File size: 14,494 Bytes
1438c00
1
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7faba0117c20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7faba0117cb0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7faba0117d40>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7faba0117dd0>", "_build": "<function ActorCriticPolicy._build at 0x7faba0117e60>", "forward": "<function ActorCriticPolicy.forward at 0x7faba0117ef0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7faba0117f80>", "_predict": "<function ActorCriticPolicy._predict at 0x7faba011f050>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7faba011f0e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7faba011f170>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7faba011f200>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7faba00ed600>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1653170858.4478705, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}