openrl.envs.wrappers package

Submodules

openrl.envs.wrappers.atari_wrappers module

class openrl.envs.wrappers.atari_wrappers.ClipRewardEnv(env)

Bases: gymnasium.core.Wrapper[gymnasium.core.ObsType, gymnasium.core.ActType, gymnasium.core.ObsType, gymnasium.core.ActType]

reward(reward)

Bin reward to {+1, 0, -1} by its sign.

class openrl.envs.wrappers.atari_wrappers.EpisodicLifeEnv(env)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

reset(**kwargs)

Reset only when lives are exhausted. This way all states are still reachable even though lives are episodic, and the learner need not know about any of this behind-the-scenes.

step(action)

Uses the step() of the env that can be overwritten to change the returned data.

class openrl.envs.wrappers.atari_wrappers.FireResetEnv(env)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

reset(**kwargs)

Uses the reset() of the env that can be overwritten to change the returned data.

class openrl.envs.wrappers.atari_wrappers.NoopResetEnv(env, noop_max=30)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

reset(**kwargs)

Do no-op action for a number of steps in [1, noop_max].

class openrl.envs.wrappers.atari_wrappers.WarpFrame(env, width=84, height=84)

Bases: gymnasium.core.Wrapper[gymnasium.core.WrapperObsType, gymnasium.core.ActType, gymnasium.core.ObsType, gymnasium.core.ActType]

observation(frame)

Returns a modified observation.

Args:

observation: The env observation

Returns:

The modified observation

openrl.envs.wrappers.base_wrapper module

class openrl.envs.wrappers.base_wrapper.BaseObservationWrapper(env)

Bases: gymnasium.core.Wrapper[gymnasium.core.WrapperObsType, gymnasium.core.ActType, gymnasium.core.ObsType, gymnasium.core.ActType]

class openrl.envs.wrappers.base_wrapper.BaseRewardWrapper(env)

Bases: gymnasium.core.Wrapper[gymnasium.core.ObsType, gymnasium.core.ActType, gymnasium.core.ObsType, gymnasium.core.ActType]

class openrl.envs.wrappers.base_wrapper.BaseWrapper(env, reward_class=None)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

property agent_num

property env_name

property has_auto_reset

step(action)

Uses the step() of the env that can be overwritten to change the returned data.

property use_monitor

openrl.envs.wrappers.extra_wrappers module

class openrl.envs.wrappers.extra_wrappers.AutoReset(env: gymnasium.core.Env)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

property has_auto_reset

class openrl.envs.wrappers.extra_wrappers.DictWrapper(env)

Bases: gymnasium.core.Wrapper[gymnasium.core.WrapperObsType, gymnasium.core.ActType, gymnasium.core.ObsType, gymnasium.core.ActType]

observation(observation)

Returns a modified observation.

Args:

observation: The env observation

Returns:

The modified observation

class openrl.envs.wrappers.extra_wrappers.GIFWrapper(env, gif_path: str)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

close()

Closes the wrapper and env.

reset(**kwargs)

Uses the reset() of the env that can be overwritten to change the returned data.

step(action)

Uses the step() of the env that can be overwritten to change the returned data.

class openrl.envs.wrappers.extra_wrappers.RecordReward(env, reward_class=None)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

property has_auto_reset

class openrl.envs.wrappers.extra_wrappers.RemoveTruncated(env: gymnasium.core.Env)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

openrl.envs.wrappers.image_wrappers module

class openrl.envs.wrappers.image_wrappers.TransposeImage(env=None, op=[2, 0, 1])

Bases: gymnasium.core.Wrapper[gymnasium.core.WrapperObsType, gymnasium.core.ActType, gymnasium.core.ObsType, gymnasium.core.ActType]

observation(ob)

Returns a modified observation.

Args:

observation: The env observation

Returns:

The modified observation

openrl.envs.wrappers.mat_wrapper module

class openrl.envs.wrappers.mat_wrapper.MATWrapper(env: openrl.envs.vec_env.base_venv.BaseVecEnv)

Bases: openrl.envs.vec_env.wrappers.base_wrapper.VectorObservationWrapper

observation(observation)

Defines the observation transformation.

Args:

observation (object): the observation from the environment

Returns:

observation (object): the transformed observation

property observation_space

Return the Env observation_space unless overwritten then the wrapper observation_space is used.

openrl.envs.wrappers.monitor module

class openrl.envs.wrappers.monitor.Monitor(env)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

A monitor wrapper for Gym environments, it is used to know the episode reward, length, time and other data.

Parameters

env – The environment

get_episode_lengths() → List[int]

Returns the number of timesteps of all the episodes

Returns

get_episode_rewards() → List[float]

Returns the rewards of all the episodes

Returns

get_episode_times() → List[float]

Returns the runtime in seconds of all the episodes

Returns

get_total_steps() → int

Returns the total number of timesteps

Returns

reset(**kwargs)

Calls the Gym environment reset.

Parameters

kwargs – Extra keywords saved for the next episode. only if defined by reset_keywords

Returns

the first observation of the environment

step(action: Union[numpy.ndarray, int])

Step the environment with the given action

Parameters

action – the action

Returns

observation, reward, done, information or observation, reward, terminal, truncated, information

openrl.envs.wrappers.multiagent_wrapper module

class openrl.envs.wrappers.multiagent_wrapper.Single2MultiAgentWrapper(env)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

property agent_num

reset(*, seed=None, options=None)

Uses the reset() of the env that can be overwritten to change the returned data.

step(action)

Uses the step() of the env that can be overwritten to change the returned data.

openrl.envs.wrappers.util module

openrl.envs.wrappers.util.is_wrapped(env: gymnasium.core.Env, wrapper_class: Type[openrl.envs.wrappers.base_wrapper.BaseWrapper]) → bool

Check if a given environment has been wrapped with a given wrapper.

Parameters

• env – Environment to check

• wrapper_class – Wrapper class to look for

Returns

True if environment has been wrapped with wrapper_class.

openrl.envs.wrappers.util.nest_expand_dim(input: Any) → Any

openrl.envs.wrappers.util.unwrap_wrapper(env: gymnasium.core.Env, wrapper_class: Type[openrl.envs.wrappers.base_wrapper.BaseWrapper]) → Optional[openrl.envs.wrappers.base_wrapper.BaseWrapper]

Retrieve a BaseWrapper object by recursively searching.

Parameters

• env – Environment to unwrap

• wrapper_class – Wrapper to look for

Returns

Environment unwrapped till wrapper_class if it has been wrapped with it

Module contents

class openrl.envs.wrappers.AutoReset(env: gymnasium.core.Env)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

property has_auto_reset

class openrl.envs.wrappers.BaseObservationWrapper(env)

Bases: gymnasium.core.Wrapper[gymnasium.core.WrapperObsType, gymnasium.core.ActType, gymnasium.core.ObsType, gymnasium.core.ActType]

class openrl.envs.wrappers.BaseWrapper(env, reward_class=None)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

property agent_num

property env_name

property has_auto_reset

step(action)

Uses the step() of the env that can be overwritten to change the returned data.

property use_monitor

class openrl.envs.wrappers.DictWrapper(env)

Bases: gymnasium.core.Wrapper[gymnasium.core.WrapperObsType, gymnasium.core.ActType, gymnasium.core.ObsType, gymnasium.core.ActType]

observation(observation)

Returns a modified observation.

Args:

observation: The env observation

Returns:

The modified observation

class openrl.envs.wrappers.GIFWrapper(env, gif_path: str)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

close()

Closes the wrapper and env.

reset(**kwargs)

Uses the reset() of the env that can be overwritten to change the returned data.

step(action)

Uses the step() of the env that can be overwritten to change the returned data.

class openrl.envs.wrappers.RemoveTruncated(env: gymnasium.core.Env)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

class openrl.envs.wrappers.Single2MultiAgentWrapper(env)

Bases: gymnasium.core.Env[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType], Generic[gymnasium.core.WrapperObsType, gymnasium.core.WrapperActType, gymnasium.core.ObsType, gymnasium.core.ActType]

property agent_num

reset(*, seed=None, options=None)

Uses the reset() of the env that can be overwritten to change the returned data.

step(action)

Uses the step() of the env that can be overwritten to change the returned data.