| {"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 0x7b2cbdc62f20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b2cbdc62fc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b2cbdc63060>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b2cbdc63100>", "_build": "<function ActorCriticPolicy._build at 0x7b2cbdc631a0>", "forward": "<function ActorCriticPolicy.forward at 0x7b2cbdc63240>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b2cbdc632e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b2cbdc63380>", "_predict": "<function ActorCriticPolicy._predict at 0x7b2cbdc63420>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b2cbdc634c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b2cbdc63560>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b2cbdc63600>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b2cbdd6c1c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1768312035814896080, "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": 248, "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:": "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-6.6.105+-x86_64-with-glibc2.35 # 1 SMP Thu Oct 2 10:42:05 UTC 2025", "Python": "3.12.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.9.0+cu126", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.2", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |