Upload policy_config.py with huggingface_hub
Browse files- policy_config.py +99 -0
policy_config.py
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exp_config = {
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'env': {
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'manager': {
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'episode_num': float("inf"),
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'max_retry': 1,
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'retry_type': 'reset',
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'auto_reset': True,
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'step_timeout': None,
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'reset_timeout': None,
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'retry_waiting_time': 0.1,
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'cfg_type': 'BaseEnvManagerDict'
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},
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'stop_value': 260,
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'n_evaluator_episode': 8,
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'env_id': 'LunarLander-v2',
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'collector_env_num': 8,
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'evaluator_env_num': 8
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},
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'policy': {
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'model': {
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'encoder_hidden_size_list': [512, 64],
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'obs_shape': 8,
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'action_shape': 4,
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'dueling': True
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},
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'learn': {
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'learner': {
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'train_iterations': 1000000000,
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'dataloader': {
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'num_workers': 0
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},
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'log_policy': True,
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'hook': {
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'load_ckpt_before_run': '',
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'log_show_after_iter': 100,
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'save_ckpt_after_iter': 10000,
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'save_ckpt_after_run': True
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},
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'cfg_type': 'BaseLearnerDict'
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},
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'update_per_collect': 10,
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'batch_size': 64,
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'learning_rate': 0.001,
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'target_update_freq': 100,
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'target_theta': 0.005,
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'ignore_done': False
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},
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'collect': {
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'collector': {},
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'n_sample': 64,
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'unroll_len': 1
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},
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'eval': {
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'evaluator': {
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'eval_freq': 1000,
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'render': {
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'render_freq': -1,
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'mode': 'train_iter'
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},
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'figure_path': None,
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'cfg_type': 'InteractionSerialEvaluatorDict',
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'stop_value': 260,
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'n_episode': 8
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}
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},
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'other': {
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'replay_buffer': {
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'replay_buffer_size': 100000
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},
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'eps': {
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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': 50000
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}
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},
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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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'type': 'dqn',
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'priority': False,
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'priority_IS_weight': False,
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'discount_factor': 0.99,
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'nstep': 3,
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'cfg_type': 'DQNPolicyDict',
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'random_collect_size': 25000
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},
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'exp_name': 'LunarLander-v2-DQN',
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'seed': 0,
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'wandb_logger': {
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'gradient_logger': True,
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'video_logger': True,
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'plot_logger': True,
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'action_logger': True,
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'return_logger': False
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}
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}
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