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from easydict import EasyDict |
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from copy import deepcopy |
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hopper_dt_config = dict( |
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exp_name='hopper_random_dt_seed0', |
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env=dict( |
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env_id='Hopper-v3', |
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norm_obs=dict(use_norm=False, ), |
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norm_reward=dict(use_norm=False, ), |
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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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policy=dict( |
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stop_value=6000, |
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cuda=True, |
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env_name='Hopper-v3', |
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rtg_target=6000, |
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max_eval_ep_len=1000, |
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num_eval_ep=10, |
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batch_size=64, |
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wt_decay=1e-4, |
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warmup_steps=10000, |
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num_updates_per_iter=100, |
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context_len=20, |
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n_blocks=3, |
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embed_dim=128, |
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n_heads=1, |
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dropout_p=0.1, |
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log_dir='/home/wangzilin/research/dt/DI-engine/dizoo/d4rl/dt_data/hopper_random_dt_log', |
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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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discount_factor=0.999, |
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nstep=3, |
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learn=dict( |
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dataset_path='/mnt/lustre/wangzilin/d4rl_data/hopper-random-v2.pkl', |
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learning_rate=0.0001, |
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target_update_freq=100, |
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kappa=1.0, |
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min_q_weight=4.0 |
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), |
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collect=dict(unroll_len=1, ), |
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eval=dict(evaluator=dict(evalu_freq=100, ), ), |
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other=dict( |
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eps=dict( |
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type='exp', |
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start=0.95, |
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end=0.1, |
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decay=10000, |
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), |
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replay_buffer=dict(replay_buffer_size=1000, ), |
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), |
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), |
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) |
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hopper_dt_config = EasyDict(hopper_dt_config) |
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main_config = hopper_dt_config |
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hopper_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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hopper_dt_create_config = EasyDict(hopper_dt_create_config) |
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create_config = hopper_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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