Upload policy_config.py with huggingface_hub
Browse files- policy_config.py +114 -0
policy_config.py
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exp_config = {
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'main_config': {
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'exp_name': 'Pendulum-v1-EfficientZero',
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'seed': 0,
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'env': {
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'env_id': 'Pendulum-v1',
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'continuous': False,
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'manually_discretization': True,
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'each_dim_disc_size': 11,
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'collector_env_num': 8,
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'evaluator_env_num': 3,
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'n_evaluator_episode': 3,
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'manager': {
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'shared_memory': False
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}
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},
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'policy': {
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'on_policy': False,
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'cuda': True,
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'multi_gpu': False,
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'bp_update_sync': True,
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'traj_len_inf': False,
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'model': {
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'observation_shape': 3,
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'action_space_size': 11,
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'model_type': 'mlp',
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'lstm_hidden_size': 128,
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'latent_state_dim': 128
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},
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'use_rnd_model': False,
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'sampled_algo': False,
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'gumbel_algo': False,
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'mcts_ctree': True,
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'collector_env_num': 8,
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'evaluator_env_num': 3,
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'env_type': 'not_board_games',
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'action_type': 'fixed_action_space',
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'battle_mode': 'play_with_bot_mode',
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'monitor_extra_statistics': True,
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'game_segment_length': 50,
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'transform2string': False,
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'gray_scale': False,
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'use_augmentation': False,
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'augmentation': ['shift', 'intensity'],
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'ignore_done': False,
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'update_per_collect': 200,
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'model_update_ratio': 0.1,
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'batch_size': 256,
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'optim_type': 'Adam',
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'learning_rate': 0.003,
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'target_update_freq': 100,
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'target_update_freq_for_intrinsic_reward': 1000,
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'weight_decay': 0.0001,
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'momentum': 0.9,
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'grad_clip_value': 10,
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'n_episode': 8,
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'num_simulations': 50,
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'discount_factor': 0.997,
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'td_steps': 5,
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'num_unroll_steps': 5,
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'reward_loss_weight': 1,
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'value_loss_weight': 0.25,
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'policy_loss_weight': 1,
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'policy_entropy_loss_weight': 0,
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'ssl_loss_weight': 2,
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'lr_piecewise_constant_decay': False,
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'threshold_training_steps_for_final_lr': 50000,
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'manual_temperature_decay': False,
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'threshold_training_steps_for_final_temperature': 100000,
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'fixed_temperature_value': 0.25,
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'use_ture_chance_label_in_chance_encoder': False,
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'use_priority': True,
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'priority_prob_alpha': 0.6,
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'priority_prob_beta': 0.4,
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'root_dirichlet_alpha': 0.3,
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'root_noise_weight': 0.25,
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'random_collect_episode_num': 0,
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'eps': {
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'eps_greedy_exploration_in_collect': False,
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'type': 'linear',
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'start': 1.0,
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'end': 0.05,
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'decay': 100000
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},
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'cfg_type': 'EfficientZeroPolicyDict',
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'lstm_horizon_len': 5,
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'reanalyze_ratio': 0,
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'eval_freq': 2000,
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'replay_buffer_size': 1000000
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},
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'wandb_logger': {
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'gradient_logger': False,
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'video_logger': False,
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'plot_logger': False,
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'action_logger': False,
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'return_logger': False
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}
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},
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'create_config': {
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'env': {
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'type':
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'pendulum_lightzero',
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'import_names':
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['zoo.classic_control.pendulum.envs.pendulum_lightzero_env']
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},
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'env_manager': {
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'type': 'subprocess'
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},
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'policy': {
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'type': 'efficientzero',
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'import_names': ['lzero.policy.efficientzero']
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}
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}
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}
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