| {"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 0x7e01cfbc2200>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e01cfbc22a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e01cfbc2340>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e01cfbc23e0>", "_build": "<function ActorCriticPolicy._build at 0x7e01cfbc2480>", "forward": "<function ActorCriticPolicy.forward at 0x7e01cfbc2520>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e01cfbc25c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e01cfbc2660>", "_predict": "<function ActorCriticPolicy._predict at 0x7e01cfbc2700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e01cfbc27a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e01cfbc2840>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e01cfbc28e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e01cffa3440>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 114688, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1743822090534474687, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.1468799999999999, "_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": 32, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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:": "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": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |