| {"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 0x7d82dc81af20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d82dc81afc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d82dc81b060>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d82dc81b100>", "_build": "<function ActorCriticPolicy._build at 0x7d82dc81b1a0>", "forward": "<function ActorCriticPolicy.forward at 0x7d82dc81b240>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d82dc81b2e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d82dc81b380>", "_predict": "<function ActorCriticPolicy._predict at 0x7d82dc81b420>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d82dc81b4c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d82dc81b560>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d82dc81b600>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d82dc975ec0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2015232, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1750772661900054908, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAAAzP4c7Jeq+P06qbD09LZU+ALyPvF5Oob0AAAAAAAAAAJohGrxCjMg+bwcGvj6Zzb71RQ29pkmPPQAAAAAAAAAAmr6zPOgllT31UuQ9qnwNv74YyT4a+ra9AAAAAAAAAAAzS0O8ZEUJP9S+kD1CguG+HRAmPbMXez0AAAAAAAAAADPBBL0WODs9HEMOPm5iob5ZWqA9sOP1vAAAAAAAAAAAmkEqPFI1vD/wCeI99qg/PuAdMrqGnJ08AAAAAAAAAADzv4Y9hcuCu3MZoLyfJYk8ESSkvN1Kaz0AAIA/AACAP6aPgb32rG66xjlpM0uxJizMWW84yti1swAAgD8AAIA/ICkyPviIPT9qMXg9xij8vry7GD74ULu8AAAAAAAAAAAgmis+5lGbP42Wcz47lSO/+mBVPml2Cz0AAAAAAAAAAAB77bwDbCm8BjCWuyfGBT3zh1e8MGgWtwAAgD8AAIA/44hUvsZYBD/KMlQ+RjTWvsoRw72jLVY+AAAAAAAAAABNLjY9XNNQuiodmDUdsaMwLdAsugKYrrQAAIA/AACAPzYcgb579Vo/Y/KGPckR7b6duGG+gL4PPgAAAAAAAAAAAHEYvoIBjz/oxCG/zR0sv+AIQL5tv8y+AAAAAAAAAABmtL283HU0vC7KTb3a0xw8HPSbPYLTBb0AAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLEEsIhpSMAUOUdJRSlC4="}, "_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": -0.007616000000000067, "_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": 738, "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": 0.99, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 6, "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": "3.11.13", "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"}} |