{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7f04bb33e290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f04bb33e320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f04bb33e3b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f04bb33e440>", "_build": "<function ActorCriticPolicy._build at 0x7f04bb33e4d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f04bb33e560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f04bb33e5f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f04bb33e680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f04bb33e710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f04bb33e7a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f04bb33e830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f04bb390330>"}, "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:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////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": 1652736667.7806036, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_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:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "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:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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"}}