Environments¶
EnvironmentInfo¶
- class nnabla_rl.environments.environment_info.EnvironmentInfo(observation_space: gym.spaces.space.Space, action_space: gym.spaces.space.Space, max_episode_steps: int)[source]¶
Environment Information class
This class contains the basic information of the target training environment.
- property action_dim¶
The dimension of action assuming that the action is flatten.
- property action_shape¶
The shape of action space
- static from_env(env)[source]¶
Create env_info from environment
- Parameters
env (gym.Env) – the environment
- Returns
EnvironmentInfo (
EnvironmentInfo
)
Example
>>> import gym >>> from nnabla_rl.environments.environment_info import EnvironmentInfo >>> env = gym.make("CartPole-v0") >>> env_info = EnvironmentInfo.from_env(env) >>> env_info.state_shape (4,)
- is_continuous_action_env()[source]¶
Check whether the action to execute in the environment is continuous or not
- Returns
True if the action to execute in the environment is continuous. Otherwise False.
- Return type
bool
- is_discrete_action_env()[source]¶
Check whether the action to execute in the environment is discrete or not
- Returns
True if the action to execute in the environment is discrete. Otherwise False.
- Return type
bool
- property state_dim¶
The dimension of state assuming that the state is flatten.
- property state_shape¶
The shape of observation space