| {"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 0x7af4c9d91580>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7af4c9d91620>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7af4c9d916c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7af4c9d91760>", "_build": "<function ActorCriticPolicy._build at 0x7af4c9d91800>", "forward": "<function ActorCriticPolicy.forward at 0x7af4c9d918a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7af4c9d91940>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7af4c9d919e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7af4c9d91a80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7af4c9d91b20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7af4c9d91bc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7af4c9d91c60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7af4ca1a2f80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 4014080, "_total_timesteps": 4000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1738856323792577267, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAEAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_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": 994, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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": 0.9999, "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": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |