| {"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 0x7d0558d5b1a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d0558d5b240>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d0558d5b2e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d0558d5b380>", "_build": "<function ActorCriticPolicy._build at 0x7d0558d5b420>", "forward": "<function ActorCriticPolicy.forward at 0x7d0558d5b4c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d0558d5b560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d0558d5b600>", "_predict": "<function ActorCriticPolicy._predict at 0x7d0558d5b6a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d0558d5b740>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d0558d5b7e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d0558d5b880>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d0559556e80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1747907811995684274, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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": 252, "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": 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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |