prompt: 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()
  
  ```
  
golden_diff: 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):
  
verification_info: {"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"}]}