Training¶
Trainer
¶
-
class
numpy_ml.rl_models.trainer.
Trainer
(agent, env)[source]¶ An object to facilitate agent training and evaluation.
Parameters: - agent (
AgentBase
instance) – The agent to train. - env (
gym.wrappers
orgym.envs
instance) – The environment to run the agent on.
-
train
(n_episodes, max_steps, seed=None, plot=True, verbose=True, render_every=None, smooth_factor=0.05)[source]¶ Train an agent on an OpenAI gym environment, logging training statistics along the way.
Parameters: - n_episodes (int) – The number of episodes to train the agent across.
- max_steps (int) – The maximum number of steps the agent can take on each episode.
- seed (int or None) – A seed for the random number generator. Default is None.
- plot (bool) – Whether to generate a plot of the cumulative reward as a function of training episode. Default is True.
- verbose (bool) – Whether to print intermediate run statistics to stdout during training. Default is True.
- smooth_factor (float in [0, 1]) – The amount to smooth the cumulative reward across episodes. Larger values correspond to less smoothing.
- agent (