| {"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 0x7bde9c339fc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bde9c33a050>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bde9c33a0e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bde9c33a170>", "_build": "<function ActorCriticPolicy._build at 0x7bde9c33a200>", "forward": "<function ActorCriticPolicy.forward at 0x7bde9c33a290>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bde9c33a320>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bde9c33a3b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7bde9c33a440>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bde9c33a4d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bde9c33a560>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bde9c33a5f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bde9c4d6ec0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1719949337229856696, "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": 248, "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": 0.999, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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 Tue Jun 18 14:18:04 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |