| {"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 0x787ceca6d090>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x787ceca6d120>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x787ceca6d1b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x787ceca6d240>", "_build": "<function ActorCriticPolicy._build at 0x787ceca6d2d0>", "forward": "<function ActorCriticPolicy.forward at 0x787ceca6d360>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x787ceca6d3f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x787ceca6d480>", "_predict": "<function ActorCriticPolicy._predict at 0x787ceca6d510>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x787ceca6d5a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x787ceca6d630>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x787ceca6d6c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x787ceca0dcc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1512000, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713114655198210029, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAQAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.008000000000000007, "_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": 378, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1500, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 90, "n_epochs": 6, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |