We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Support basic indexing in Variable class
Currently `Variable` partially supports `__getitem__`. I need full support of basic indexing.
- [x] int index #1343 
- [x] slices #1154
- [x] new axis #1257 
- [x] elipsis #1343 

see also: http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#basic-slicing-and-indexing


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `chainer/functions/array/get_item.py`
Content:
```
1 import collections
2 
3 from chainer import cuda
4 from chainer import function
5 from chainer.utils import type_check
6 from chainer import variable
7 
8 
9 class GetItem(function.Function):
10 
11     """Function that slices array and extract elements."""
12 
13     def __init__(self, slices):
14         if not isinstance(slices, collections.Iterable):
15             slices = tuple([slices])
16         self.slices = slices
17 
18     def check_type_forward(self, in_types):
19         type_check.expect(in_types.size() == 1)
20         valid_slice = len(self.slices) - self.slices.count(None)
21         type_check.expect(in_types[0].ndim == valid_slice)
22 
23     def forward(self, xs):
24         ary = xs[0]
25         return ary[tuple(self.slices)],
26 
27     def backward(self, xs, gys):
28         xp = cuda.get_array_module(*xs)
29         gy = gys[0]
30         gx = xp.zeros_like(xs[0])
31         gx[tuple(self.slices)] = gy
32         return gx,
33 
34 
35 def get_item(x, slices):
36     """Extract elements from array with specified shape, axes and offsets.
37 
38     Args:
39         x (tuple of Variables): Variable to be sliced.
40         slices (slice or tuple of slices): Slice objects to slice variable.
41 
42     Returns:
43         Variable: :class:`~chainer.Variable` object
44             which contains sliced array of ``x``.
45 
46     """
47     return GetItem(slices)(x)
48 
49 
50 def install_variable_get_item():
51     variable.Variable.__getitem__ = get_item
52
```
--- 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/chainer/functions/array/get_item.py b/chainer/functions/array/get_item.py
--- a/chainer/functions/array/get_item.py
+++ b/chainer/functions/array/get_item.py
@@ -1,7 +1,11 @@
 import collections
 
+import numpy
+
+import chainer
 from chainer import cuda
 from chainer import function
+from chainer import utils
 from chainer.utils import type_check
 from chainer import variable
 
@@ -13,16 +17,29 @@
     def __init__(self, slices):
         if not isinstance(slices, collections.Iterable):
             slices = tuple([slices])
+
+        if chainer.is_debug():
+            n_ellipses = 0
+            for s in slices:
+                if numpy.isscalar(s) or s is None or isinstance(s, slice):
+                    pass
+                elif s is Ellipsis:
+                    n_ellipses += 1
+                else:
+                    raise ValueError('Only basic indexing is supported')
+            if n_ellipses > 1:
+                raise ValueError('Only one Ellipsis is allowed')
+
         self.slices = slices
 
     def check_type_forward(self, in_types):
         type_check.expect(in_types.size() == 1)
         valid_slice = len(self.slices) - self.slices.count(None)
-        type_check.expect(in_types[0].ndim == valid_slice)
+        type_check.expect(in_types[0].ndim >= valid_slice)
 
     def forward(self, xs):
         ary = xs[0]
-        return ary[tuple(self.slices)],
+        return utils.force_array(ary[tuple(self.slices)]),
 
     def backward(self, xs, gys):
         xp = cuda.get_array_module(*xs)
@@ -37,12 +54,19 @@
 
     Args:
         x (tuple of Variables): Variable to be sliced.
-        slices (slice or tuple of slices): Slice objects to slice variable.
+        slices (int, slice, None or Ellipsis or tuple of them): Basic slicing
+            to slice a variable. It supports ``int``, ``slice``, ``newaxis``
+            (equivalent to ``None``) and ``Ellipsis``.
 
     Returns:
         Variable: :class:`~chainer.Variable` object
             which contains sliced array of ``x``.
 
+    .. note::
+
+       See NumPy document for details of `indexing
+       <http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html>`_.
+
     """
     return GetItem(slices)(x)

{"golden_diff": "diff --git a/chainer/functions/array/get_item.py b/chainer/functions/array/get_item.py\n--- a/chainer/functions/array/get_item.py\n+++ b/chainer/functions/array/get_item.py\n@@ -1,7 +1,11 @@\n import collections\n \n+import numpy\n+\n+import chainer\n from chainer import cuda\n from chainer import function\n+from chainer import utils\n from chainer.utils import type_check\n from chainer import variable\n \n@@ -13,16 +17,29 @@\n     def __init__(self, slices):\n         if not isinstance(slices, collections.Iterable):\n             slices = tuple([slices])\n+\n+        if chainer.is_debug():\n+            n_ellipses = 0\n+            for s in slices:\n+                if numpy.isscalar(s) or s is None or isinstance(s, slice):\n+                    pass\n+                elif s is Ellipsis:\n+                    n_ellipses += 1\n+                else:\n+                    raise ValueError('Only basic indexing is supported')\n+            if n_ellipses > 1:\n+                raise ValueError('Only one Ellipsis is allowed')\n+\n         self.slices = slices\n \n     def check_type_forward(self, in_types):\n         type_check.expect(in_types.size() == 1)\n         valid_slice = len(self.slices) - self.slices.count(None)\n-        type_check.expect(in_types[0].ndim == valid_slice)\n+        type_check.expect(in_types[0].ndim >= valid_slice)\n \n     def forward(self, xs):\n         ary = xs[0]\n-        return ary[tuple(self.slices)],\n+        return utils.force_array(ary[tuple(self.slices)]),\n \n     def backward(self, xs, gys):\n         xp = cuda.get_array_module(*xs)\n@@ -37,12 +54,19 @@\n \n     Args:\n         x (tuple of Variables): Variable to be sliced.\n-        slices (slice or tuple of slices): Slice objects to slice variable.\n+        slices (int, slice, None or Ellipsis or tuple of them): Basic slicing\n+            to slice a variable. It supports ``int``, ``slice``, ``newaxis``\n+            (equivalent to ``None``) and ``Ellipsis``.\n \n     Returns:\n         Variable: :class:`~chainer.Variable` object\n             which contains sliced array of ``x``.\n \n+    .. note::\n+\n+       See NumPy document for details of `indexing\n+       <http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html>`_.\n+\n     \"\"\"\n     return GetItem(slices)(x)\n", "issue": "Support basic indexing in Variable class\nCurrently `Variable` partially supports `__getitem__`. I need full support of basic indexing.\n- [x] int index #1343 \n- [x] slices #1154\n- [x] new axis #1257 \n- [x] elipsis #1343 \n\nsee also: http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#basic-slicing-and-indexing\n\n", "before_files": [{"content": "import collections\n\nfrom chainer import cuda\nfrom chainer import function\nfrom chainer.utils import type_check\nfrom chainer import variable\n\n\nclass GetItem(function.Function):\n\n    \"\"\"Function that slices array and extract elements.\"\"\"\n\n    def __init__(self, slices):\n        if not isinstance(slices, collections.Iterable):\n            slices = tuple([slices])\n        self.slices = slices\n\n    def check_type_forward(self, in_types):\n        type_check.expect(in_types.size() == 1)\n        valid_slice = len(self.slices) - self.slices.count(None)\n        type_check.expect(in_types[0].ndim == valid_slice)\n\n    def forward(self, xs):\n        ary = xs[0]\n        return ary[tuple(self.slices)],\n\n    def backward(self, xs, gys):\n        xp = cuda.get_array_module(*xs)\n        gy = gys[0]\n        gx = xp.zeros_like(xs[0])\n        gx[tuple(self.slices)] = gy\n        return gx,\n\n\ndef get_item(x, slices):\n    \"\"\"Extract elements from array with specified shape, axes and offsets.\n\n    Args:\n        x (tuple of Variables): Variable to be sliced.\n        slices (slice or tuple of slices): Slice objects to slice variable.\n\n    Returns:\n        Variable: :class:`~chainer.Variable` object\n            which contains sliced array of ``x``.\n\n    \"\"\"\n    return GetItem(slices)(x)\n\n\ndef install_variable_get_item():\n    variable.Variable.__getitem__ = get_item\n", "path": "chainer/functions/array/get_item.py"}], "after_files": [{"content": "import collections\n\nimport numpy\n\nimport chainer\nfrom chainer import cuda\nfrom chainer import function\nfrom chainer import utils\nfrom chainer.utils import type_check\nfrom chainer import variable\n\n\nclass GetItem(function.Function):\n\n    \"\"\"Function that slices array and extract elements.\"\"\"\n\n    def __init__(self, slices):\n        if not isinstance(slices, collections.Iterable):\n            slices = tuple([slices])\n\n        if chainer.is_debug():\n            n_ellipses = 0\n            for s in slices:\n                if numpy.isscalar(s) or s is None or isinstance(s, slice):\n                    pass\n                elif s is Ellipsis:\n                    n_ellipses += 1\n                else:\n                    raise ValueError('Only basic indexing is supported')\n            if n_ellipses > 1:\n                raise ValueError('Only one Ellipsis is allowed')\n\n        self.slices = slices\n\n    def check_type_forward(self, in_types):\n        type_check.expect(in_types.size() == 1)\n        valid_slice = len(self.slices) - self.slices.count(None)\n        type_check.expect(in_types[0].ndim >= valid_slice)\n\n    def forward(self, xs):\n        ary = xs[0]\n        return utils.force_array(ary[tuple(self.slices)]),\n\n    def backward(self, xs, gys):\n        xp = cuda.get_array_module(*xs)\n        gy = gys[0]\n        gx = xp.zeros_like(xs[0])\n        gx[tuple(self.slices)] = gy\n        return gx,\n\n\ndef get_item(x, slices):\n    \"\"\"Extract elements from array with specified shape, axes and offsets.\n\n    Args:\n        x (tuple of Variables): Variable to be sliced.\n        slices (int, slice, None or Ellipsis or tuple of them): Basic slicing\n            to slice a variable. It supports ``int``, ``slice``, ``newaxis``\n            (equivalent to ``None``) and ``Ellipsis``.\n\n    Returns:\n        Variable: :class:`~chainer.Variable` object\n            which contains sliced array of ``x``.\n\n    .. note::\n\n       See NumPy document for details of `indexing\n       <http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html>`_.\n\n    \"\"\"\n    return GetItem(slices)(x)\n\n\ndef install_variable_get_item():\n    variable.Variable.__getitem__ = get_item\n", "path": "chainer/functions/array/get_item.py"}]}