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from easydict import EasyDict
cartpole_discrete_dt_config = dict(
exp_name='cartpole_dt_seed0',
env=dict(
collector_env_num=8,
evaluator_env_num=5,
n_evaluator_episode=5,
stop_value=195,
),
dataset=dict(
data_dir_prefix='./cartpole_qrdqn_generation_data_seed0/expert_demos.hdf5',
rtg_scale=None,
context_len=20,
env_type='classic',
),
policy=dict(
cuda=False,
rtg_target=10,
evaluator_env_num=5,
clip_grad_norm_p=1.0,
state_mean=1,
state_std=0,
model=dict(
state_dim=4,
act_dim=2,
n_blocks=6,
h_dim=128,
context_len=20,
n_heads=8,
drop_p=0.1,
continuous=False,
),
max_timestep=1000,
discount_factor=0.97,
nstep=3,
batch_size=64,
learning_rate=0.001,
target_update_freq=100,
kappa=1.0,
min_q_weight=4.0,
collect=dict(
data_type='hdf5',
data_path='./cartpole_qrdqn_generation_data_seed0/expert_demos.hdf5',
),
eval=dict(evaluator=dict(eval_freq=100, )),
),
)
cartpole_discrete_dt_config = EasyDict(cartpole_discrete_dt_config)
main_config = cartpole_discrete_dt_config
cartpole_discrete_dt_create_config = dict(
env=dict(
type='cartpole',
import_names=['dizoo.classic_control.cartpole.envs.cartpole_env'],
),
env_manager=dict(type='base'),
policy=dict(type='dt'),
)
cartpole_discrete_dt_create_config = EasyDict(cartpole_discrete_dt_create_config)
create_config = cartpole_discrete_dt_create_config
# You can run this config with the entry file like `ding/example/dt.py`
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