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from easydict import EasyDict |
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from copy import deepcopy |
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halfcheetah_dt_config = dict( |
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exp_name='dt_log/d4rl/halfcheetah/halfcheetah_medium_replay_dt_seed0', |
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env=dict( |
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env_id='HalfCheetah-v3', |
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collector_env_num=1, |
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evaluator_env_num=8, |
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use_act_scale=True, |
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n_evaluator_episode=8, |
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stop_value=6000, |
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), |
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dataset=dict( |
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env_type='mujoco', |
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rtg_scale=1000, |
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context_len=30, |
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data_dir_prefix='d4rl/halfcheetah_medium_replay-v2.pkl', |
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), |
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policy=dict( |
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cuda=True, |
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stop_value=6000, |
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state_mean=None, |
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state_std=None, |
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evaluator_env_num=8, |
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env_name='HalfCheetah-v3', |
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rtg_target=6000, |
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max_eval_ep_len=1000, |
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wt_decay=1e-4, |
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warmup_steps=10000, |
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context_len=20, |
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weight_decay=0.1, |
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clip_grad_norm_p=0.25, |
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model=dict( |
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state_dim=11, |
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act_dim=3, |
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n_blocks=3, |
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h_dim=128, |
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context_len=20, |
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n_heads=1, |
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drop_p=0.1, |
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continuous=True, |
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), |
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batch_size=64, |
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learning_rate=1e-4, |
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collect=dict( |
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data_type='d4rl_trajectory', |
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unroll_len=1, |
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), |
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eval=dict(evaluator=dict(eval_freq=100, ), ), |
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), |
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) |
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halfcheetah_dt_config = EasyDict(halfcheetah_dt_config) |
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main_config = halfcheetah_dt_config |
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halfcheetah_dt_create_config = dict( |
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env=dict( |
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type='mujoco', |
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import_names=['dizoo.mujoco.envs.mujoco_env'], |
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), |
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env_manager=dict(type='subprocess'), |
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policy=dict(type='dt'), |
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) |
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halfcheetah_dt_create_config = EasyDict(halfcheetah_dt_create_config) |
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create_config = halfcheetah_dt_create_config |
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if __name__ == "__main__": |
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from ding.entry import serial_pipeline_dt |
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config = deepcopy([main_config, create_config]) |
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serial_pipeline_dt(config, seed=0, max_train_iter=1000) |
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