Move RLSamplingConfig to separate module config, fixing cyclic import

examples/mujoco/mujoco_env.py

@@ -4,7 +4,7 @@ import gymnasium as gym
 
 from tianshou.env import ShmemVectorEnv, VectorEnvNormObs
 from tianshou.highlevel.env import ContinuousEnvironments, EnvFactory
-from tianshou.highlevel.experiment import RLSamplingConfig
+from tianshou.highlevel.config import RLSamplingConfig
 
 try:
     import envpool

examples/mujoco/mujoco_ppo_hl.py

@@ -13,8 +13,8 @@ from tianshou.highlevel.agent import PGConfig, PPOAgentFactory, PPOConfig, RLAge
 from tianshou.highlevel.experiment import (
     RLExperiment,
     RLExperimentConfig,
-    RLSamplingConfig,
 )
+from tianshou.highlevel.config import RLSamplingConfig
 from tianshou.highlevel.logger import DefaultLoggerFactory
 from tianshou.highlevel.module import (
     ContinuousActorProbFactory,

examples/mujoco/mujoco_sac_hl.py

@@ -11,8 +11,8 @@ from tianshou.highlevel.agent import DefaultAutoAlphaFactory, SACAgentFactory, S
 from tianshou.highlevel.experiment import (
     RLExperiment,
     RLExperimentConfig,
-    RLSamplingConfig,
 )
+from tianshou.highlevel.config import RLSamplingConfig
 from tianshou.highlevel.logger import DefaultLoggerFactory
 from tianshou.highlevel.module import (
     ContinuousActorProbFactory,

tianshou/highlevel/agent.py

@@ -10,7 +10,7 @@ import torch
 from tianshou.data import Collector, ReplayBuffer, VectorReplayBuffer
 from tianshou.exploration import BaseNoise
 from tianshou.highlevel.env import Environments
-from tianshou.highlevel.experiment import RLSamplingConfig
+from tianshou.highlevel.config import RLSamplingConfig
 from tianshou.highlevel.logger import Logger
 from tianshou.highlevel.module import ActorFactory, CriticFactory, TDevice
 from tianshou.highlevel.optim import LRSchedulerFactory, OptimizerFactory

tianshou/highlevel/config.py

@@ -0,0 +1,18 @@
+from dataclasses import dataclass
+
+
+@dataclass
+class RLSamplingConfig:
+    """Sampling, epochs, parallelization, buffers, collectors, and batching."""
+
+    num_epochs: int = 100
+    step_per_epoch: int = 30000
+    batch_size: int = 64
+    num_train_envs: int = 64
+    num_test_envs: int = 10
+    buffer_size: int = 4096
+    step_per_collect: int = 2048
+    repeat_per_collect: int = 10
+    update_per_step: int = 1
+    start_timesteps: int = 0
+    start_timesteps_random: bool = False

tianshou/highlevel/experiment.py

@@ -33,23 +33,6 @@ class RLExperimentConfig:
     watch_num_episodes = 10
 
 
-@dataclass
-class RLSamplingConfig:
-    """Sampling, epochs, parallelization, buffers, collectors, and batching."""
-
-    num_epochs: int = 100
-    step_per_epoch: int = 30000
-    batch_size: int = 64
-    num_train_envs: int = 64
-    num_test_envs: int = 10
-    buffer_size: int = 4096
-    step_per_collect: int = 2048
-    repeat_per_collect: int = 10
-    update_per_step: int = 1
-    start_timesteps: int = 0
-    start_timesteps_random: bool = False
-
-
 class RLExperiment(Generic[TPolicy, TTrainer]):
     def __init__(
         self,

tianshou/highlevel/optim.py

@@ -8,7 +8,7 @@ from torch import Tensor
 from torch.optim import Adam
 from torch.optim.lr_scheduler import LambdaLR, LRScheduler
 
-from tianshou.highlevel.experiment import RLSamplingConfig
+from tianshou.highlevel.config import RLSamplingConfig
 
 TParams = Iterable[Tensor] | Iterable[dict[str, Any]]