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Upload policy_config.py with huggingface_hub

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  1. policy_config.py +114 -0
policy_config.py ADDED
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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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+ }