| {"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 0x7bf045120400>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bf0451204a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bf045120540>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bf0451205e0>", "_build": "<function ActorCriticPolicy._build at 0x7bf045120680>", "forward": "<function ActorCriticPolicy.forward at 0x7bf045120720>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bf0451207c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bf045120860>", "_predict": "<function ActorCriticPolicy._predict at 0x7bf045120900>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bf0451209a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bf045120a40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bf045120ae0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bf04511cac0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1736150989257823245, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlgAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAmXAK+Q91ZvDR+Kbx3okw8YDC/Pc2VKr0AAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksBhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3908, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdwIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBNudW1weS5fY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolggAAAAAAAAAAQEBAQEBAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUjAFDlHSUUpSMDWJvdW5kZWRfYWJvdmWUaBEolggAAAAAAAAAAQEBAQEBAQGUaBVLCIWUaBl0lFKUjAZfc2hhcGWUSwiFlIwDbG93lGgRKJYgAAAAAAAAAAAAtMIAALTCAACgwAAAoMDbD0nAAACgwAAAAIAAAACAlGgLSwiFlGgZdJRSlIwEaGlnaJRoESiWIAAAAAAAAAAAALRCAAC0QgAAoEAAAKBA2w9JQAAAoEAAAIA/AACAP5RoC0sIhZRoGXSUUpSMCGxvd19yZXBylIxbWy05MC4gICAgICAgIC05MC4gICAgICAgICAtNS4gICAgICAgICAtNS4gICAgICAgICAtMy4xNDE1OTI3ICAtNS4KICAtMC4gICAgICAgICAtMC4gICAgICAgXZSMCWhpZ2hfcmVwcpSMU1s5MC4gICAgICAgIDkwLiAgICAgICAgIDUuICAgICAgICAgNS4gICAgICAgICAzLjE0MTU5MjcgIDUuCiAgMS4gICAgICAgICAxLiAgICAgICBdlIwKX25wX3JhbmRvbZROdWIu", "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "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-6.9.3-76060903-generic-x86_64-with-glibc2.35 # 202405300957~1732141768~22.04~f2697e1 SMP PREEMPT_DYNAMIC Wed N", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "2.2.1", "Cloudpickle": "3.1.0", "Gymnasium": "0.28.1"}} |