{"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 0x7950467663b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x795046766440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7950467664d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x795046766560>", "_build": "<function ActorCriticPolicy._build at 0x7950467665f0>", "forward": "<function ActorCriticPolicy.forward at 0x795046766680>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x795046766710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7950467667a0>", "_predict": "<function ActorCriticPolicy._predict at 0x795046766830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7950467668c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x795046766950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7950467669e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7950467704c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 524288, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1697029419908126511, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAAMmqOr8RLja8ZBgVv13bXLuw/je/URxGu+LrwL4Ayj48xY8Av808SDs9Qhq/YiQkvPeiK7+SJj+8WUn7vuDcTDwE3x6/uVwuvNRtKr8zYqO5pq0Ov/avJ7wzowm/6fjnudGs/L6Uldq7d63kvp5rS7yHEua+8ZIfPIoVOb9K9mI8lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="}, "_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": -0.04857599999999995, "_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": 67, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True]", "bounded_above": "[ True True]", "_shape": [2], "low": "[-1.2 -0.07]", "high": "[0.6 0.07]", "low_repr": "[-1.2 -0.07]", "high_repr": "[0.6 0.07]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIAwAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "3", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |