| {"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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f731c223f40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f731c214040>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f731c2140d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f731c214160>", "_build": "<function ActorCriticPolicy._build at 0x7f731c2141f0>", "forward": "<function ActorCriticPolicy.forward at 0x7f731c214280>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f731c214310>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f731c2143a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f731c214430>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f731c2144c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f731c214550>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f731c2145e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f731c1c3f00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1704027800045556747, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAADMW4rwlvCc+oau7PVZciL69K0u9h+EBPgAAAAAAAAAAmrvJPIUTvTo3kZk9djl6vhgO8Ls7a4g9AAAAAAAAAABGTRU+gYi8vKzrgL4eaX6+IscTvUaXNz8AAIA/AACAPwBCVLyPunm6is0IO+eIkTao+mo73icdugAAAAAAAAAAAEDivKKpqD/eqoW+POAIv/R0h7ya8LG9AAAAAAAAAACAeha9lhNGPT2157z3Vpi+e77gvQIHWrwAAAAAAAAAADOpKzyG0IM//eDVvP4W476wsvI9lpKBvQAAAAAAAAAAml+9vHLDUD8GaEG8W/PZvgRLuzp1cF49AAAAAAAAAACAWg69q5ysP01IPr4v1sK+bRQ3O1NH2rwAAAAAAAAAAH7dlL5se4o+YKz9Pgmev77vMUS9tmFxPgAAAAAAAAAAWgmlPVX2vj+kMxI/8fvvPUxtwzwlImY+AAAAAAAAAADNbxu9diG4P8kVub6eUjw76UYOu04Vm70AAAAAAAAAAABmUbw4I8Y9UjqoPc4Mkb7clTO8jvXHPAAAAAAAAAAAQGOLvUhLhLo23Nw7LSQGuaDZpjkzlQC4AACAPwAAgD9mVr463EcxPwT5k76zwfy+NAdwvepwbr4AAAAAAAAAAM3MOTwp/A66OxzjOwFjdTXIxSI75Vl9NAAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 428, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |