Feat/refactor collector (#1063)

Closes: #1058 

### Api Extensions
- Batch received two new methods: `to_dict` and `to_list_of_dicts`.
#1063
- `Collector`s can now be closed, and their reset is more granular.
#1063
- Trainers can control whether collectors should be reset prior to
training. #1063
- Convenience constructor for `CollectStats` called
`with_autogenerated_stats`. #1063

### Internal Improvements
- `Collector`s rely less on state, the few stateful things are stored
explicitly instead of through a `.data` attribute. #1063
- Introduced a first iteration of a naming convention for vars in
`Collector`s. #1063
- Generally improved readability of Collector code and associated tests
(still quite some way to go). #1063
- Improved typing for `exploration_noise` and within Collector. #1063

### Breaking Changes

- Removed `.data` attribute from `Collector` and its child classes.
#1063
- Collectors no longer reset the environment on initialization. Instead,
the user might have to call `reset`
expicitly or pass `reset_before_collect=True` . #1063
- VectorEnvs now return an array of info-dicts on reset instead of a
list. #1063
- Fixed `iter(Batch(...)` which now behaves the same way as
`Batch(...).__iter__()`. Can be considered a bugfix. #1063

---------

Co-authored-by: Michael Panchenko <[email protected]>

CHANGELOG.md

@@ -1,4 +1,27 @@
 # Changelog
 
+## Release 1.1.0
+
+### Api Extensions
+- Batch received two new methods: `to_dict` and `to_list_of_dicts`. #1063
+- `Collector`s can now be closed, and their reset is more granular. #1063
+- Trainers can control whether collectors should be reset prior to training. #1063
+- Convenience constructor for `CollectStats` called `with_autogenerated_stats`. #1063
+
+### Internal Improvements
+- `Collector`s rely less on state, the few stateful things are stored explicitly instead of through a `.data` attribute. #1063
+- Introduced a first iteration of a naming convention for vars in `Collector`s. #1063
+- Generally improved readability of Collector code and associated tests (still quite some way to go). #1063
+- Improved typing for `exploration_noise` and within Collector. #1063
+
+### Breaking Changes
+
+- Removed `.data` attribute from `Collector` and its child classes. #1063
+- Collectors no longer reset the environment on initialization. Instead, the user might have to call `reset` 
+expicitly or pass `reset_before_collect=True` . #1063
+- VectorEnvs now return an array of info-dicts on reset instead of a list. #1063
+- Fixed `iter(Batch(...)` which now behaves the same way as `Batch(...).__iter__()`. Can be considered a bugfix. #1063
+
+
 Started after v1.0.0
 

docs/02_notebooks/L0_overview.ipynb

@@ -164,7 +164,7 @@
    "source": [
     "# Let's watch its performance!\n",
     "policy.eval()\n",
-    "eval_result = test_collector.collect(n_episode=1, render=False)\n",
+    "eval_result = test_collector.collect(n_episode=3, render=False)\n",
     "print(f\"Final reward: {eval_result.returns.mean()}, length: {eval_result.lens.mean()}\")"
    ]
   },

docs/02_notebooks/L5_Collector.ipynb

@@ -119,7 +119,7 @@
    },
    "outputs": [],
    "source": [
-    "collect_result = test_collector.collect(n_episode=9)\n",
+    "collect_result = test_collector.collect(reset_before_collect=True, n_episode=9)\n",
     "\n",
     "collect_result.pprint_asdict()"
    ]
@@ -146,8 +146,7 @@
    "outputs": [],
    "source": [
     "# Reset the collector\n",
-    "test_collector.reset()\n",
-    "collect_result = test_collector.collect(n_episode=9, random=True)\n",
+    "collect_result = test_collector.collect(reset_before_collect=True, n_episode=9, random=True)\n",
     "\n",
     "collect_result.pprint_asdict()"
    ]

pyproject.toml

@@ -166,6 +166,7 @@ ignore = [
     "RET505",
     "D106", # undocumented public nested class
     "D205", # blank line after summary (prevents summary-only docstrings, which makes no sense)
+    "PLW2901", # overwrite vars in loop
 ]
 unfixable = [
     "F841", # unused variable. ruff keeps the call, but mostly we want to get rid of it all

test/base/env.py

@@ -9,13 +9,24 @@
 from gymnasium.spaces import Box, Dict, Discrete, MultiDiscrete, Space, Tuple
 
 
-class MyTestEnv(gym.Env):
-    """A task for "going right". The task is to go right ``size`` steps."""
+class MoveToRightEnv(gym.Env):
+    """A task for "going right". The task is to go right ``size`` steps.
+
+    The observation is the current index, and the action is to go left or right.
+    Action 0 is to go left, and action 1 is to go right.
+    Taking action 0 at index 0 will keep the index at 0.
+    Arriving at index ``size`` means the task is done.
+    In the current implementation, stepping after the task is done is possible, which will
+    lead the index to be larger than ``size``.
+
+    Index 0 is the starting point. If reset is called with default options, the index will
+    be reset to 0.
+    """
 
     def __init__(
         self,
         size: int,
-        sleep: int = 0,
+        sleep: float = 0.0,
         dict_state: bool = False,
         recurse_state: bool = False,
         ma_rew: int = 0,
@@ -74,8 +85,13 @@ def __init__(
     def reset(
         self,
         seed: int | None = None,
+        # TODO: passing a dict here doesn't make any sense
         options: dict[str, Any] | None = None,
     ) -> tuple[dict[str, Any] | np.ndarray, dict]:
+        """:param seed:
+        :param options: the start index is provided in options["state"]
+        :return:
+        """
         if options is None:
             options = {"state": 0}
         super().reset(seed=seed)
@@ -188,7 +204,7 @@ def step(
         return self._encode_obs(), 1.0, False, False, {}
 
 
-class MyGoalEnv(MyTestEnv):
+class MyGoalEnv(MoveToRightEnv):
     def __init__(self, *args: Any, **kwargs: Any) -> None:
         assert (
             kwargs.get("dict_state", 0) + kwargs.get("recurse_state", 0) == 0

test/base/test_buffer.py

@@ -22,13 +22,13 @@
 from tianshou.data.utils.converter import to_hdf5
 
 if __name__ == "__main__":
-    from env import MyGoalEnv, MyTestEnv
+    from env import MoveToRightEnv, MyGoalEnv
 else:  # pytest
-    from test.base.env import MyGoalEnv, MyTestEnv
+    from test.base.env import MoveToRightEnv, MyGoalEnv
 
 
 def test_replaybuffer(size=10, bufsize=20) -> None:
-    env = MyTestEnv(size)
+    env = MoveToRightEnv(size)
     buf = ReplayBuffer(bufsize)
     buf.update(buf)
     assert str(buf) == buf.__class__.__name__ + "()"
@@ -209,7 +209,7 @@ def test_ignore_obs_next(size=10) -> None:
 
 
 def test_stack(size=5, bufsize=9, stack_num=4, cached_num=3) -> None:
-    env = MyTestEnv(size)
+    env = MoveToRightEnv(size)
     buf = ReplayBuffer(bufsize, stack_num=stack_num)
     buf2 = ReplayBuffer(bufsize, stack_num=stack_num, sample_avail=True)
     buf3 = ReplayBuffer(bufsize, stack_num=stack_num, save_only_last_obs=True)
@@ -280,7 +280,7 @@ def test_stack(size=5, bufsize=9, stack_num=4, cached_num=3) -> None:
 
 
 def test_priortized_replaybuffer(size=32, bufsize=15) -> None:
-    env = MyTestEnv(size)
+    env = MoveToRightEnv(size)
     buf = PrioritizedReplayBuffer(bufsize, 0.5, 0.5)
     buf2 = PrioritizedVectorReplayBuffer(bufsize, buffer_num=3, alpha=0.5, beta=0.5)
     obs, info = env.reset()
@@ -1028,7 +1028,7 @@ def test_multibuf_stack() -> None:
     bufsize = 9
     stack_num = 4
     cached_num = 3
-    env = MyTestEnv(size)
+    env = MoveToRightEnv(size)
     # test if CachedReplayBuffer can handle stack_num + ignore_obs_next
     buf4 = CachedReplayBuffer(
         ReplayBuffer(bufsize, stack_num=stack_num, ignore_obs_next=True),