We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Bug in PixelObservationWrapper 
Error log
```
    env = PixelObservationWrapper(env, pixels_only=True)
  File "/home/tsan/Desktop/gym/gym/wrappers/pixel_observation.py", line 89, in __init__
    pixels = self.env.render(**render_kwargs)
  File "/home/tsan/Desktop/gym/gym/core.py", line 233, in render
    return self.env.render(mode, **kwargs)
TypeError: render() got an unexpected keyword argument 'pixels'
```

Can be reproduced by running
```
import gym
from gym.wrappers.pixel_observation import PixelObservationWrapper  # pylint: disable=E0401

env = gym.make('Acrobot-v1')
env.reset()
env = PixelObservationWrapper(env, pixels_only=True)
env.step(0)
```

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `gym/wrappers/pixel_observation.py`
Content:
```
1 """An observation wrapper that augments observations by pixel values."""
2 
3 import collections
4 import copy
5 
6 import numpy as np
7 
8 from gym import spaces
9 from gym import ObservationWrapper
10 
11 STATE_KEY = 'state'
12 
13 
14 class PixelObservationWrapper(ObservationWrapper):
15     """Augment observations by pixel values."""
16 
17     def __init__(self,
18                  env,
19                  pixels_only=True,
20                  render_kwargs=None,
21                  pixel_keys=('pixels', )):
22         """Initializes a new pixel Wrapper.
23 
24         Args:
25             env: The environment to wrap.
26             pixels_only: If `True` (default), the original observation returned
27                 by the wrapped environment will be discarded, and a dictionary
28                 observation will only include pixels. If `False`, the
29                 observation dictionary will contain both the original
30                 observations and the pixel observations.
31             render_kwargs: Optional `dict` containing keyword arguments passed
32                 to the `self.render` method.
33             pixel_keys: Optional custom string specifying the pixel
34                 observation's key in the `OrderedDict` of observations.
35                 Defaults to 'pixels'.
36 
37         Raises:
38             ValueError: If `env`'s observation spec is not compatible with the
39                 wrapper. Supported formats are a single array, or a dict of
40                 arrays.
41             ValueError: If `env`'s observation already contains any of the
42                 specified `pixel_keys`.
43         """
44 
45         super(PixelObservationWrapper, self).__init__(env)
46 
47         if render_kwargs is None:
48             render_kwargs = {}
49 
50         for key in pixel_keys:
51             render_kwargs.setdefault(key, {})
52 
53             render_mode = render_kwargs[key].pop('mode', 'rgb_array')
54             assert render_mode == 'rgb_array', render_mode
55             render_kwargs[key]['mode'] = 'rgb_array'
56 
57         wrapped_observation_space = env.observation_space
58 
59         if isinstance(wrapped_observation_space, spaces.Box):
60             self._observation_is_dict = False
61             invalid_keys = set([STATE_KEY])
62         elif isinstance(wrapped_observation_space,
63                         (spaces.Dict, collections.MutableMapping)):
64             self._observation_is_dict = True
65             invalid_keys = set(wrapped_observation_space.spaces.keys())
66         else:
67             raise ValueError("Unsupported observation space structure.")
68 
69         if not pixels_only:
70             # Make sure that now keys in the `pixel_keys` overlap with
71             # `observation_keys`
72             overlapping_keys = set(pixel_keys) & set(invalid_keys)
73             if overlapping_keys:
74                 raise ValueError("Duplicate or reserved pixel keys {!r}."
75                                  .format(overlapping_keys))
76 
77         if pixels_only:
78             self.observation_space = spaces.Dict()
79         elif self._observation_is_dict:
80             self.observation_space = copy.deepcopy(wrapped_observation_space)
81         else:
82             self.observation_space = spaces.Dict()
83             self.observation_space.spaces[STATE_KEY] = wrapped_observation_space
84 
85         # Extend observation space with pixels.
86 
87         pixels_spaces = {}
88         for pixel_key in pixel_keys:
89             pixels = self.env.render(**render_kwargs)
90 
91             if np.issubdtype(pixels.dtype, np.integer):
92                 low, high = (0, 255)
93             elif np.issubdtype(pixels.dtype, np.float):
94                 low, high = (-float('inf'), float('inf'))
95             else:
96                 raise TypeError(pixels.dtype)
97 
98             pixels_space = spaces.Box(
99                 shape=pixels.shape, low=low, high=high, dtype=pixels.dtype)
100             pixels_spaces[pixel_key] = pixels_space
101 
102         self.observation_space.spaces.update(pixels_spaces)
103 
104         self._env = env
105         self._pixels_only = pixels_only
106         self._render_kwargs = render_kwargs
107         self._pixel_keys = pixel_keys
108 
109     def observation(self, observation):
110         pixel_observation = self._add_pixel_observation(observation)
111         return pixel_observation
112 
113     def _add_pixel_observation(self, observation):
114         if self._pixels_only:
115             observation = collections.OrderedDict()
116         elif self._observation_is_dict:
117             observation = type(observation)(observation)
118         else:
119             observation = collections.OrderedDict()
120             observation[STATE_KEY] = observation
121 
122         pixel_observations = {
123             pixel_key: self.env.render(**self._render_kwargs[pixel_key])
124             for pixel_key in self._pixel_keys
125         }
126 
127         observation.update(pixel_observations)
128 
129         return observation
130
```
--- 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/gym/wrappers/pixel_observation.py b/gym/wrappers/pixel_observation.py
--- a/gym/wrappers/pixel_observation.py
+++ b/gym/wrappers/pixel_observation.py
@@ -86,7 +86,7 @@
 
         pixels_spaces = {}
         for pixel_key in pixel_keys:
-            pixels = self.env.render(**render_kwargs)
+            pixels = self.env.render(**render_kwargs[pixel_key])
 
             if np.issubdtype(pixels.dtype, np.integer):
                 low, high = (0, 255)

{"golden_diff": "diff --git a/gym/wrappers/pixel_observation.py b/gym/wrappers/pixel_observation.py\n--- a/gym/wrappers/pixel_observation.py\n+++ b/gym/wrappers/pixel_observation.py\n@@ -86,7 +86,7 @@\n \n         pixels_spaces = {}\n         for pixel_key in pixel_keys:\n-            pixels = self.env.render(**render_kwargs)\n+            pixels = self.env.render(**render_kwargs[pixel_key])\n \n             if np.issubdtype(pixels.dtype, np.integer):\n                 low, high = (0, 255)\n", "issue": "Bug in PixelObservationWrapper \nError log\r\n```\r\n    env = PixelObservationWrapper(env, pixels_only=True)\r\n  File \"/home/tsan/Desktop/gym/gym/wrappers/pixel_observation.py\", line 89, in __init__\r\n    pixels = self.env.render(**render_kwargs)\r\n  File \"/home/tsan/Desktop/gym/gym/core.py\", line 233, in render\r\n    return self.env.render(mode, **kwargs)\r\nTypeError: render() got an unexpected keyword argument 'pixels'\r\n```\r\n\r\nCan be reproduced by running\r\n```\r\nimport gym\r\nfrom gym.wrappers.pixel_observation import PixelObservationWrapper  # pylint: disable=E0401\r\n\r\nenv = gym.make('Acrobot-v1')\r\nenv.reset()\r\nenv = PixelObservationWrapper(env, pixels_only=True)\r\nenv.step(0)\r\n```\n", "before_files": [{"content": "\"\"\"An observation wrapper that augments observations by pixel values.\"\"\"\n\nimport collections\nimport copy\n\nimport numpy as np\n\nfrom gym import spaces\nfrom gym import ObservationWrapper\n\nSTATE_KEY = 'state'\n\n\nclass PixelObservationWrapper(ObservationWrapper):\n    \"\"\"Augment observations by pixel values.\"\"\"\n\n    def __init__(self,\n                 env,\n                 pixels_only=True,\n                 render_kwargs=None,\n                 pixel_keys=('pixels', )):\n        \"\"\"Initializes a new pixel Wrapper.\n\n        Args:\n            env: The environment to wrap.\n            pixels_only: If `True` (default), the original observation returned\n                by the wrapped environment will be discarded, and a dictionary\n                observation will only include pixels. If `False`, the\n                observation dictionary will contain both the original\n                observations and the pixel observations.\n            render_kwargs: Optional `dict` containing keyword arguments passed\n                to the `self.render` method.\n            pixel_keys: Optional custom string specifying the pixel\n                observation's key in the `OrderedDict` of observations.\n                Defaults to 'pixels'.\n\n        Raises:\n            ValueError: If `env`'s observation spec is not compatible with the\n                wrapper. Supported formats are a single array, or a dict of\n                arrays.\n            ValueError: If `env`'s observation already contains any of the\n                specified `pixel_keys`.\n        \"\"\"\n\n        super(PixelObservationWrapper, self).__init__(env)\n\n        if render_kwargs is None:\n            render_kwargs = {}\n\n        for key in pixel_keys:\n            render_kwargs.setdefault(key, {})\n\n            render_mode = render_kwargs[key].pop('mode', 'rgb_array')\n            assert render_mode == 'rgb_array', render_mode\n            render_kwargs[key]['mode'] = 'rgb_array'\n\n        wrapped_observation_space = env.observation_space\n\n        if isinstance(wrapped_observation_space, spaces.Box):\n            self._observation_is_dict = False\n            invalid_keys = set([STATE_KEY])\n        elif isinstance(wrapped_observation_space,\n                        (spaces.Dict, collections.MutableMapping)):\n            self._observation_is_dict = True\n            invalid_keys = set(wrapped_observation_space.spaces.keys())\n        else:\n            raise ValueError(\"Unsupported observation space structure.\")\n\n        if not pixels_only:\n            # Make sure that now keys in the `pixel_keys` overlap with\n            # `observation_keys`\n            overlapping_keys = set(pixel_keys) & set(invalid_keys)\n            if overlapping_keys:\n                raise ValueError(\"Duplicate or reserved pixel keys {!r}.\"\n                                 .format(overlapping_keys))\n\n        if pixels_only:\n            self.observation_space = spaces.Dict()\n        elif self._observation_is_dict:\n            self.observation_space = copy.deepcopy(wrapped_observation_space)\n        else:\n            self.observation_space = spaces.Dict()\n            self.observation_space.spaces[STATE_KEY] = wrapped_observation_space\n\n        # Extend observation space with pixels.\n\n        pixels_spaces = {}\n        for pixel_key in pixel_keys:\n            pixels = self.env.render(**render_kwargs)\n\n            if np.issubdtype(pixels.dtype, np.integer):\n                low, high = (0, 255)\n            elif np.issubdtype(pixels.dtype, np.float):\n                low, high = (-float('inf'), float('inf'))\n            else:\n                raise TypeError(pixels.dtype)\n\n            pixels_space = spaces.Box(\n                shape=pixels.shape, low=low, high=high, dtype=pixels.dtype)\n            pixels_spaces[pixel_key] = pixels_space\n\n        self.observation_space.spaces.update(pixels_spaces)\n\n        self._env = env\n        self._pixels_only = pixels_only\n        self._render_kwargs = render_kwargs\n        self._pixel_keys = pixel_keys\n\n    def observation(self, observation):\n        pixel_observation = self._add_pixel_observation(observation)\n        return pixel_observation\n\n    def _add_pixel_observation(self, observation):\n        if self._pixels_only:\n            observation = collections.OrderedDict()\n        elif self._observation_is_dict:\n            observation = type(observation)(observation)\n        else:\n            observation = collections.OrderedDict()\n            observation[STATE_KEY] = observation\n\n        pixel_observations = {\n            pixel_key: self.env.render(**self._render_kwargs[pixel_key])\n            for pixel_key in self._pixel_keys\n        }\n\n        observation.update(pixel_observations)\n\n        return observation\n", "path": "gym/wrappers/pixel_observation.py"}], "after_files": [{"content": "\"\"\"An observation wrapper that augments observations by pixel values.\"\"\"\n\nimport collections\nimport copy\n\nimport numpy as np\n\nfrom gym import spaces\nfrom gym import ObservationWrapper\n\nSTATE_KEY = 'state'\n\n\nclass PixelObservationWrapper(ObservationWrapper):\n    \"\"\"Augment observations by pixel values.\"\"\"\n\n    def __init__(self,\n                 env,\n                 pixels_only=True,\n                 render_kwargs=None,\n                 pixel_keys=('pixels', )):\n        \"\"\"Initializes a new pixel Wrapper.\n\n        Args:\n            env: The environment to wrap.\n            pixels_only: If `True` (default), the original observation returned\n                by the wrapped environment will be discarded, and a dictionary\n                observation will only include pixels. If `False`, the\n                observation dictionary will contain both the original\n                observations and the pixel observations.\n            render_kwargs: Optional `dict` containing keyword arguments passed\n                to the `self.render` method.\n            pixel_keys: Optional custom string specifying the pixel\n                observation's key in the `OrderedDict` of observations.\n                Defaults to 'pixels'.\n\n        Raises:\n            ValueError: If `env`'s observation spec is not compatible with the\n                wrapper. Supported formats are a single array, or a dict of\n                arrays.\n            ValueError: If `env`'s observation already contains any of the\n                specified `pixel_keys`.\n        \"\"\"\n\n        super(PixelObservationWrapper, self).__init__(env)\n\n        if render_kwargs is None:\n            render_kwargs = {}\n\n        for key in pixel_keys:\n            render_kwargs.setdefault(key, {})\n\n            render_mode = render_kwargs[key].pop('mode', 'rgb_array')\n            assert render_mode == 'rgb_array', render_mode\n            render_kwargs[key]['mode'] = 'rgb_array'\n\n        wrapped_observation_space = env.observation_space\n\n        if isinstance(wrapped_observation_space, spaces.Box):\n            self._observation_is_dict = False\n            invalid_keys = set([STATE_KEY])\n        elif isinstance(wrapped_observation_space,\n                        (spaces.Dict, collections.MutableMapping)):\n            self._observation_is_dict = True\n            invalid_keys = set(wrapped_observation_space.spaces.keys())\n        else:\n            raise ValueError(\"Unsupported observation space structure.\")\n\n        if not pixels_only:\n            # Make sure that now keys in the `pixel_keys` overlap with\n            # `observation_keys`\n            overlapping_keys = set(pixel_keys) & set(invalid_keys)\n            if overlapping_keys:\n                raise ValueError(\"Duplicate or reserved pixel keys {!r}.\"\n                                 .format(overlapping_keys))\n\n        if pixels_only:\n            self.observation_space = spaces.Dict()\n        elif self._observation_is_dict:\n            self.observation_space = copy.deepcopy(wrapped_observation_space)\n        else:\n            self.observation_space = spaces.Dict()\n            self.observation_space.spaces[STATE_KEY] = wrapped_observation_space\n\n        # Extend observation space with pixels.\n\n        pixels_spaces = {}\n        for pixel_key in pixel_keys:\n            pixels = self.env.render(**render_kwargs[pixel_key])\n\n            if np.issubdtype(pixels.dtype, np.integer):\n                low, high = (0, 255)\n            elif np.issubdtype(pixels.dtype, np.float):\n                low, high = (-float('inf'), float('inf'))\n            else:\n                raise TypeError(pixels.dtype)\n\n            pixels_space = spaces.Box(\n                shape=pixels.shape, low=low, high=high, dtype=pixels.dtype)\n            pixels_spaces[pixel_key] = pixels_space\n\n        self.observation_space.spaces.update(pixels_spaces)\n\n        self._env = env\n        self._pixels_only = pixels_only\n        self._render_kwargs = render_kwargs\n        self._pixel_keys = pixel_keys\n\n    def observation(self, observation):\n        pixel_observation = self._add_pixel_observation(observation)\n        return pixel_observation\n\n    def _add_pixel_observation(self, observation):\n        if self._pixels_only:\n            observation = collections.OrderedDict()\n        elif self._observation_is_dict:\n            observation = type(observation)(observation)\n        else:\n            observation = collections.OrderedDict()\n            observation[STATE_KEY] = observation\n\n        pixel_observations = {\n            pixel_key: self.env.render(**self._render_kwargs[pixel_key])\n            for pixel_key in self._pixel_keys\n        }\n\n        observation.update(pixel_observations)\n\n        return observation\n", "path": "gym/wrappers/pixel_observation.py"}]}