Remove 'RL' prefix from class names

examples/atari/atari_dqn_hl.py

@@ -10,10 +10,10 @@ from examples.atari.atari_network import (
     FeatureNetFactoryDQN,
 )
 from examples.atari.atari_wrapper import AtariEnvFactory, AtariStopCallback
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.experiment import (
     DQNExperimentBuilder,
-    RLExperimentConfig,
+    ExperimentConfig,
 )
 from tianshou.highlevel.params.policy_params import DQNParams
 from tianshou.highlevel.params.policy_wrapper import (
@@ -25,7 +25,7 @@ from tianshou.utils import logging
 
 
 def main(
-    experiment_config: RLExperimentConfig,
+    experiment_config: ExperimentConfig,
     task: str = "PongNoFrameskip-v4",
     scale_obs: int = 0,
     eps_test: float = 0.005,
@@ -52,7 +52,7 @@ def main(
     now = datetime.datetime.now().strftime("%y%m%d-%H%M%S")
     log_name = os.path.join(task, "ppo", str(experiment_config.seed), now)
 
-    sampling_config = RLSamplingConfig(
+    sampling_config = SamplingConfig(
         num_epochs=epoch,
         step_per_epoch=step_per_epoch,
         batch_size=batch_size,

examples/atari/atari_ppo_hl.py

@@ -11,10 +11,10 @@ from examples.atari.atari_network import (
     FeatureNetFactoryDQN,
 )
 from examples.atari.atari_wrapper import AtariEnvFactory, AtariStopCallback
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.experiment import (
     PPOExperimentBuilder,
-    RLExperimentConfig,
+    ExperimentConfig,
 )
 from tianshou.highlevel.params.lr_scheduler import LRSchedulerFactoryLinear
 from tianshou.highlevel.params.policy_params import PPOParams
@@ -25,7 +25,7 @@ from tianshou.utils import logging
 
 
 def main(
-    experiment_config: RLExperimentConfig,
+    experiment_config: ExperimentConfig,
     task: str = "PongNoFrameskip-v4",
     scale_obs: bool = True,
     buffer_size: int = 100000,
@@ -59,7 +59,7 @@ def main(
     now = datetime.datetime.now().strftime("%y%m%d-%H%M%S")
     log_name = os.path.join(task, "ppo", str(experiment_config.seed), now)
 
-    sampling_config = RLSamplingConfig(
+    sampling_config = SamplingConfig(
         num_epochs=epoch,
         step_per_epoch=step_per_epoch,
         batch_size=batch_size,

examples/atari/atari_wrapper.py

@@ -9,7 +9,7 @@ import gymnasium as gym
 import numpy as np
 
 from tianshou.env import ShmemVectorEnv
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.env import DiscreteEnvironments, EnvFactory
 from tianshou.highlevel.trainer import TrainerStopCallback, TrainingContext
 
@@ -379,7 +379,7 @@ class AtariEnvFactory(EnvFactory):
         self,
         task: str,
         seed: int,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
         frame_stack: int,
         scale: int = 0,
     ):

examples/mujoco/mujoco_a2c_hl.py

@@ -8,10 +8,10 @@ from typing import Literal
 from jsonargparse import CLI
 
 from examples.mujoco.mujoco_env import MujocoEnvFactory
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.experiment import (
     A2CExperimentBuilder,
-    RLExperimentConfig,
+    ExperimentConfig,
 )
 from tianshou.highlevel.optim import OptimizerFactoryRMSprop
 from tianshou.highlevel.params.lr_scheduler import LRSchedulerFactoryLinear
@@ -20,7 +20,7 @@ from tianshou.utils import logging
 
 
 def main(
-    experiment_config: RLExperimentConfig,
+    experiment_config: ExperimentConfig,
     task: str = "Ant-v3",
     buffer_size: int = 4096,
     hidden_sizes: Sequence[int] = (64, 64),
@@ -44,7 +44,7 @@ def main(
     now = datetime.datetime.now().strftime("%y%m%d-%H%M%S")
     log_name = os.path.join(task, "ppo", str(experiment_config.seed), now)
 
-    sampling_config = RLSamplingConfig(
+    sampling_config = SamplingConfig(
         num_epochs=epoch,
         step_per_epoch=step_per_epoch,
         batch_size=batch_size,

examples/mujoco/mujoco_ddpg_hl.py

@@ -7,10 +7,10 @@ from collections.abc import Sequence
 from jsonargparse import CLI
 
 from examples.mujoco.mujoco_env import MujocoEnvFactory
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.experiment import (
     DDPGExperimentBuilder,
-    RLExperimentConfig,
+    ExperimentConfig,
 )
 from tianshou.highlevel.params.noise import MaxActionScaledGaussian
 from tianshou.highlevel.params.policy_params import DDPGParams
@@ -18,7 +18,7 @@ from tianshou.utils import logging
 
 
 def main(
-    experiment_config: RLExperimentConfig,
+    experiment_config: ExperimentConfig,
     task: str = "Ant-v3",
     buffer_size: int = 1000000,
     hidden_sizes: Sequence[int] = (256, 256),
@@ -40,7 +40,7 @@ def main(
     now = datetime.datetime.now().strftime("%y%m%d-%H%M%S")
     log_name = os.path.join(task, "ppo", str(experiment_config.seed), now)
 
-    sampling_config = RLSamplingConfig(
+    sampling_config = SamplingConfig(
         num_epochs=epoch,
         step_per_epoch=step_per_epoch,
         batch_size=batch_size,

examples/mujoco/mujoco_env.py

@@ -3,7 +3,7 @@ import warnings
 import gymnasium as gym
 
 from tianshou.env import ShmemVectorEnv, VectorEnvNormObs
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.env import ContinuousEnvironments, EnvFactory
 
 try:
@@ -41,7 +41,7 @@ def make_mujoco_env(task: str, seed: int, num_train_envs: int, num_test_envs: in
 
 
 class MujocoEnvFactory(EnvFactory):
-    def __init__(self, task: str, seed: int, sampling_config: RLSamplingConfig):
+    def __init__(self, task: str, seed: int, sampling_config: SamplingConfig):
         self.task = task
         self.sampling_config = sampling_config
         self.seed = seed

examples/mujoco/mujoco_ppo_hl.py

@@ -9,10 +9,10 @@ from jsonargparse import CLI
 from torch.distributions import Independent, Normal
 
 from examples.mujoco.mujoco_env import MujocoEnvFactory
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.experiment import (
     PPOExperimentBuilder,
-    RLExperimentConfig,
+    ExperimentConfig,
 )
 from tianshou.highlevel.params.lr_scheduler import LRSchedulerFactoryLinear
 from tianshou.highlevel.params.policy_params import PPOParams
@@ -20,7 +20,7 @@ from tianshou.utils import logging
 
 
 def main(
-    experiment_config: RLExperimentConfig,
+    experiment_config: ExperimentConfig,
     task: str = "Ant-v4",
     buffer_size: int = 4096,
     hidden_sizes: Sequence[int] = (64, 64),
@@ -49,7 +49,7 @@ def main(
     now = datetime.datetime.now().strftime("%y%m%d-%H%M%S")
     log_name = os.path.join(task, "ppo", str(experiment_config.seed), now)
 
-    sampling_config = RLSamplingConfig(
+    sampling_config = SamplingConfig(
         num_epochs=epoch,
         step_per_epoch=step_per_epoch,
         batch_size=batch_size,

examples/mujoco/mujoco_sac_hl.py

@@ -7,9 +7,9 @@ from collections.abc import Sequence
 from jsonargparse import CLI
 
 from examples.mujoco.mujoco_env import MujocoEnvFactory
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.experiment import (
-    RLExperimentConfig,
+    ExperimentConfig,
     SACExperimentBuilder,
 )
 from tianshou.highlevel.params.alpha import AutoAlphaFactoryDefault
@@ -18,7 +18,7 @@ from tianshou.utils import logging
 
 
 def main(
-    experiment_config: RLExperimentConfig,
+    experiment_config: ExperimentConfig,
     task: str = "Ant-v3",
     buffer_size: int = 1000000,
     hidden_sizes: Sequence[int] = (256, 256),
@@ -42,7 +42,7 @@ def main(
     now = datetime.datetime.now().strftime("%y%m%d-%H%M%S")
     log_name = os.path.join(task, "sac", str(experiment_config.seed), now)
 
-    sampling_config = RLSamplingConfig(
+    sampling_config = SamplingConfig(
         num_epochs=epoch,
         step_per_epoch=step_per_epoch,
         num_train_envs=training_num,

examples/mujoco/mujoco_td3_hl.py

@@ -7,9 +7,9 @@ from collections.abc import Sequence
 from jsonargparse import CLI
 
 from examples.mujoco.mujoco_env import MujocoEnvFactory
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.experiment import (
-    RLExperimentConfig,
+    ExperimentConfig,
     TD3ExperimentBuilder,
 )
 from tianshou.highlevel.params.env_param import MaxActionScaled
@@ -21,7 +21,7 @@ from tianshou.utils import logging
 
 
 def main(
-    experiment_config: RLExperimentConfig,
+    experiment_config: ExperimentConfig,
     task: str = "Ant-v3",
     buffer_size: int = 1000000,
     hidden_sizes: Sequence[int] = (256, 256),
@@ -46,7 +46,7 @@ def main(
     now = datetime.datetime.now().strftime("%y%m%d-%H%M%S")
     log_name = os.path.join(task, "td3", str(experiment_config.seed), now)
 
-    sampling_config = RLSamplingConfig(
+    sampling_config = SamplingConfig(
         num_epochs=epoch,
         step_per_epoch=step_per_epoch,
         num_train_envs=training_num,

test/highlevel/test_continuous.py

@@ -2,12 +2,12 @@ from test.highlevel.env_factory import ContinuousTestEnvFactory
 
 import pytest
 
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.experiment import (
     A2CExperimentBuilder,
     DDPGExperimentBuilder,
     PPOExperimentBuilder,
-    RLExperimentConfig,
+    ExperimentConfig,
     SACExperimentBuilder,
     TD3ExperimentBuilder,
 )
@@ -25,8 +25,8 @@ from tianshou.highlevel.experiment import (
 )
 def test_experiment_builder_continuous_default_params(builder_cls):
     env_factory = ContinuousTestEnvFactory()
-    sampling_config = RLSamplingConfig(num_epochs=1, step_per_epoch=100)
+    sampling_config = SamplingConfig(num_epochs=1, step_per_epoch=100)
-    experiment_config = RLExperimentConfig()
+    experiment_config = ExperimentConfig()
     builder = builder_cls(
         experiment_config=experiment_config,
         env_factory=env_factory,

test/highlevel/test_discrete.py

@@ -2,12 +2,12 @@ from test.highlevel.env_factory import DiscreteTestEnvFactory
 
 import pytest
 
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.experiment import (
     A2CExperimentBuilder,
     DQNExperimentBuilder,
     PPOExperimentBuilder,
-    RLExperimentConfig,
+    ExperimentConfig,
 )
 
 
@@ -17,9 +17,9 @@ from tianshou.highlevel.experiment import (
 )
 def test_experiment_builder_discrete_default_params(builder_cls):
     env_factory = DiscreteTestEnvFactory()
-    sampling_config = RLSamplingConfig(num_epochs=1, step_per_epoch=100)
+    sampling_config = SamplingConfig(num_epochs=1, step_per_epoch=100)
     builder = builder_cls(
-        experiment_config=RLExperimentConfig(),
+        experiment_config=ExperimentConfig(),
         env_factory=env_factory,
         sampling_config=sampling_config,
     )

tianshou/highlevel/agent.py

@@ -6,7 +6,7 @@ import gymnasium
 import torch
 
 from tianshou.data import Collector, ReplayBuffer, VectorReplayBuffer
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.env import Environments
 from tianshou.highlevel.logger import Logger
 from tianshou.highlevel.module.actor import (
@@ -54,7 +54,7 @@ TPolicy = TypeVar("TPolicy", bound=BasePolicy)
 
 
 class AgentFactory(ABC, ToStringMixin):
-    def __init__(self, sampling_config: RLSamplingConfig, optim_factory: OptimizerFactory):
+    def __init__(self, sampling_config: SamplingConfig, optim_factory: OptimizerFactory):
         self.sampling_config = sampling_config
         self.optim_factory = optim_factory
         self.policy_wrapper_factory: PolicyWrapperFactory | None = None
@@ -352,7 +352,7 @@ class ActorCriticAgentFactory(
     def __init__(
         self,
         params: TParams,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
         actor_factory: ActorFactory,
         critic_factory: CriticFactory,
         optimizer_factory: OptimizerFactory,
@@ -399,7 +399,7 @@ class A2CAgentFactory(ActorCriticAgentFactory[A2CParams, A2CPolicy]):
     def __init__(
         self,
         params: A2CParams,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
         actor_factory: ActorFactory,
         critic_factory: CriticFactory,
         optimizer_factory: OptimizerFactory,
@@ -423,7 +423,7 @@ class PPOAgentFactory(ActorCriticAgentFactory[PPOParams, PPOPolicy]):
     def __init__(
         self,
         params: PPOParams,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
         actor_factory: ActorFactory,
         critic_factory: CriticFactory,
         optimizer_factory: OptimizerFactory,
@@ -447,7 +447,7 @@ class DQNAgentFactory(OffpolicyAgentFactory):
     def __init__(
         self,
         params: DQNParams,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
         actor_factory: ActorFactory,
         optim_factory: OptimizerFactory,
     ):
@@ -483,7 +483,7 @@ class DDPGAgentFactory(OffpolicyAgentFactory, _ActorAndCriticMixin):
     def __init__(
         self,
         params: DDPGParams,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
         actor_factory: ActorFactory,
         critic_factory: CriticFactory,
         optim_factory: OptimizerFactory,
@@ -526,7 +526,7 @@ class SACAgentFactory(OffpolicyAgentFactory, _ActorAndDualCriticsMixin):
     def __init__(
         self,
         params: SACParams,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
         actor_factory: ActorFactory,
         critic1_factory: CriticFactory,
         critic2_factory: CriticFactory,
@@ -575,7 +575,7 @@ class TD3AgentFactory(OffpolicyAgentFactory, _ActorAndDualCriticsMixin):
     def __init__(
         self,
         params: TD3Params,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
         actor_factory: ActorFactory,
         critic1_factory: CriticFactory,
         critic2_factory: CriticFactory,

tianshou/highlevel/config.py

@@ -2,7 +2,7 @@ from dataclasses import dataclass
 
 
 @dataclass
-class RLSamplingConfig:
+class SamplingConfig:
     """Sampling, epochs, parallelization, buffers, collectors, and batching."""
 
     # TODO: What are reasonable defaults?

tianshou/highlevel/experiment.py

@@ -18,7 +18,7 @@ from tianshou.highlevel.agent import (
     SACAgentFactory,
     TD3AgentFactory,
 )
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.highlevel.env import EnvFactory, Environments
 from tianshou.highlevel.logger import DefaultLoggerFactory, LoggerFactory
 from tianshou.highlevel.module.actor import (
@@ -53,7 +53,7 @@ TTrainer = TypeVar("TTrainer", bound=BaseTrainer)
 
 
 @dataclass
-class RLExperimentConfig:
+class ExperimentConfig:
     """Generic config for setting up the experiment, not RL or training specific."""
 
     seed: int = 42
@@ -69,10 +69,10 @@ class RLExperimentConfig:
     watch_num_episodes = 10
 
 
-class RLExperiment(Generic[TPolicy, TTrainer], ToStringMixin):
+class Experiment(Generic[TPolicy, TTrainer], ToStringMixin):
     def __init__(
         self,
-        config: RLExperimentConfig,
+        config: ExperimentConfig,
         env_factory: EnvFactory | Callable[[PersistableConfigProtocol | None], Environments],
         agent_factory: AgentFactory,
         logger_factory: LoggerFactory | None = None,
@@ -153,12 +153,12 @@ class RLExperiment(Generic[TPolicy, TTrainer], ToStringMixin):
 TBuilder = TypeVar("TBuilder", bound="RLExperimentBuilder")
 
 
-class RLExperimentBuilder:
+class ExperimentBuilder:
     def __init__(
         self,
-        experiment_config: RLExperimentConfig,
+        experiment_config: ExperimentConfig,
         env_factory: EnvFactory,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
     ):
         self._config = experiment_config
         self._env_factory = env_factory
@@ -223,12 +223,12 @@ class RLExperimentBuilder:
         else:
             return self._optim_factory
 
-    def build(self) -> RLExperiment:
+    def build(self) -> Experiment:
         agent_factory = self._create_agent_factory()
         agent_factory.set_trainer_callbacks(self._trainer_callbacks)
         if self._policy_wrapper_factory:
             agent_factory.set_policy_wrapper_factory(self._policy_wrapper_factory)
-        experiment = RLExperiment(
+        experiment = Experiment(
             self._config,
             self._env_factory,
             agent_factory,
@@ -394,15 +394,15 @@ class _BuilderMixinDualCriticFactory(_BuilderMixinCriticsFactory):
 
 
 class A2CExperimentBuilder(
-    RLExperimentBuilder,
+    ExperimentBuilder,
     _BuilderMixinActorFactory_ContinuousGaussian,
     _BuilderMixinSingleCriticCanUseActorFactory,
 ):
     def __init__(
         self,
-        experiment_config: RLExperimentConfig,
+        experiment_config: ExperimentConfig,
         env_factory: EnvFactory,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
         env_config: PersistableConfigProtocol | None = None,
     ):
         super().__init__(experiment_config, env_factory, sampling_config)
@@ -428,15 +428,15 @@ class A2CExperimentBuilder(
 
 
 class PPOExperimentBuilder(
-    RLExperimentBuilder,
+    ExperimentBuilder,
     _BuilderMixinActorFactory_ContinuousGaussian,
     _BuilderMixinSingleCriticCanUseActorFactory,
 ):
     def __init__(
         self,
-        experiment_config: RLExperimentConfig,
+        experiment_config: ExperimentConfig,
         env_factory: EnvFactory,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
     ):
         super().__init__(experiment_config, env_factory, sampling_config)
         _BuilderMixinActorFactory_ContinuousGaussian.__init__(self)
@@ -460,14 +460,14 @@ class PPOExperimentBuilder(
 
 
 class DQNExperimentBuilder(
-    RLExperimentBuilder,
+    ExperimentBuilder,
     _BuilderMixinActorFactory,
 ):
     def __init__(
         self,
-        experiment_config: RLExperimentConfig,
+        experiment_config: ExperimentConfig,
         env_factory: EnvFactory,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
     ):
         super().__init__(experiment_config, env_factory, sampling_config)
         _BuilderMixinActorFactory.__init__(self, ContinuousActorType.UNSUPPORTED)
@@ -488,15 +488,15 @@ class DQNExperimentBuilder(
 
 
 class DDPGExperimentBuilder(
-    RLExperimentBuilder,
+    ExperimentBuilder,
     _BuilderMixinActorFactory_ContinuousDeterministic,
     _BuilderMixinSingleCriticCanUseActorFactory,
 ):
     def __init__(
         self,
-        experiment_config: RLExperimentConfig,
+        experiment_config: ExperimentConfig,
         env_factory: EnvFactory,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
     ):
         super().__init__(experiment_config, env_factory, sampling_config)
         _BuilderMixinActorFactory_ContinuousDeterministic.__init__(self)
@@ -519,15 +519,15 @@ class DDPGExperimentBuilder(
 
 
 class SACExperimentBuilder(
-    RLExperimentBuilder,
+    ExperimentBuilder,
     _BuilderMixinActorFactory_ContinuousGaussian,
     _BuilderMixinDualCriticFactory,
 ):
     def __init__(
         self,
-        experiment_config: RLExperimentConfig,
+        experiment_config: ExperimentConfig,
         env_factory: EnvFactory,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
     ):
         super().__init__(experiment_config, env_factory, sampling_config)
         _BuilderMixinActorFactory_ContinuousGaussian.__init__(self)
@@ -550,15 +550,15 @@ class SACExperimentBuilder(
 
 
 class TD3ExperimentBuilder(
-    RLExperimentBuilder,
+    ExperimentBuilder,
     _BuilderMixinActorFactory_ContinuousDeterministic,
     _BuilderMixinDualCriticFactory,
 ):
     def __init__(
         self,
-        experiment_config: RLExperimentConfig,
+        experiment_config: ExperimentConfig,
         env_factory: EnvFactory,
-        sampling_config: RLSamplingConfig,
+        sampling_config: SamplingConfig,
     ):
         super().__init__(experiment_config, env_factory, sampling_config)
         _BuilderMixinActorFactory_ContinuousDeterministic.__init__(self)

tianshou/highlevel/params/lr_scheduler.py

@@ -4,7 +4,7 @@ import numpy as np
 import torch
 from torch.optim.lr_scheduler import LambdaLR, LRScheduler
 
-from tianshou.highlevel.config import RLSamplingConfig
+from tianshou.highlevel.config import SamplingConfig
 from tianshou.utils.string import ToStringMixin
 
 
@@ -15,7 +15,7 @@ class LRSchedulerFactory(ToStringMixin, ABC):
 
 
 class LRSchedulerFactoryLinear(LRSchedulerFactory):
-    def __init__(self, sampling_config: RLSamplingConfig):
+    def __init__(self, sampling_config: SamplingConfig):
         self.sampling_config = sampling_config
 
     def create_scheduler(self, optim: torch.optim.Optimizer) -> LRScheduler: