We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
[BUG]: Flasbax bug on LBF (type issue)
### Describe the bug
In the AgentID wrapper, the new_agents_view type is not enforced to be consistent, so for LBF with flashbax a dtype error emerges.

### To Reproduce
Steps to reproduce the behavior:
1. Run LBF with flashbax.

### Expected behavior
Expected the observation to be added easily to the buffer.

### Context (Environment)
 - Updated jumanji

### Additional context
This is somewhat an exercise in opening an issue!

### Possible Solution
Will make a PR soon! Basically a cast to the agents_view type.


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `mava/wrappers/observation.py`
Content:
```
1 # Copyright 2022 InstaDeep Ltd. All rights reserved.
2 #
3 # Licensed under the Apache License, Version 2.0 (the "License");
4 # you may not use this file except in compliance with the License.
5 # You may obtain a copy of the License at
6 #
7 #     http://www.apache.org/licenses/LICENSE-2.0
8 #
9 # Unless required by applicable law or agreed to in writing, software
10 # distributed under the License is distributed on an "AS IS" BASIS,
11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 # See the License for the specific language governing permissions and
13 # limitations under the License.
14 
15 from typing import Tuple, Union
16 
17 import chex
18 import jax.numpy as jnp
19 from jumanji import specs
20 from jumanji.env import Environment
21 from jumanji.types import TimeStep
22 from jumanji.wrappers import Wrapper
23 
24 from mava.types import Observation, ObservationGlobalState, State
25 
26 
27 class AgentIDWrapper(Wrapper):
28     """A wrapper to add a one-hot vector as agent IDs to the original observation.
29     It can be useful in multi-agent environments where agents require unique identification.
30     """
31 
32     def __init__(self, env: Environment):
33         super().__init__(env)
34 
35     def _add_agent_ids(
36         self, timestep: TimeStep, num_agents: int
37     ) -> Union[Observation, ObservationGlobalState]:
38         """Adds agent IDs to the observation."""
39         obs = timestep.observation
40         agent_ids = jnp.eye(num_agents)
41         agents_view = jnp.concatenate([agent_ids, obs.agents_view], axis=-1)
42 
43         return obs._replace(agents_view=agents_view)  # type: ignore
44 
45     def reset(self, key: chex.PRNGKey) -> Tuple[State, TimeStep]:
46         """Reset the environment."""
47         state, timestep = self._env.reset(key)
48         timestep.observation = self._add_agent_ids(timestep, self._env.num_agents)
49 
50         return state, timestep
51 
52     def step(
53         self,
54         state: State,
55         action: chex.Array,
56     ) -> Tuple[State, TimeStep]:
57         """Step the environment."""
58         state, timestep = self._env.step(state, action)
59         timestep.observation = self._add_agent_ids(timestep, self._env.num_agents)
60 
61         return state, timestep
62 
63     def observation_spec(
64         self,
65     ) -> Union[specs.Spec[Observation], specs.Spec[ObservationGlobalState]]:
66         """Specification of the observation of the selected environment."""
67         obs_spec = self._env.observation_spec()
68         num_obs_features = obs_spec.agents_view.shape[-1] + self._env.num_agents
69         dtype = obs_spec.agents_view.dtype
70         agents_view = specs.Array((self._env.num_agents, num_obs_features), dtype, "agents_view")
71 
72         return obs_spec.replace(agents_view=agents_view)
73 
74 
75 class GlobalStateWrapper(Wrapper):
76     """Wrapper for adding global state to an environment that follows the mava API.
77 
78     The wrapper includes a global environment state to be used by the centralised critic.
79     Note here that since most environments do not have a global state, we create one
80     by concatenating the observations of all agents.
81     """
82 
83     def modify_timestep(self, timestep: TimeStep) -> TimeStep[ObservationGlobalState]:
84         global_state = jnp.concatenate(timestep.observation.agents_view, axis=0)
85         global_state = jnp.tile(global_state, (self._env.num_agents, 1))
86 
87         observation = ObservationGlobalState(
88             global_state=global_state,
89             agents_view=timestep.observation.agents_view,
90             action_mask=timestep.observation.action_mask,
91             step_count=timestep.observation.step_count,
92         )
93 
94         return timestep.replace(observation=observation)
95 
96     def reset(self, key: chex.PRNGKey) -> Tuple[State, TimeStep]:
97         """Reset the environment. Updates the step count."""
98         state, timestep = self._env.reset(key)
99         return state, self.modify_timestep(timestep)
100 
101     def step(self, state: State, action: chex.Array) -> Tuple[State, TimeStep]:
102         """Step the environment. Updates the step count."""
103         state, timestep = self._env.step(state, action)
104         return state, self.modify_timestep(timestep)
105 
106     def observation_spec(self) -> specs.Spec[ObservationGlobalState]:
107         """Specification of the observation of the selected environment."""
108 
109         obs_spec = self._env.observation_spec()
110         num_obs_features = obs_spec.agents_view.shape[-1]
111         global_state = specs.Array(
112             (self._env.num_agents, self._env.num_agents * num_obs_features),
113             obs_spec.agents_view.dtype,
114             "global_state",
115         )
116 
117         return specs.Spec(
118             ObservationGlobalState,
119             "ObservationSpec",
120             agents_view=obs_spec.agents_view,
121             action_mask=obs_spec.action_mask,
122             global_state=global_state,
123             step_count=obs_spec.step_count,
124         )
125
```
--- 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/mava/wrappers/observation.py b/mava/wrappers/observation.py
--- a/mava/wrappers/observation.py
+++ b/mava/wrappers/observation.py
@@ -38,7 +38,11 @@
         """Adds agent IDs to the observation."""
         obs = timestep.observation
         agent_ids = jnp.eye(num_agents)
-        agents_view = jnp.concatenate([agent_ids, obs.agents_view], axis=-1)
+        agents_view = jnp.concatenate(
+            [agent_ids, obs.agents_view],
+            axis=-1,
+            dtype=obs.agents_view.dtype,
+        )
 
         return obs._replace(agents_view=agents_view)  # type: ignore

{"golden_diff": "diff --git a/mava/wrappers/observation.py b/mava/wrappers/observation.py\n--- a/mava/wrappers/observation.py\n+++ b/mava/wrappers/observation.py\n@@ -38,7 +38,11 @@\n         \"\"\"Adds agent IDs to the observation.\"\"\"\n         obs = timestep.observation\n         agent_ids = jnp.eye(num_agents)\n-        agents_view = jnp.concatenate([agent_ids, obs.agents_view], axis=-1)\n+        agents_view = jnp.concatenate(\n+            [agent_ids, obs.agents_view],\n+            axis=-1,\n+            dtype=obs.agents_view.dtype,\n+        )\n \n         return obs._replace(agents_view=agents_view)  # type: ignore\n", "issue": "[BUG]: Flasbax bug on LBF (type issue)\n### Describe the bug\r\nIn the AgentID wrapper, the new_agents_view type is not enforced to be consistent, so for LBF with flashbax a dtype error emerges.\r\n\r\n### To Reproduce\r\nSteps to reproduce the behavior:\r\n1. Run LBF with flashbax.\r\n\r\n### Expected behavior\r\nExpected the observation to be added easily to the buffer.\r\n\r\n### Context (Environment)\r\n - Updated jumanji\r\n\r\n### Additional context\r\nThis is somewhat an exercise in opening an issue!\r\n\r\n### Possible Solution\r\nWill make a PR soon! Basically a cast to the agents_view type.\r\n\n", "before_files": [{"content": "# Copyright 2022 InstaDeep Ltd. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom typing import Tuple, Union\n\nimport chex\nimport jax.numpy as jnp\nfrom jumanji import specs\nfrom jumanji.env import Environment\nfrom jumanji.types import TimeStep\nfrom jumanji.wrappers import Wrapper\n\nfrom mava.types import Observation, ObservationGlobalState, State\n\n\nclass AgentIDWrapper(Wrapper):\n    \"\"\"A wrapper to add a one-hot vector as agent IDs to the original observation.\n    It can be useful in multi-agent environments where agents require unique identification.\n    \"\"\"\n\n    def __init__(self, env: Environment):\n        super().__init__(env)\n\n    def _add_agent_ids(\n        self, timestep: TimeStep, num_agents: int\n    ) -> Union[Observation, ObservationGlobalState]:\n        \"\"\"Adds agent IDs to the observation.\"\"\"\n        obs = timestep.observation\n        agent_ids = jnp.eye(num_agents)\n        agents_view = jnp.concatenate([agent_ids, obs.agents_view], axis=-1)\n\n        return obs._replace(agents_view=agents_view)  # type: ignore\n\n    def reset(self, key: chex.PRNGKey) -> Tuple[State, TimeStep]:\n        \"\"\"Reset the environment.\"\"\"\n        state, timestep = self._env.reset(key)\n        timestep.observation = self._add_agent_ids(timestep, self._env.num_agents)\n\n        return state, timestep\n\n    def step(\n        self,\n        state: State,\n        action: chex.Array,\n    ) -> Tuple[State, TimeStep]:\n        \"\"\"Step the environment.\"\"\"\n        state, timestep = self._env.step(state, action)\n        timestep.observation = self._add_agent_ids(timestep, self._env.num_agents)\n\n        return state, timestep\n\n    def observation_spec(\n        self,\n    ) -> Union[specs.Spec[Observation], specs.Spec[ObservationGlobalState]]:\n        \"\"\"Specification of the observation of the selected environment.\"\"\"\n        obs_spec = self._env.observation_spec()\n        num_obs_features = obs_spec.agents_view.shape[-1] + self._env.num_agents\n        dtype = obs_spec.agents_view.dtype\n        agents_view = specs.Array((self._env.num_agents, num_obs_features), dtype, \"agents_view\")\n\n        return obs_spec.replace(agents_view=agents_view)\n\n\nclass GlobalStateWrapper(Wrapper):\n    \"\"\"Wrapper for adding global state to an environment that follows the mava API.\n\n    The wrapper includes a global environment state to be used by the centralised critic.\n    Note here that since most environments do not have a global state, we create one\n    by concatenating the observations of all agents.\n    \"\"\"\n\n    def modify_timestep(self, timestep: TimeStep) -> TimeStep[ObservationGlobalState]:\n        global_state = jnp.concatenate(timestep.observation.agents_view, axis=0)\n        global_state = jnp.tile(global_state, (self._env.num_agents, 1))\n\n        observation = ObservationGlobalState(\n            global_state=global_state,\n            agents_view=timestep.observation.agents_view,\n            action_mask=timestep.observation.action_mask,\n            step_count=timestep.observation.step_count,\n        )\n\n        return timestep.replace(observation=observation)\n\n    def reset(self, key: chex.PRNGKey) -> Tuple[State, TimeStep]:\n        \"\"\"Reset the environment. Updates the step count.\"\"\"\n        state, timestep = self._env.reset(key)\n        return state, self.modify_timestep(timestep)\n\n    def step(self, state: State, action: chex.Array) -> Tuple[State, TimeStep]:\n        \"\"\"Step the environment. Updates the step count.\"\"\"\n        state, timestep = self._env.step(state, action)\n        return state, self.modify_timestep(timestep)\n\n    def observation_spec(self) -> specs.Spec[ObservationGlobalState]:\n        \"\"\"Specification of the observation of the selected environment.\"\"\"\n\n        obs_spec = self._env.observation_spec()\n        num_obs_features = obs_spec.agents_view.shape[-1]\n        global_state = specs.Array(\n            (self._env.num_agents, self._env.num_agents * num_obs_features),\n            obs_spec.agents_view.dtype,\n            \"global_state\",\n        )\n\n        return specs.Spec(\n            ObservationGlobalState,\n            \"ObservationSpec\",\n            agents_view=obs_spec.agents_view,\n            action_mask=obs_spec.action_mask,\n            global_state=global_state,\n            step_count=obs_spec.step_count,\n        )\n", "path": "mava/wrappers/observation.py"}], "after_files": [{"content": "# Copyright 2022 InstaDeep Ltd. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom typing import Tuple, Union\n\nimport chex\nimport jax.numpy as jnp\nfrom jumanji import specs\nfrom jumanji.env import Environment\nfrom jumanji.types import TimeStep\nfrom jumanji.wrappers import Wrapper\n\nfrom mava.types import Observation, ObservationGlobalState, State\n\n\nclass AgentIDWrapper(Wrapper):\n    \"\"\"A wrapper to add a one-hot vector as agent IDs to the original observation.\n    It can be useful in multi-agent environments where agents require unique identification.\n    \"\"\"\n\n    def __init__(self, env: Environment):\n        super().__init__(env)\n\n    def _add_agent_ids(\n        self, timestep: TimeStep, num_agents: int\n    ) -> Union[Observation, ObservationGlobalState]:\n        \"\"\"Adds agent IDs to the observation.\"\"\"\n        obs = timestep.observation\n        agent_ids = jnp.eye(num_agents)\n        agents_view = jnp.concatenate(\n            [agent_ids, obs.agents_view],\n            axis=-1,\n            dtype=obs.agents_view.dtype,\n        )\n\n        return obs._replace(agents_view=agents_view)  # type: ignore\n\n    def reset(self, key: chex.PRNGKey) -> Tuple[State, TimeStep]:\n        \"\"\"Reset the environment.\"\"\"\n        state, timestep = self._env.reset(key)\n        timestep.observation = self._add_agent_ids(timestep, self._env.num_agents)\n\n        return state, timestep\n\n    def step(\n        self,\n        state: State,\n        action: chex.Array,\n    ) -> Tuple[State, TimeStep]:\n        \"\"\"Step the environment.\"\"\"\n        state, timestep = self._env.step(state, action)\n        timestep.observation = self._add_agent_ids(timestep, self._env.num_agents)\n\n        return state, timestep\n\n    def observation_spec(\n        self,\n    ) -> Union[specs.Spec[Observation], specs.Spec[ObservationGlobalState]]:\n        \"\"\"Specification of the observation of the selected environment.\"\"\"\n        obs_spec = self._env.observation_spec()\n        num_obs_features = obs_spec.agents_view.shape[-1] + self._env.num_agents\n        dtype = obs_spec.agents_view.dtype\n        agents_view = specs.Array((self._env.num_agents, num_obs_features), dtype, \"agents_view\")\n\n        return obs_spec.replace(agents_view=agents_view)\n\n\nclass GlobalStateWrapper(Wrapper):\n    \"\"\"Wrapper for adding global state to an environment that follows the mava API.\n\n    The wrapper includes a global environment state to be used by the centralised critic.\n    Note here that since most environments do not have a global state, we create one\n    by concatenating the observations of all agents.\n    \"\"\"\n\n    def modify_timestep(self, timestep: TimeStep) -> TimeStep[ObservationGlobalState]:\n        global_state = jnp.concatenate(timestep.observation.agents_view, axis=0)\n        global_state = jnp.tile(global_state, (self._env.num_agents, 1))\n\n        observation = ObservationGlobalState(\n            global_state=global_state,\n            agents_view=timestep.observation.agents_view,\n            action_mask=timestep.observation.action_mask,\n            step_count=timestep.observation.step_count,\n        )\n\n        return timestep.replace(observation=observation)\n\n    def reset(self, key: chex.PRNGKey) -> Tuple[State, TimeStep]:\n        \"\"\"Reset the environment. Updates the step count.\"\"\"\n        state, timestep = self._env.reset(key)\n        return state, self.modify_timestep(timestep)\n\n    def step(self, state: State, action: chex.Array) -> Tuple[State, TimeStep]:\n        \"\"\"Step the environment. Updates the step count.\"\"\"\n        state, timestep = self._env.step(state, action)\n        return state, self.modify_timestep(timestep)\n\n    def observation_spec(self) -> specs.Spec[ObservationGlobalState]:\n        \"\"\"Specification of the observation of the selected environment.\"\"\"\n\n        obs_spec = self._env.observation_spec()\n        num_obs_features = obs_spec.agents_view.shape[-1]\n        global_state = specs.Array(\n            (self._env.num_agents, self._env.num_agents * num_obs_features),\n            obs_spec.agents_view.dtype,\n            \"global_state\",\n        )\n\n        return specs.Spec(\n            ObservationGlobalState,\n            \"ObservationSpec\",\n            agents_view=obs_spec.agents_view,\n            action_mask=obs_spec.action_mask,\n            global_state=global_state,\n            step_count=obs_spec.step_count,\n        )\n", "path": "mava/wrappers/observation.py"}]}