| {"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 0x7afe05c05120>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7afe05c051c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7afe05c05260>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7afe05c05300>", "_build": "<function ActorCriticPolicy._build at 0x7afe05c053a0>", "forward": "<function ActorCriticPolicy.forward at 0x7afe05c05440>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7afe05c054e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7afe05c05580>", "_predict": "<function ActorCriticPolicy._predict at 0x7afe05c05620>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7afe05c056c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7afe05c05760>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7afe05c05800>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7afe05d74f80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1741976607594137946, "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:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 350, "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": 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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "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"}} |