| {"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 0x78d45a46ede0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78d45a46ee80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78d45a46ef20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78d45a46efc0>", "_build": "<function ActorCriticPolicy._build at 0x78d45a46f060>", "forward": "<function ActorCriticPolicy.forward at 0x78d45a46f100>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78d45a46f1a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78d45a46f240>", "_predict": "<function ActorCriticPolicy._predict at 0x78d45a46f2e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78d45a46f380>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78d45a46f420>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78d45a46f4c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78d45a5e2980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1742228693949370117, "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:": "gAWV+AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQBuFV1fVqeuMAWyUS6mMAXSUR0CajtXMQmNSdX2UKGgGR0BwF/zundftaAdLyWgIR0Caj2zTWoWIdX2UKGgGR0BwlS1D0DlpaAdLwWgIR0CakN7/GVAzdX2UKGgGR0BxP+RvFWGRaAdL3WgIR0CakRk8RtgsdX2UKGgGR0ByF7b+Lm6oaAdL8GgIR0CalUVdHDrJdX2UKGgGR0ByArl+3H7xaAdL6mgIR0CalbCMglnidX2UKGgGR0BuzNQyhzvJaAdLyWgIR0CaliNTLns+dX2UKGgGR0BuA9P1tfoiaAdL7mgIR0CalllnRLK3dX2UKGgGR0BwYoFkhA4XaAdL0WgIR0CamNgSeyzHdX2UKGgGR0Bxt1oduHeraAdL1WgIR0CamQJBw++udX2UKGgGR0BxLA3yZrpJaAdLv2gIR0CamRwwCbMHdX2UKGgGR0Bx4kRg7YChaAdNfQFoCEdAmpm9krf+CXV9lChoBkdAcPWWn0kGA2gHS81oCEdAmpvYNI9TxXV9lChoBkdAbfiIcBEKE2gHS+JoCEdAmpx1kpZwGXV9lChoBkdAW6xyxRl6JWgHTegDaAhHQJqeatHQQcx1fZQoaAZHQHIRQfZElVtoB0vNaAhHQJqey+UQkHF1fZQoaAZHQG0WlBppN9JoB0vRaAhHQJqfpEPUayd1fZQoaAZHQHGUiWmgrYpoB010AWgIR0Can9Y2sJY1dX2UKGgGR0BvIn/95yEMaAdL4mgIR0Can9aq0dBCdX2UKGgGR0BwWX/LkjoqaAdL3mgIR0Can/pjMFEBdX2UKGgGR0BelvUaya/iaAdN6ANoCEdAmqF6ioKlYXV9lChoBkdAcMAWE9Mbm2gHS+VoCEdAmqH3hfjS5XV9lChoBkdAcgbe0ojOcGgHTR8BaAhHQJqkIdNnGsF1fZQoaAZHQFpRdbPhQ3xoB03oA2gIR0CapVWBz3h5dX2UKGgGR0BxF6TgVGkOaAdL+mgIR0CapaLS/j82dX2UKGgGR0BwyMn1FpfyaAdNEQFoCEdAmqXpPZZjhHV9lChoBkdAceS7gbZOBWgHS+RoCEdAmqbEY0l7dHV9lChoBkdAcowpz90ihWgHS+xoCEdAmqdmaYu01XV9lChoBkdAbPp/x2B8QmgHS9loCEdAmqeKvmoze3V9lChoBkdAcfVcmShakmgHS9NoCEdAmqeiSidrf3V9lChoBkdAclZHKfWc0GgHS+ZoCEdAmqglog3cYnV9lChoBkdAcbILAHmig2gHS+5oCEdAmqoDcM3IdXV9lChoBkdAcuCykKu0TmgHTR4BaAhHQJqqD3XZoPF1fZQoaAZHQHAtv863iJhoB0vHaAhHQJqrSuZCv5h1fZQoaAZHQGE8py6tknVoB03oA2gIR0Caq1Zl4C6pdX2UKGgGR0Bx7UpMHryEaAdNEwFoCEdAmqvIgJTl1nV9lChoBkdAcWuFC9h7V2gHS7poCEdAmqwaOtGNJnV9lChoBkdAcRRDMvAXVWgHS8xoCEdAmqxnQpnYhHV9lChoBkdActUechC+lGgHS/JoCEdAmq4ZQDV6NXV9lChoBkdAcIMr5qM3qGgHS+poCEdAmq6Mv24/eXV9lChoBkdAbjhiMo+fRWgHS85oCEdAmq70yckMTnV9lChoBkdAcZ0byYoiLWgHS/RoCEdAmq+co2GZeHV9lChoBkdAcU8qqOtGNWgHS/xoCEdAmq/24qgAZXV9lChoBkdAcPts4ku6E2gHTQgBaAhHQJqwIQTVUdd1fZQoaAZHQGSEqwpvxYtoB03oA2gIR0CasKSr5qM4dX2UKGgGR0BveybUgB91aAdL12gIR0CasQT238XOdX2UKGgGR0Bx2YnJDE3saAdLvmgIR0CasU0tRNypdX2UKGgGR0Bwacmv4dp7aAdLxmgIR0CasZEJ0GNadX2UKGgGR0Bw4kbVBlcyaAdL4WgIR0CassGNJe3QdX2UKGgGR0BwqCPNmlImaAdL2WgIR0Casx+lj3EidX2UKGgGR0BxkKGDcuanaAdNWQFoCEdAmrUJ2t+1B3V9lChoBkdAcfYeK8+Ro2gHS+5oCEdAmrWwJXyRS3V9lChoBkdAbpQAhje9BmgHS9ZoCEdAmrXCdjG1hXV9lChoBkdAU4VnXd0q6WgHS59oCEdAmrZofwI+n3V9lChoBkdAb9WLwWnCO2gHS9ZoCEdAmrb8Q/X5FnV9lChoBkdAb4CxCY1HfGgHS91oCEdAmrcO/tY0VXV9lChoBkdAcYKufEn9emgHS85oCEdAmrdK3uuzQnV9lChoBkdAcYymKIi1RmgHS8loCEdAmrgicLBsRHV9lChoBkdAcz2vWpZOi2gHS/NoCEdAmrjoSHuZ1HV9lChoBkdAbp7SmZVn3GgHS8RoCEdAmrnXWvr4WXV9lChoBkdAcvMpu/Dcd2gHS9loCEdAmrom606YFHV9lChoBkdAX2PJcPe54GgHTegDaAhHQJq8XhNucc51fZQoaAZHQGNa9Sde6ZpoB03oA2gIR0CavMcSoOx0dX2UKGgGR0Bxc8qe9SMtaAdL6mgIR0CavWYkE9t/dX2UKGgGR0BwGkXcgyM2aAdL2mgIR0CavXkeZG8VdX2UKGgGR0By7yXv6TGHaAdL4mgIR0CavcpyZKFqdX2UKGgGR0BwZV4hUzbfaAdL2GgIR0CavhXko4MndX2UKGgGR0BxBxZ9uxbCaAdLzGgIR0CavkRMN+b3dX2UKGgGR0ByAbX6InBtaAdNEwFoCEdAmsCR3V09yXV9lChoBkdAcQgcf/3nIWgHS/NoCEdAmsCwOnVG1HV9lChoBkdAcTS2itaIN2gHS+loCEdAmsEonndO7HV9lChoBkdAc0R1EVnEl2gHS9RoCEdAmsGlA7gbZXV9lChoBkdAcjRCpWFN+WgHTQQBaAhHQJrC8zN2TxJ1fZQoaAZHQG+Gzho/RmdoB0vSaAhHQJrEdS9/SYx1fZQoaAZHQHD8cZgogFJoB0veaAhHQJrEhD6WPcV1fZQoaAZHQG7GULDye7NoB0vOaAhHQJrFo2/BWPt1fZQoaAZHQHMvjpkf9xZoB0vfaAhHQJrF9AD7qIJ1fZQoaAZHQHCg1kH2RJVoB0vKaAhHQJrGLwUg0TF1fZQoaAZHQG8SGEXcgyNoB0vwaAhHQJrHm3Td+G51fZQoaAZHQHAvsEaESM9oB0vOaAhHQJrLP779AHF1fZQoaAZHQHDjHmV7hNxoB0vhaAhHQJrLkp+c6Nl1fZQoaAZHQHEdsyWRigFoB0viaAhHQJrODPmgam51fZQoaAZHQHKmaBI4EOloB0vRaAhHQJrOjjDKoyd1fZQoaAZHQG/RsewLVnVoB0vWaAhHQJrPzDaXa8J1fZQoaAZHQHC31eBxxT9oB0vcaAhHQJrQpCAtnPF1fZQoaAZHQHGbAy2x6fJoB0vPaAhHQJrRgZflZHN1fZQoaAZHQHGvNpRGc4JoB00aAWgIR0Ca0ebjtG/fdX2UKGgGR0BjfLIgeRxMaAdN6ANoCEdAmtIef29L6HV9lChoBkdAY7NNfw7T2GgHTegDaAhHQJrVh/pdKNB1fZQoaAZHQHAZtbgTAWVoB0vkaAhHQJrV0MlTm4l1fZQoaAZHQHDKOJ1q33JoB0v3aAhHQJrWXALy+Yd1fZQoaAZHQGCLdPtUn5VoB03oA2gIR0Ca1t+1SflIdX2UKGgGR0BvcqP+4smOaAdNcQFoCEdAmtbz5Kvmo3V9lChoBkdAbr12lEZzgmgHS9VoCEdAmte3xFy7w3V9lChoBkdAcZ9Eehf0E2gHTQoBaAhHQJrZLlXA/LV1fZQoaAZHQHD4ox+KCQNoB0vnaAhHQJrZaYnfEXN1fZQoaAZHQHL9dJe3QUpoB0vBaAhHQJrZ0pYs/Y91fZQoaAZHQHMk912aDwpoB0vraAhHQJraMwpON5t1fZQoaAZHQHEm36/IsAhoB0vjaAhHQJra1hb4agp1fZQoaAZHQHCHLc9GI9FoB00KAWgIR0Ca2+rMTviMdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 310, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "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"}} |