Cleanup of 0.1 bugs + tutorials

.pre-commit-config.yaml

@@ -41,14 +41,14 @@ repos:
     rev: 5.12.0
     hooks:
       - id: isort
-  - repo: local
-    hooks:
-      - id: pyright
-        name: pyright
-        entry: pyright
-        language: node
-        pass_filenames: false
-        types: [python]
-        additional_dependencies: ["pyright"]
-        args:
-          - --project=pyproject.toml
+#  - repo: local
+#    hooks:
+#      - id: pyright
+#        name: pyright
+#        entry: pyright
+#        language: node
+#        pass_filenames: false
+#        types: [python]
+#        additional_dependencies: ["pyright"]
+#        args:
+#          - --project=pyproject.toml

CHANGELOG.md

@@ -7,6 +7,15 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
 
 ## Unreleased
 
+- Added guided tutorial notebooks
+- Added an option to customize the orchestrator and datastore ports
+- Added ParallelEnvironment as a default export from envs
+- Added a placeholder image for the web UI
+- Updated the uvicorn dependency to require the [standard] option
+- Fixed a breaking bug in ParallelEnv
+- Dropped openCV as a requirement
+- Fixed some type issues, ignore some spurious warnings
+
 ## v0.1.0 - 2024-01-17
 
 ### Added

cogment_lab/actors/nn_actor.py

@@ -78,7 +78,7 @@ async def act(self, observation: np.ndarray, rendered_frame=None) -> int:
             [act_vals] = self.network(obs)
             act_probs = F.softmax(act_vals / self.temperature, dim=0)
 
-            action = torch.multinomial(act_probs, 1).item()
+            action = int(torch.multinomial(act_probs, 1).item())
 
         return action
 

cogment_lab/core.py

@@ -256,14 +256,16 @@ async def impl(self, actor_session: ActorSession):
 
             if event.observation:
                 observation = self.session_helper.get_observation(event)
+                if observation is None:
+                    continue
                 logging.info(f"Got observation: {observation}")
 
                 if not observation.active:
                     action = None
                 elif not observation.alive:
                     action = None
                 else:
-                    action = await self.act(observation.value, observation.rendered_frame)
+                    action = await self.act(observation.value, observation.rendered_frame)  # type: ignore
                 logging.info(f"Got action: {action} with action_space: {self.action_space.gym_space}")
                 cog_action = self.action_space.create_serialize(action)
                 actor_session.do_action(cog_action)

cogment_lab/envs/__init__.py

@@ -13,4 +13,4 @@
 # limitations under the License.
 
 from cogment_lab.envs.gymnasium import GymEnvironment
-from cogment_lab.envs.pettingzoo import AECEnvironment
+from cogment_lab.envs.pettingzoo import AECEnvironment, ParallelEnvironment

cogment_lab/envs/conversions/teacher.py

@@ -60,7 +60,7 @@ def reset(self, seed: int | None = None, options: dict | None = None):
         self.infos = {"gym": info, "teacher": info}
         self._gym_action = None
 
-    def step(self, action):
+    def step(self, action: dict):
         current_agent = self.agent_selection
         next_agent = self._agent_selector.next()
 
@@ -110,10 +110,10 @@ def render(self):
             N = 5
 
             # Set the borders to red
-            img[:N, :, :] = [255, 0, 0]  # Top border
-            img[-N:, :, :] = [255, 0, 0]  # Bottom border
-            img[:, :N, :] = [255, 0, 0]  # Left border
-            img[:, -N:, :] = [255, 0, 0]  # Right border
+            img[:N, :, :] = [255, 0, 0]  # type: ignore
+            img[-N:, :, :] = [255, 0, 0]  # type: ignore
+            img[:, :N, :] = [255, 0, 0]  # type: ignore
+            img[:, -N:, :] = [255, 0, 0]  # type: ignore
         return img
 
     def close(self):
@@ -190,10 +190,10 @@ def render(self):
             N = 5
 
             # Set the borders to red
-            img[:N, :, :] = [255, 0, 0]  # Top border
-            img[-N:, :, :] = [255, 0, 0]  # Bottom border
-            img[:, :N, :] = [255, 0, 0]  # Left border
-            img[:, -N:, :] = [255, 0, 0]  # Right border
+            img[:N, :, :] = [255, 0, 0]  # type: ignore
+            img[-N:, :, :] = [255, 0, 0]  # type: ignore
+            img[:, :N, :] = [255, 0, 0]  # type: ignore
+            img[:, -N:, :] = [255, 0, 0]  # type: ignore
         return img
 
     def close(self):

cogment_lab/envs/gymnasium.py

@@ -94,8 +94,10 @@ def __init__(
 
         if isinstance(self.env_id, Callable):
             self.env_maker = self.env_id
+        elif isinstance(self.env_id, str):
+            self.env_maker = lambda **kwargs: gym.make(self.env_id, **kwargs)  # type: ignore
         else:
-            self.env_maker = lambda **kwargs: gym.make(self.env_id, **kwargs)
+            raise ValueError(f"env_id must be a string or a callable, got {self.env_id}")
 
         if self.registration:
             importlib.import_module(self.registration)

cogment_lab/envs/pettingzoo.py

@@ -21,7 +21,7 @@
 from pettingzoo import AECEnv, ParallelEnv
 
 from cogment_lab.core import CogmentEnv, State
-from cogment_lab.generated.data_pb2 import Observation as PbObservation
+from cogment_lab.generated.data_pb2 import Observation as PbObservation  # type: ignore
 from cogment_lab.session_helpers import EnvironmentSessionHelper
 from cogment_lab.specs import AgentSpecs
 from cogment_lab.utils import import_object
@@ -42,7 +42,7 @@ def __init__(
         self,
         env_path: str,
         make_kwargs: dict | None = None,
-        reset_options: dict = None,
+        reset_options: dict | None = None,
         render: bool = False,
         reinitialize: bool = False,
         dry: bool = False,
@@ -91,7 +91,7 @@ def __init__(
             self.env: AECEnv = self.env_maker(**self.make_args)
             self.agent_specs = self.create_agent_specs(self.env)
         else:
-            self.env = None
+            self.env = AECEnv()
             self.agent_specs = {}
 
         self.initialized = False
@@ -221,14 +221,15 @@ async def end(self, state: State):
 
     @staticmethod
     def fill_observations_(
-        state: State, observations: dict[str, PbObservation], frame: np.ndarray
+        state: State, observations: dict[str, PbObservation], frame: np.ndarray | None
     ) -> dict[str, PbObservation]:
         """
         Fill in any missing observations with the default observation. Mutates the observations dict.
 
         Args:
             state: The Cogment state.
             observations: The observations dict.
+            frame: The rendered frame.
 
         Returns:
             The filled observations dict.
@@ -292,7 +293,7 @@ def __init__(
         self,
         env_path: str,
         make_kwargs: dict | None = None,
-        reset_options: dict = None,
+        reset_options: dict | None = None,
         render: bool = False,
         reinitialize: bool = False,
         dry: bool = False,
@@ -341,7 +342,7 @@ def __init__(
             self.env: ParallelEnv = self.env_maker(**self.make_args)
             self.agent_specs = self.create_agent_specs(self.env)
         else:
-            self.env = None
+            self.env = ParallelEnv()
             self.agent_specs = {}
 
         self.initialized = False
@@ -365,10 +366,10 @@ async def initialize(self, state: State, environment_session: EnvironmentSession
             state.env = self.env
             state.agent_specs = self.agent_specs
         elif self.initialized and not self.reinitialize:
-            state.env: ParallelEnv = self.env
+            state.env = self.env  # type: ignore
             state.agent_specs = self.agent_specs
         elif self.reinitialize:
-            state.env: ParallelEnv = self.env_maker(**self.make_args)
+            state.env = self.env_maker(**self.make_args)  # type: ignore
             state.agent_specs = self.create_agent_specs(state.env)
 
         self.initialized = True
@@ -429,7 +430,6 @@ async def step(self, state: State, action: dict[str, Any]):
         """
         logging.info("Stepping environment")
 
-        state.env.step(action)
         obs, rewards, terminated, truncated, info = state.env.step(action)
 
         frame = state.env.render() if state.session_cfg.render else None

cogment_lab/humans/actor.py

@@ -39,9 +39,9 @@
 def image_to_msg(img: np.ndarray | None) -> str | None:
     if img is None:
         return None
-    img = Image.fromarray(img)
+    image = Image.fromarray(img)
     img_byte_array = io.BytesIO()
-    img.save(img_byte_array, format="PNG")  # type: ignore
+    image.save(img_byte_array, format="PNG")  # type: ignore
     base64_encoded_result_bytes = base64.b64encode(img_byte_array.getvalue())
     base64_encoded_result_str = base64_encoded_result_bytes.decode("ascii")
     return f"data:image/png;base64,{base64_encoded_result_str}"
@@ -157,11 +157,11 @@ def __init__(self, send_queue: asyncio.Queue, recv_queue: asyncio.Queue):
         self.recv_queue = recv_queue
 
     async def act(self, observation: Any, rendered_frame: np.ndarray | None = None) -> int:
-        logging.info(
-            f"Getting an action with {observation=}" + f" and {rendered_frame.shape=}"
-            if rendered_frame is not None
-            else "no frame"
-        )
+        # logging.info(
+        #     f"Getting an action with {observation=}" + f" and {rendered_frame.shape=}"
+        #     if rendered_frame is not None
+        #     else "no frame"
+        # )
         await self.send_queue.put(rendered_frame)
         action = await self.recv_queue.get()
         return action
@@ -187,30 +187,3 @@ async def run_cogment_actor(
     signal_queue.put(True)
 
     await serve
-
-
-async def shutdown():
-    tasks = [t for t in asyncio.all_tasks() if t is not asyncio.current_task()]
-    for task in tasks:
-        task.cancel()
-    await asyncio.gather(*tasks, return_exceptions=True)
-    asyncio.get_event_loop().stop()
-
-
-def signal_handler(sig, frame):
-    asyncio.create_task(shutdown())
-
-
-async def main(app_port: int = 8000, cogment_port: int = 8999):
-    app_to_actor = asyncio.Queue()
-    actor_to_app = asyncio.Queue()
-    fastapi_task = asyncio.create_task(start_fastapi(port=app_port, send_queue=app_to_actor, recv_queue=actor_to_app))
-    cogment_task = asyncio.create_task(
-        run_cogment_actor(port=cogment_port, send_queue=actor_to_app, recv_queue=app_to_actor)
-    )
-
-    await asyncio.gather(fastapi_task, cogment_task)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

cogment_lab/process_manager.py

@@ -21,11 +21,13 @@
 import multiprocessing as mp
 import os
 from asyncio import Task
-from collections.abc import Sequence
+from collections.abc import Callable, Coroutine, Sequence
 from multiprocessing import Process, Queue
-from typing import Any, Callable, Coroutine
+from typing import Any
 
 import cogment
+from cogment.control import Controller
+from cogment.datastore import Datastore
 
 from cogment_lab.actors.runner import actor_runner
 from cogment_lab.core import BaseActor, BaseEnv
@@ -39,13 +41,6 @@
 )
 
 
-ORCHESTRATOR_ENDPOINT = "grpc://localhost:9000"
-ENVIRONMENT_ENDPOINT = "grpc://localhost:9001"
-RANDOM_AGENT_ENDPOINT = "grpc://localhost:9002"
-HUMAN_AGENT_ENDPOINT = "grpc://localhost:8999"
-DATASTORE_ENDPOINT = "grpc://localhost:9003"
-
-
 AgentName = str
 ImplName = str
 TrialName = str
@@ -54,12 +49,17 @@
 class Cogment:
     """Main Cogment class for managing experiments"""
 
+    controller: Controller
+    datastore: Datastore
+
     def __init__(
         self,
         user_id: str = "cogment_lab",
         torch_mode: bool = False,
         log_dir: str | None = None,
         mp_method: str | None = None,
+        orchestrator_port: int = 9000,
+        datastore_port: int = 9003,
     ):
         """Initializes the Cogment instance
 
@@ -79,9 +79,20 @@ def __init__(
         self.envs: dict[ImplName, BaseEnv] = {}
         self.actors: dict[ImplName, BaseActor] = {}
 
+        self.orchestrator_endpoint = f"grpc://localhost:{orchestrator_port}"
+        self.datastore_endpoint = f"grpc://localhost:{datastore_port}"
+
         self.context = cogment.Context(cog_settings=cog_settings, user_id=user_id)
-        self.controller = self.context.get_controller(endpoint=cogment.Endpoint(ORCHESTRATOR_ENDPOINT))
-        self.datastore = self.context.get_datastore(endpoint=cogment.Endpoint(DATASTORE_ENDPOINT))
+        controller = self.context.get_controller(endpoint=cogment.Endpoint(self.orchestrator_endpoint))
+        datastore = self.context.get_datastore(endpoint=cogment.Endpoint(self.datastore_endpoint))
+
+        assert isinstance(
+            controller, Controller
+        ), "self.controller is not an instance of Controller. Please report this."
+        assert isinstance(datastore, Datastore), "self.datastore is not an instance of Datastore. Please report this."
+
+        self.controller = controller
+        self.datastore = datastore
 
         self.env_ports: dict[ImplName, int] = {}
         self.actor_ports: dict[ImplName, int] = {}
@@ -121,7 +132,7 @@ def _add_process(
 
             p = TorchProcess(target=target, args=args)
         else:
-            p = self.mp_ctx.Process(target=target, args=args)
+            p = self.mp_ctx.Process(target=target, args=args)  # type: ignore
         p.start()
         self.processes[name] = p
 
@@ -148,7 +159,7 @@ def run_env(
         env_name: ImplName,
         port: int = 9001,
         log_file: str | None = None,
-    ) -> Coroutine[bool]:
+    ) -> Coroutine[None, None, bool]:
         """Given an environment, runs it in a subprocess
 
         Args:
@@ -195,7 +206,7 @@ def run_actor(
         actor_name: ImplName,
         port: int = 9002,
         log_file: str | None = None,
-    ) -> Coroutine[bool]:
+    ) -> Coroutine[None, None, bool]:
         """Given an actor, runs it
 
         Args:
@@ -282,7 +293,7 @@ def run_web_ui(
         html_override: str | None = None,
         file_override: str | None = None,
         jinja_parameters: dict[str, Any] | None = None,
-    ) -> Coroutine[bool]:
+    ) -> Coroutine[None, None, bool]:
         """Runs the human actor in a separate process
 
         Args:
@@ -457,7 +468,7 @@ async def start_trial(
             for agent_name, actor_impl in actor_impls.items()
         ]
 
-        env_config = data_pb2.EnvironmentConfig(**session_config)
+        env_config = data_pb2.EnvironmentConfig(**session_config)  # type: ignore
 
         trial_params = cogment.TrialParameters(
             cog_settings,
@@ -466,7 +477,7 @@ async def start_trial(
             environment_config=env_config,
             actors=actor_params,
             environment_implementation=env_name,
-            datalog_endpoint=DATASTORE_ENDPOINT,
+            datalog_endpoint=self.datastore_endpoint,
         )
 
         trial_id = await self.controller.start_trial(trial_id_requested=trial_name, trial_params=trial_params)