Python Trajectory.fit示例

示例#1

import gym

from trickster.agent import REINFORCE, A2C, PPO
from trickster.rollout import Trajectory
from trickster import callbacks

ENV_NAME = "LunarLanderContinuous-v2"
ALGO = "REINFORCE"
TRAJECTORY_MAX_STEPS = 100
EPOCHS = 1000
ROLLOUTS_PER_EPOCH = 4

env = gym.make(ENV_NAME)

algo = {"REINFORCE": REINFORCE, "A2C": A2C, "PPO": PPO}[ALGO]

agent = algo.from_environment(env)
rollout = Trajectory(agent, env, TRAJECTORY_MAX_STEPS)

cbs = [callbacks.ProgressPrinter(keys=rollout.progress_keys)]

rollout.fit(epochs=EPOCHS,
            updates_per_epoch=1,
            rollouts_per_update=4,
            callbacks=cbs)
rollout.render(repeats=100)

示例#2

from trickster.agent import REINFORCE
from trickster.rollout import Trajectory, RolloutConfig
from trickster.utility import gymic
from trickster.model import mlp

env = gymic.rwd_scaled_env()
input_shape = env.observation_space.shape
num_actions = env.action_space.n

policy = mlp.wide_mlp_actor_categorical(input_shape, num_actions, adam_lr=1e-4)
agent = REINFORCE(policy, action_space=num_actions)
rollout = Trajectory(agent, env, config=RolloutConfig(max_steps=300))

rollout.fit(episodes=500, rollouts_per_update=1, update_batch_size=-1)
rollout.render(repeats=10)