File size: 13,789 Bytes
ebfde1d |
1 |
{"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 0x7a60c4466050>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a60c44660e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a60c4466170>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a60c4466200>", "_build": "<function ActorCriticPolicy._build at 0x7a60c4466290>", "forward": "<function ActorCriticPolicy.forward at 0x7a60c4466320>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a60c44663b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a60c4466440>", "_predict": "<function ActorCriticPolicy._predict at 0x7a60c44664d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a60c4466560>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a60c44665f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a60c4466680>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a60c4402000>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1709926513410471575, "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:": "gAWVQQwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQG5myyD7IkuMAWyUTT4BjAF0lEdAmICDK1XvIHV9lChoBkdAcGy+dsi0OWgHTSgBaAhHQJiB+SW7e2x1fZQoaAZHQHDNDlcQiA5oB01MAWgIR0CYghFPznRtdX2UKGgGR0Bx6sX+ERJ3aAdNNwFoCEdAmIJBmXgLqnV9lChoBkdAcslHKwIMSmgHTTABaAhHQJiCyvt+kQB1fZQoaAZHQHIi4caOxSpoB00tAWgIR0CYg8tUGVzIdX2UKGgGR0BwxTiDM/yHaAdNJQFoCEdAmIP18LKFI3V9lChoBkdAcm2bpu/DcmgHTUEBaAhHQJiEG+SKWLR1fZQoaAZHQHKgiBshxHZoB01eAWgIR0CYhSBD5TIedX2UKGgGR0BwQ45wOvt/aAdNEwFoCEdAmIW3Adn003V9lChoBkdAbtJHCGetjmgHTUUBaAhHQJiGZ8ma6SV1fZQoaAZHQHFKxpYcNpdoB01LAWgIR0CYhrK+SKWLdX2UKGgGR0ByNJIpYs/ZaAdNJgFoCEdAmIjNSIgvDnV9lChoBkdAccI3bmEGq2gHTSkBaAhHQJiJsl7dBSl1fZQoaAZHQHFZJ/CqIadoB00mAWgIR0CYic/2kBS2dX2UKGgGR0Bx9mM72criaAdNQgFoCEdAmIofWtlqanV9lChoBkdAcFzAggX/HmgHTQoBaAhHQJiKn0Gu9vl1fZQoaAZHQHIbmitaIN5oB01UAWgIR0CYi+gLqlgudX2UKGgGR0BxtOQkona4aAdNOQFoCEdAmIzSOzY29HV9lChoBkdAcA2zWwu/UWgHTUEBaAhHQJiNcYDTz/Z1fZQoaAZHQGz/EfcN6PdoB00rAWgIR0CYjqTSsr/bdX2UKGgGR0BwjFefI0ZWaAdNMwFoCEdAmI+LbxmTT3V9lChoBkdAcXEOFg2If2gHTXEBaAhHQJiQf8AJb+t1fZQoaAZHQHCmWNzbN8poB00tAWgIR0CYkMTho/RmdX2UKGgGR0ByMa4gA6uGaAdNXwFoCEdAmJFMXizcAXV9lChoBkdAcVcZkTYdyWgHTSMBaAhHQJiSRUT+NtJ1fZQoaAZHQHHECzollbxoB00vAWgIR0CYkk2aUiY+dX2UKGgGR0Bw9WTmnwXqaAdNTgFoCEdAmJJ9NFjNIXV9lChoBkdAQhM9W6shgWgHS99oCEdAmJMaBRQ793V9lChoBkdAcdBcH4XXRWgHTR0BaAhHQJiUsyVObiJ1fZQoaAZHQGyHxoh6jWVoB01HAWgIR0CYlXOtnwocdX2UKGgGR0ByF0JVsDW9aAdNJgFoCEdAmJWke2d/a3V9lChoBkdAcL2aDwpe/2gHTT4BaAhHQJiXaXjU/fR1fZQoaAZHQHJpja0x/NJoB000AWgIR0CYl88jRlYmdX2UKGgGR0BwHP4zrNW3aAdNigFoCEdAmJiCfthNNHV9lChoBkdAROYbXHzYmWgHS+5oCEdAmJjgX2ugYnV9lChoBkdAcg1qXnhbW2gHTRgBaAhHQJiY+lBQemx1fZQoaAZHQHCZdyYG+sZoB01TAWgIR0CYmWJVsDW9dX2UKGgGR0Bs4ECo0hvBaAdNNwFoCEdAmJrO9SMtLHV9lChoBkdAbN2+mFaje2gHTUgBaAhHQJibLjdYW+J1fZQoaAZHQHES89bHIZJoB00cAWgIR0CYm6Z+hGpddX2UKGgGR0Bv/58neBQOaAdNJgFoCEdAmJu8w+MZP3V9lChoBkdAcKU0uUUwjGgHTZQBaAhHQJicT5ULlV91fZQoaAZHQHDgnVPN3W5oB01IAWgIR0CYnK6K+BYndX2UKGgGR0BwZgTTOPeYaAdNRwFoCEdAmKBCMYMvy3V9lChoBkdAck+DdxhlUmgHTXoBaAhHQJihKslsxfx1fZQoaAZHQHBiR15jYqZoB00jAWgIR0CYoWM98qnWdX2UKGgGR0BwF4oScslLaAdNLwFoCEdAmLPmOZLIxXV9lChoBkdAceUkE9t/F2gHTZ0BaAhHQJi0NQKrq+t1fZQoaAZHQHIFQv6CUX5oB01mAWgIR0CYtGL/CIk7dX2UKGgGR0BvnA8fV7QcaAdNTQFoCEdAmLSQkcCHRHV9lChoBkdAcjX4rSVnmWgHTVYBaAhHQJi1WYiPhhp1fZQoaAZHQHCNhR64UexoB01IAWgIR0CYtW3bmEGrdX2UKGgGR0BvXMH6dlNDaAdNQAFoCEdAmLavcJtzjnV9lChoBkdAb7PdDYywfWgHTTkBaAhHQJi20yJsO5J1fZQoaAZHQHDEde2NNrVoB01OAWgIR0CYuAN1yNn5dX2UKGgGR0Bw8Ewj+rEMaAdNTQFoCEdAmLgTnJT2nXV9lChoBkdAcR1kUKzAvmgHTVABaAhHQJi4w5tFa0R1fZQoaAZHQGyWAOrhispoB01FAWgIR0CYuOm5UcXFdX2UKGgGR0BxsD779AHFaAdNCQFoCEdAmLrPa+N96XV9lChoBkdAbQCDRMN+b2gHTRQBaAhHQJi8RUPxx1h1fZQoaAZHQG8QcbBGhEloB00BAWgIR0CYvmnXNC7cdX2UKGgGR0BwBGa8Yht+aAdNPQFoCEdAmL5pEx7AtXV9lChoBkdAcKugmqo60mgHTREBaAhHQJi+w6Lfk3l1fZQoaAZHQHIl5mEoOQRoB0v6aAhHQJi+//Q0GeN1fZQoaAZHQHE4GrsByS5oB01IAWgIR0CYwNu4PPLQdX2UKGgGR0BxDJ5UtI07aAdNPAFoCEdAmMHedK/VRXV9lChoBkdAcLBTb349HWgHTV4BaAhHQJjCJydWhh91fZQoaAZHQHKsN07r9l5oB007AWgIR0CYwwKB/ZuidX2UKGgGR0BzGkKNQ0oCaAdNHQFoCEdAmMQbRBu4w3V9lChoBkdAcWI1Ng0CR2gHTT0BaAhHQJjEXJYDDCR1fZQoaAZHQHKHeUQkHD9oB02CAWgIR0CYxY8JUo8ZdX2UKGgGR0BwCuGYa5wwaAdNRAFoCEdAmMWlDKHO8nV9lChoBkdAcuEi8Fpwj2gHTWUBaAhHQJjF2BI4EOl1fZQoaAZHQHD94AOrhitoB00MAWgIR0CYxojhUBGQdX2UKGgGR0By5Fky1uzhaAdNNwFoCEdAmMbXfEXLvHV9lChoBkdATUXEyckMTmgHTegDaAhHQJjHTKifxtp1fZQoaAZHQHGED238XN1oB00EAWgIR0CYx8EIPbwjdX2UKGgGR0Bx6cGVzIV/aAdNHgFoCEdAmMh8jNY8uHV9lChoBkdAbkQ371qWT2gHTR4BaAhHQJjIt6qsEJV1fZQoaAZHQG5NsLORkmRoB005AWgIR0CYyaW2PT5PdX2UKGgGR0BwmZRUFSsKaAdNRwFoCEdAmMt3zxwyZnV9lChoBkdAbsFO6/ZdwGgHTRkBaAhHQJjMD4Kx9oh1fZQoaAZHQG/5wFTvRZ5oB01dAWgIR0CYzUAdn004dX2UKGgGR0BzCJJFspG4aAdNAgFoCEdAmM366e5Fw3V9lChoBkdAb64lSjxkNGgHTUQBaAhHQJjO6lVLi/B1fZQoaAZHQHN2wlByCFtoB009AWgIR0CYzvDK5kLAdX2UKGgGR0BwVpAE+xGEaAdNmwFoCEdAmM/SydFvynV9lChoBkdAbvqWuX/o7mgHTS4BaAhHQJjP5N7Bwdd1fZQoaAZHQHEp26f8MuxoB01DAWgIR0CY0FlyR0U5dX2UKGgGR0BxZ0dmxt52aAdNQQFoCEdAmNEmkvboKXV9lChoBkdAcslrrgOz6mgHTR0BaAhHQJjRQSqU/wB1fZQoaAZHQG04ldTo+wFoB008AWgIR0CY0UmzjWCmdX2UKGgGR0Bya2h0yP+5aAdNQQFoCEdAmNHS1iONpHV9lChoBkdAcHsL/S6UaGgHTQYBaAhHQJjSXg0j1PF1fZQoaAZHQHMp1ByCFsZoB01LAWgIR0CY0zEgGKQ8dX2UKGgGR0BxXSgpSaVlaAdNUwFoCEdAmNOecH4XXXV9lChoBkdAcS63qAz55GgHTRUBaAhHQJjUvK1XvH91fZQoaAZHQHGkF8kUsWhoB000AWgIR0CY1TCZF5OadX2UKGgGR0BunOCXhOxjaAdNAwFoCEdAmNW+m78Nx3VlLg=="}, "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:": "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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-6.1.58+-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": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |