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from easydict import EasyDict
collector_env_num = 8
evaluator_env_num = 8
qbert_r2d2_config = dict(
exp_name='qbert_r2d2_seed0',
env=dict(
collector_env_num=collector_env_num,
evaluator_env_num=evaluator_env_num,
n_evaluator_episode=evaluator_env_num,
stop_value=int(1e6),
env_id='QbertNoFrameskip-v4',
#'ALE/Qbert-v5' is available. But special setting is needed after gym make.
frame_stack=4
),
policy=dict(
cuda=True,
priority=True,
priority_IS_weight=True,
model=dict(
obs_shape=[4, 84, 84],
action_shape=6,
encoder_hidden_size_list=[128, 128, 512],
res_link=False,
),
discount_factor=0.997,
nstep=5,
burnin_step=20,
# (int) the whole sequence length to unroll the RNN network minus
# the timesteps of burnin part,
# i.e., <the whole sequence length> = <unroll_len> = <burnin_step> + <learn_unroll_len>
learn_unroll_len=80,
learn=dict(
# according to the R2D2 paper, actor parameter update interval is 400
# environment timesteps, and in per collect phase, we collect <n_sample> sequence
# samples, the length of each sequence sample is <burnin_step> + <learn_unroll_len>,
# e.g. if n_sample=32, <sequence length> is 100, thus 32*100/400=8,
# we will set update_per_collect=8 in most environments.
update_per_collect=8,
batch_size=64,
learning_rate=0.0005,
target_update_theta=0.001,
),
collect=dict(
# NOTE: It is important that set key traj_len_inf=True here,
# to make sure self._traj_len=INF in serial_sample_collector.py.
# In sequence-based policy, for each collect_env,
# we want to collect data of length self._traj_len=INF
# unless the episode enters the 'done' state.
# In each collect phase, we collect a total of <n_sample> sequence samples.
n_sample=32,
traj_len_inf=True,
env_num=collector_env_num,
),
eval=dict(env_num=evaluator_env_num, ),
other=dict(
eps=dict(
type='exp',
start=0.95,
end=0.05,
decay=1e5,
),
replay_buffer=dict(
replay_buffer_size=10000,
# (Float type) How much prioritization is used: 0 means no prioritization
# while 1 means full prioritization
alpha=0.6,
# (Float type) How much correction is used: 0 means no correction while 1 means full correction
beta=0.4,
)
),
),
)
qbert_r2d2_config = EasyDict(qbert_r2d2_config)
main_config = qbert_r2d2_config
qbert_r2d2_create_config = dict(
env=dict(
type='atari',
import_names=['dizoo.atari.envs.atari_env'],
),
env_manager=dict(type='subprocess'),
policy=dict(type='r2d2'),
)
qbert_r2d2_create_config = EasyDict(qbert_r2d2_create_config)
create_config = qbert_r2d2_create_config
if __name__ == "__main__":
# or you can enter ding -m serial -c qbert_r2d2_config.py -s 0
from ding.entry import serial_pipeline
serial_pipeline([main_config, create_config], seed=0)
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