本文整理汇总了Python中baselines.acer.buffer.Buffer方法的典型用法代码示例。如果您正苦于以下问题：Python buffer.Buffer方法的具体用法？Python buffer.Buffer怎么用？Python buffer.Buffer使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类baselines.acer.buffer的用法示例。
在下文中一共展示了buffer.Buffer方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: learn
# 需要导入模块: from baselines.acer import buffer [as 别名]
# 或者: from baselines.acer.buffer import Buffer [as 别名]
def learn(policy, env, seed, nsteps=20, nstack=4, total_timesteps=int(80e6), q_coef=0.5, ent_coef=0.01,
max_grad_norm=10, lr=7e-4, lrschedule='linear', rprop_epsilon=1e-5, rprop_alpha=0.99, gamma=0.99,
log_interval=100, buffer_size=50000, replay_ratio=4, replay_start=10000, c=10.0,
trust_region=True, alpha=0.99, delta=1):
print("Running Acer Simple")
print(locals())
tf.reset_default_graph()
set_global_seeds(seed)
nenvs = env.num_envs
ob_space = env.observation_space
ac_space = env.action_space
num_procs = len(env.remotes) # HACK
model = Model(policy=policy, ob_space=ob_space, ac_space=ac_space, nenvs=nenvs, nsteps=nsteps, nstack=nstack,
num_procs=num_procs, ent_coef=ent_coef, q_coef=q_coef, gamma=gamma,
max_grad_norm=max_grad_norm, lr=lr, rprop_alpha=rprop_alpha, rprop_epsilon=rprop_epsilon,
total_timesteps=total_timesteps, lrschedule=lrschedule, c=c,
trust_region=trust_region, alpha=alpha, delta=delta)
runner = Runner(env=env, model=model, nsteps=nsteps, nstack=nstack)
if replay_ratio > 0:
buffer = Buffer(env=env, nsteps=nsteps, nstack=nstack, size=buffer_size)
else:
buffer = None
nbatch = nenvs*nsteps
acer = Acer(runner, model, buffer, log_interval)
acer.tstart = time.time()
for acer.steps in range(0, total_timesteps, nbatch): #nbatch samples, 1 on_policy call and multiple off-policy calls
acer.call(on_policy=True)
if replay_ratio > 0 and buffer.has_atleast(replay_start):
n = np.random.poisson(replay_ratio)
for _ in range(n):
acer.call(on_policy=False) # no simulation steps in this
env.close()