_length, periodic=False, beta=beta, dtype=dtype)\n\n\n@with_supported_dtypes(\n    {\"2.13.0 and below\": (\"float16\", \"float32\", \"float64\", \"bfloat16\")},\n    \"tensorflow\",\n)\n@to_ivy_arrays_and_back\ndef vorbis_window(window_length, dtype=ivy.float32, name=None):\n    return ivy.vorbis_window(window_length, dtype=dtype, out=None)\n", "path": "ivy/functional/frontends/tensorflow/signal.py"}]}