| {"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 0x7c3a9a296660>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c3a9a296700>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c3a9a2967a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c3a9a296840>", "_build": "<function ActorCriticPolicy._build at 0x7c3a9a2968e0>", "forward": "<function ActorCriticPolicy.forward at 0x7c3a9a296980>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c3a9a296a20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c3a9a296ac0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c3a9a296b60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c3a9a296c00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c3a9a296ca0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c3a9a296d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c3a9a202940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1742153084530101670, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAO0HCD7Dhm+8eFfPvFWJmzx+yOC9RbR5PQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.00044800000000000395, "_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": 3908, "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": 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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |