|
from easydict import EasyDict |
|
|
|
|
|
|
|
|
|
collector_env_num = 8 |
|
n_episode = 8 |
|
evaluator_env_num = 3 |
|
num_simulations = 25 |
|
update_per_collect = 100 |
|
batch_size = 256 |
|
max_env_step = int(1e5) |
|
reanalyze_ratio = 0 |
|
|
|
|
|
|
|
|
|
cfg = dict( |
|
main_config=dict( |
|
exp_name='CartPole-v0-MuZero', |
|
seed=0, |
|
env=dict( |
|
env_id='CartPole-v0', |
|
continuous=False, |
|
manually_discretization=False, |
|
collector_env_num=collector_env_num, |
|
evaluator_env_num=evaluator_env_num, |
|
n_evaluator_episode=evaluator_env_num, |
|
manager=dict(shared_memory=False, ), |
|
), |
|
policy=dict( |
|
model=dict( |
|
observation_shape=4, |
|
action_space_size=2, |
|
model_type='mlp', |
|
lstm_hidden_size=128, |
|
latent_state_dim=128, |
|
self_supervised_learning_loss=True, |
|
discrete_action_encoding_type='one_hot', |
|
norm_type='BN', |
|
), |
|
cuda=True, |
|
env_type='not_board_games', |
|
game_segment_length=50, |
|
update_per_collect=update_per_collect, |
|
batch_size=batch_size, |
|
optim_type='Adam', |
|
lr_piecewise_constant_decay=False, |
|
learning_rate=0.003, |
|
ssl_loss_weight=2, |
|
num_simulations=num_simulations, |
|
reanalyze_ratio=reanalyze_ratio, |
|
n_episode=n_episode, |
|
eval_freq=int(2e2), |
|
replay_buffer_size=int(1e6), |
|
collector_env_num=collector_env_num, |
|
evaluator_env_num=evaluator_env_num, |
|
), |
|
wandb_logger=dict( |
|
gradient_logger=False, video_logger=False, plot_logger=False, action_logger=False, return_logger=False |
|
), |
|
), |
|
create_config=dict( |
|
env=dict( |
|
type='cartpole_lightzero', |
|
import_names=['zoo.classic_control.cartpole.envs.cartpole_lightzero_env'], |
|
), |
|
env_manager=dict(type='subprocess'), |
|
policy=dict( |
|
type='muzero', |
|
import_names=['lzero.policy.muzero'], |
|
), |
|
), |
|
) |
|
|
|
cfg = EasyDict(cfg) |
|
|