| {"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 0x7d027ebc8c10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d027ebc8ca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d027ebc8d30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d027ebc8dc0>", "_build": "<function ActorCriticPolicy._build at 0x7d027ebc8e50>", "forward": "<function ActorCriticPolicy.forward at 0x7d027ebc8ee0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d027ebc8f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d027ebc9000>", "_predict": "<function ActorCriticPolicy._predict at 0x7d027ebc9090>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d027ebc9120>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d027ebc91b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d027ebc9240>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d027f500d40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1709776552811573293, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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": "2.1.0+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |