File size: 11,744 Bytes
1c51130
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 0x7f4e58cc50e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4e58cc5170>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4e58cc5200>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4e58cc5290>", "_build": "<function ActorCriticPolicy._build at 0x7f4e58cc5320>", "forward": "<function ActorCriticPolicy.forward at 0x7f4e58cc53b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4e58cc5440>", "_predict": "<function ActorCriticPolicy._predict at 0x7f4e58cc54d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4e58cc5560>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4e58cc55f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4e58cc5680>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f4e58c8b9f0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLEIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 16, "_shape": [], "dtype": "int64", "_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": 1654605414.735013, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gASVCAEAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYolDgAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAoAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAAAAAAAAAAIAAAAAAAAAAgAAAAAAAAAAAAAAAAAAAAIAAAAAAAAAAQAAAAAAAAACAAAAAAAAAAIAAAAAAAAAAkAAAAAAAAAlHSUYi4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAABAAAAAAAAAAAAAACUdJRiLg=="}, "_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": 310, "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": 5, "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"}}