| {"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 0x7f1c4509c040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1c4509c0e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1c4509c180>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1c4509c220>", "_build": "<function ActorCriticPolicy._build at 0x7f1c4509c2c0>", "forward": "<function ActorCriticPolicy.forward at 0x7f1c4509c360>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f1c4509c400>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1c4509c4a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f1c4509c540>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1c4509c5e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1c4509c680>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1c4509c720>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f1c45023840>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1745158819070526940, "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-6.1.123+-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"}} |