| {"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 0x7f39538523b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3953852440>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f39538524d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3953852560>", "_build": "<function ActorCriticPolicy._build at 0x7f39538525f0>", "forward": "<function ActorCriticPolicy.forward at 0x7f3953852680>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f3953852710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f39538527a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3953852830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f39538528c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3953852950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f39538529e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f3953846a40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 100352, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688021762260279513, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAABCktT5SK827buFVPTQGg72P6Ae9c8+7PQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "_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": 392, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "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:": "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"}, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |