We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
cupy.broadcast_arrays returns tuple, while numpy returns list
CuPy: current master (e51b311)
```
>>> cupy.broadcast_arrays(cupy.ones((1,)), cupy.ones((2)))
(array([ 1.,  1.]), array([ 1.,  1.]))
>>> numpy.broadcast_arrays(numpy.ones((1,)), numpy.ones((2)))
[array([ 1.,  1.]), array([ 1.,  1.])]
```

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `cupy/manipulation/dims.py`
Content:
```
1 import six
2 
3 import cupy
4 from cupy import core
5 
6 
7 zip_longest = six.moves.zip_longest
8 six_zip = six.moves.zip
9 
10 
11 # Shape map for atleast_nd functions
12 # (minimum dimension, input dimension) -> (output shape)
13 _atleast_nd_shape_map = {
14     (1, 0): lambda shape: (1,),
15     (2, 0): lambda shape: (1, 1),
16     (2, 1): lambda shape: (1,) + shape,
17     (3, 0): lambda shape: (1, 1, 1),
18     (3, 1): lambda shape: (1,) + shape + (1,),
19     (3, 2): lambda shape: shape + (1,),
20 }
21 
22 
23 def _atleast_nd_helper(n, arys):
24     """Helper function for atleast_nd functions."""
25 
26     res = []
27     for a in arys:
28         if isinstance(a, cupy.ndarray):
29             if a.ndim < n:
30                 new_shape = _atleast_nd_shape_map[(n, a.ndim)](a.shape)
31                 a = a.reshape(*new_shape)
32         else:
33             raise TypeError('Unsupported type {}'.format(type(a)))
34         res.append(a)
35 
36     if len(res) == 1:
37         res, = res
38     return res
39 
40 
41 def atleast_1d(*arys):
42     """Converts arrays to arrays with dimensions >= 1.
43 
44     Args:
45         arys (tuple of arrays): Arrays to be converted. All arguments must be
46             :class:`cupy.ndarray` objects. Only zero-dimensional array is
47             affected.
48 
49     Returns:
50         If there are only one input, then it returns its converted version.
51         Otherwise, it returns a list of converted arrays.
52 
53     .. seealso:: :func:`numpy.atleast_1d`
54 
55     """
56     return _atleast_nd_helper(1, arys)
57 
58 
59 def atleast_2d(*arys):
60     """Converts arrays to arrays with dimensions >= 2.
61 
62     If an input array has dimensions less than two, then this function inserts
63     new axes at the head of dimensions to make it have two dimensions.
64 
65     Args:
66         arys (tuple of arrays): Arrays to be converted. All arguments must be
67             :class:`cupy.ndarray` objects.
68 
69     Returns:
70         If there are only one input, then it returns its converted version.
71         Otherwise, it returns a list of converted arrays.
72 
73     .. seealso:: :func:`numpy.atleast_2d`
74 
75     """
76     return _atleast_nd_helper(2, arys)
77 
78 
79 def atleast_3d(*arys):
80     """Converts arrays to arrays with dimensions >= 3.
81 
82     If an input array has dimensions less than three, then this function
83     inserts new axes to make it have three dimensions. The place of the new
84     axes are following:
85 
86     - If its shape is ``()``, then the shape of output is ``(1, 1, 1)``.
87     - If its shape is ``(N,)``, then the shape of output is ``(1, N, 1)``.
88     - If its shape is ``(M, N)``, then the shape of output is ``(M, N, 1)``.
89     - Otherwise, the output is the input array itself.
90 
91     Args:
92         arys (tuple of arrays): Arrays to be converted. All arguments must be
93             :class:`cupy.ndarray` objects.
94 
95     Returns:
96         If there are only one input, then it returns its converted version.
97         Otherwise, it returns a list of converted arrays.
98 
99     .. seealso:: :func:`numpy.atleast_3d`
100 
101     """
102     return _atleast_nd_helper(3, arys)
103 
104 
105 broadcast = core.broadcast
106 
107 
108 def broadcast_arrays(*args):
109     """Broadcasts given arrays.
110 
111     Args:
112         args (tuple of arrays): Arrays to broadcast for each other.
113 
114     Returns:
115         list: A list of broadcasted arrays.
116 
117     .. seealso:: :func:`numpy.broadcast_arrays`
118 
119     """
120     return broadcast(*args).values
121 
122 
123 def broadcast_to(array, shape):
124     """Broadcast an array to a given shape.
125 
126     Args:
127         array (cupy.ndarray): Array to broadcast.
128         shape (tuple of int): The shape of the desired array.
129 
130     Returns:
131         cupy.ndarray: Broadcasted view.
132 
133     .. seealso:: :func:`numpy.broadcast_to`
134 
135     """
136     return core.broadcast_to(array, shape)
137 
138 
139 def expand_dims(a, axis):
140     """Expands given arrays.
141 
142     Args:
143         a (cupy.ndarray): Array to be expanded.
144         axis (int): Position where new axis is to be inserted.
145 
146     Returns:
147         cupy.ndarray: The number of dimensions is one greater than that of
148             the input array.
149 
150     .. seealso:: :func:`numpy.expand_dims`
151 
152     """
153     # TODO(okuta): check type
154     shape = a.shape
155     if axis < 0:
156         axis = axis + len(shape) + 1
157     return a.reshape(shape[:axis] + (1,) + shape[axis:])
158 
159 
160 def squeeze(a, axis=None):
161     """Removes size-one axes from the shape of an array.
162 
163     Args:
164         a (cupy.ndarray): Array to be reshaped.
165         axis (int or tuple of ints): Axes to be removed. This function removes
166             all size-one axes by default. If one of the specified axes is not
167             of size one, an exception is raised.
168 
169     Returns:
170         cupy.ndarray: An array without (specified) size-one axes.
171 
172     .. seealso:: :func:`numpy.squeeze`
173 
174     """
175     # TODO(okuta): check type
176     return a.squeeze(axis)
177
```
--- 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()

```

diff --git a/cupy/manipulation/dims.py b/cupy/manipulation/dims.py
--- a/cupy/manipulation/dims.py
+++ b/cupy/manipulation/dims.py
@@ -117,7 +117,7 @@
     .. seealso:: :func:`numpy.broadcast_arrays`
 
     """
-    return broadcast(*args).values
+    return list(broadcast(*args).values)
 
 
 def broadcast_to(array, shape):

{"golden_diff": "diff --git a/cupy/manipulation/dims.py b/cupy/manipulation/dims.py\n--- a/cupy/manipulation/dims.py\n+++ b/cupy/manipulation/dims.py\n@@ -117,7 +117,7 @@\n     .. seealso:: :func:`numpy.broadcast_arrays`\n \n     \"\"\"\n-    return broadcast(*args).values\n+    return list(broadcast(*args).values)\n \n \n def broadcast_to(array, shape):\n", "issue": "cupy.broadcast_arrays returns tuple, while numpy returns list\nCuPy: current master (e51b311)\r\n```\r\n>>> cupy.broadcast_arrays(cupy.ones((1,)), cupy.ones((2)))\r\n(array([ 1.,  1.]), array([ 1.,  1.]))\r\n>>> numpy.broadcast_arrays(numpy.ones((1,)), numpy.ones((2)))\r\n[array([ 1.,  1.]), array([ 1.,  1.])]\r\n```\n", "before_files": [{"content": "import six\n\nimport cupy\nfrom cupy import core\n\n\nzip_longest = six.moves.zip_longest\nsix_zip = six.moves.zip\n\n\n# Shape map for atleast_nd functions\n# (minimum dimension, input dimension) -> (output shape)\n_atleast_nd_shape_map = {\n    (1, 0): lambda shape: (1,),\n    (2, 0): lambda shape: (1, 1),\n    (2, 1): lambda shape: (1,) + shape,\n    (3, 0): lambda shape: (1, 1, 1),\n    (3, 1): lambda shape: (1,) + shape + (1,),\n    (3, 2): lambda shape: shape + (1,),\n}\n\n\ndef _atleast_nd_helper(n, arys):\n    \"\"\"Helper function for atleast_nd functions.\"\"\"\n\n    res = []\n    for a in arys:\n        if isinstance(a, cupy.ndarray):\n            if a.ndim < n:\n                new_shape = _atleast_nd_shape_map[(n, a.ndim)](a.shape)\n                a = a.reshape(*new_shape)\n        else:\n            raise TypeError('Unsupported type {}'.format(type(a)))\n        res.append(a)\n\n    if len(res) == 1:\n        res, = res\n    return res\n\n\ndef atleast_1d(*arys):\n    \"\"\"Converts arrays to arrays with dimensions >= 1.\n\n    Args:\n        arys (tuple of arrays): Arrays to be converted. All arguments must be\n            :class:`cupy.ndarray` objects. Only zero-dimensional array is\n            affected.\n\n    Returns:\n        If there are only one input, then it returns its converted version.\n        Otherwise, it returns a list of converted arrays.\n\n    .. seealso:: :func:`numpy.atleast_1d`\n\n    \"\"\"\n    return _atleast_nd_helper(1, arys)\n\n\ndef atleast_2d(*arys):\n    \"\"\"Converts arrays to arrays with dimensions >= 2.\n\n    If an input array has dimensions less than two, then this function inserts\n    new axes at the head of dimensions to make it have two dimensions.\n\n    Args:\n        arys (tuple of arrays): Arrays to be converted. All arguments must be\n            :class:`cupy.ndarray` objects.\n\n    Returns:\n        If there are only one input, then it returns its converted version.\n        Otherwise, it returns a list of converted arrays.\n\n    .. seealso:: :func:`numpy.atleast_2d`\n\n    \"\"\"\n    return _atleast_nd_helper(2, arys)\n\n\ndef atleast_3d(*arys):\n    \"\"\"Converts arrays to arrays with dimensions >= 3.\n\n    If an input array has dimensions less than three, then this function\n    inserts new axes to make it have three dimensions. The place of the new\n    axes are following:\n\n    - If its shape is ``()``, then the shape of output is ``(1, 1, 1)``.\n    - If its shape is ``(N,)``, then the shape of output is ``(1, N, 1)``.\n    - If its shape is ``(M, N)``, then the shape of output is ``(M, N, 1)``.\n    - Otherwise, the output is the input array itself.\n\n    Args:\n        arys (tuple of arrays): Arrays to be converted. All arguments must be\n            :class:`cupy.ndarray` objects.\n\n    Returns:\n        If there are only one input, then it returns its converted version.\n        Otherwise, it returns a list of converted arrays.\n\n    .. seealso:: :func:`numpy.atleast_3d`\n\n    \"\"\"\n    return _atleast_nd_helper(3, arys)\n\n\nbroadcast = core.broadcast\n\n\ndef broadcast_arrays(*args):\n    \"\"\"Broadcasts given arrays.\n\n    Args:\n        args (tuple of arrays): Arrays to broadcast for each other.\n\n    Returns:\n        list: A list of broadcasted arrays.\n\n    .. seealso:: :func:`numpy.broadcast_arrays`\n\n    \"\"\"\n    return broadcast(*args).values\n\n\ndef broadcast_to(array, shape):\n    \"\"\"Broadcast an array to a given shape.\n\n    Args:\n        array (cupy.ndarray): Array to broadcast.\n        shape (tuple of int): The shape of the desired array.\n\n    Returns:\n        cupy.ndarray: Broadcasted view.\n\n    .. seealso:: :func:`numpy.broadcast_to`\n\n    \"\"\"\n    return core.broadcast_to(array, shape)\n\n\ndef expand_dims(a, axis):\n    \"\"\"Expands given arrays.\n\n    Args:\n        a (cupy.ndarray): Array to be expanded.\n        axis (int): Position where new axis is to be inserted.\n\n    Returns:\n        cupy.ndarray: The number of dimensions is one greater than that of\n            the input array.\n\n    .. seealso:: :func:`numpy.expand_dims`\n\n    \"\"\"\n    # TODO(okuta): check type\n    shape = a.shape\n    if axis < 0:\n        axis = axis + len(shape) + 1\n    return a.reshape(shape[:axis] + (1,) + shape[axis:])\n\n\ndef squeeze(a, axis=None):\n    \"\"\"Removes size-one axes from the shape of an array.\n\n    Args:\n        a (cupy.ndarray): Array to be reshaped.\n        axis (int or tuple of ints): Axes to be removed. This function removes\n            all size-one axes by default. If one of the specified axes is not\n            of size one, an exception is raised.\n\n    Returns:\n        cupy.ndarray: An array without (specified) size-one axes.\n\n    .. seealso:: :func:`numpy.squeeze`\n\n    \"\"\"\n    # TODO(okuta): check type\n    return a.squeeze(axis)\n", "path": "cupy/manipulation/dims.py"}], "after_files": [{"content": "import six\n\nimport cupy\nfrom cupy import core\n\n\nzip_longest = six.moves.zip_longest\nsix_zip = six.moves.zip\n\n\n# Shape map for atleast_nd functions\n# (minimum dimension, input dimension) -> (output shape)\n_atleast_nd_shape_map = {\n    (1, 0): lambda shape: (1,),\n    (2, 0): lambda shape: (1, 1),\n    (2, 1): lambda shape: (1,) + shape,\n    (3, 0): lambda shape: (1, 1, 1),\n    (3, 1): lambda shape: (1,) + shape + (1,),\n    (3, 2): lambda shape: shape + (1,),\n}\n\n\ndef _atleast_nd_helper(n, arys):\n    \"\"\"Helper function for atleast_nd functions.\"\"\"\n\n    res = []\n    for a in arys:\n        if isinstance(a, cupy.ndarray):\n            if a.ndim < n:\n                new_shape = _atleast_nd_shape_map[(n, a.ndim)](a.shape)\n                a = a.reshape(*new_shape)\n        else:\n            raise TypeError('Unsupported type {}'.format(type(a)))\n        res.append(a)\n\n    if len(res) == 1:\n        res, = res\n    return res\n\n\ndef atleast_1d(*arys):\n    \"\"\"Converts arrays to arrays with dimensions >= 1.\n\n    Args:\n        arys (tuple of arrays): Arrays to be converted. All arguments must be\n            :class:`cupy.ndarray` objects. Only zero-dimensional array is\n            affected.\n\n    Returns:\n        If there are only one input, then it returns its converted version.\n        Otherwise, it returns a list of converted arrays.\n\n    .. seealso:: :func:`numpy.atleast_1d`\n\n    \"\"\"\n    return _atleast_nd_helper(1, arys)\n\n\ndef atleast_2d(*arys):\n    \"\"\"Converts arrays to arrays with dimensions >= 2.\n\n    If an input array has dimensions less than two, then this function inserts\n    new axes at the head of dimensions to make it have two dimensions.\n\n    Args:\n        arys (tuple of arrays): Arrays to be converted. All arguments must be\n            :class:`cupy.ndarray` objects.\n\n    Returns:\n        If there are only one input, then it returns its converted version.\n        Otherwise, it returns a list of converted arrays.\n\n    .. seealso:: :func:`numpy.atleast_2d`\n\n    \"\"\"\n    return _atleast_nd_helper(2, arys)\n\n\ndef atleast_3d(*arys):\n    \"\"\"Converts arrays to arrays with dimensions >= 3.\n\n    If an input array has dimensions less than three, then this function\n    inserts new axes to make it have three dimensions. The place of the new\n    axes are following:\n\n    - If its shape is ``()``, then the shape of output is ``(1, 1, 1)``.\n    - If its shape is ``(N,)``, then the shape of output is ``(1, N, 1)``.\n    - If its shape is ``(M, N)``, then the shape of output is ``(M, N, 1)``.\n    - Otherwise, the output is the input array itself.\n\n    Args:\n        arys (tuple of arrays): Arrays to be converted. All arguments must be\n            :class:`cupy.ndarray` objects.\n\n    Returns:\n        If there are only one input, then it returns its converted version.\n        Otherwise, it returns a list of converted arrays.\n\n    .. seealso:: :func:`numpy.atleast_3d`\n\n    \"\"\"\n    return _atleast_nd_helper(3, arys)\n\n\nbroadcast = core.broadcast\n\n\ndef broadcast_arrays(*args):\n    \"\"\"Broadcasts given arrays.\n\n    Args:\n        args (tuple of arrays): Arrays to broadcast for each other.\n\n    Returns:\n        list: A list of broadcasted arrays.\n\n    .. seealso:: :func:`numpy.broadcast_arrays`\n\n    \"\"\"\n    return list(broadcast(*args).values)\n\n\ndef broadcast_to(array, shape):\n    \"\"\"Broadcast an array to a given shape.\n\n    Args:\n        array (cupy.ndarray): Array to broadcast.\n        shape (tuple of int): The shape of the desired array.\n\n    Returns:\n        cupy.ndarray: Broadcasted view.\n\n    .. seealso:: :func:`numpy.broadcast_to`\n\n    \"\"\"\n    return core.broadcast_to(array, shape)\n\n\ndef expand_dims(a, axis):\n    \"\"\"Expands given arrays.\n\n    Args:\n        a (cupy.ndarray): Array to be expanded.\n        axis (int): Position where new axis is to be inserted.\n\n    Returns:\n        cupy.ndarray: The number of dimensions is one greater than that of\n            the input array.\n\n    .. seealso:: :func:`numpy.expand_dims`\n\n    \"\"\"\n    # TODO(okuta): check type\n    shape = a.shape\n    if axis < 0:\n        axis = axis + len(shape) + 1\n    return a.reshape(shape[:axis] + (1,) + shape[axis:])\n\n\ndef squeeze(a, axis=None):\n    \"\"\"Removes size-one axes from the shape of an array.\n\n    Args:\n        a (cupy.ndarray): Array to be reshaped.\n        axis (int or tuple of ints): Axes to be removed. This function removes\n            all size-one axes by default. If one of the specified axes is not\n            of size one, an exception is raised.\n\n    Returns:\n        cupy.ndarray: An array without (specified) size-one axes.\n\n    .. seealso:: :func:`numpy.squeeze`\n\n    \"\"\"\n    # TODO(okuta): check type\n    return a.squeeze(axis)\n", "path": "cupy/manipulation/dims.py"}]}