File size: 13,793 Bytes
e7954b7 |
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 0x7d5671b23be0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d5671b23c70>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d5671b23d00>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d5671b23d90>", "_build": "<function ActorCriticPolicy._build at 0x7d5671b23e20>", "forward": "<function ActorCriticPolicy.forward at 0x7d5671b23eb0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d5671b23f40>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d5671b2c040>", "_predict": "<function ActorCriticPolicy._predict at 0x7d5671b2c0d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d5671b2c160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d5671b2c1f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d5671b2c280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d5671b28ac0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1709216641627673732, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJq1XT5mHQs/6bQ4vohLhb7uGvC8uIccvQAAAAAAAAAAyliDPqMOlj4OiTu+ZrBTvu4xVb0zLyo7AAAAAAAAAABaeTa+rT7rPgfuSj4r80++gJrduxKKBz0AAAAAAAAAADPVH71guSM/neMDPgHDEb6N7AY8uI5YvAAAAAAAAAAAU0wjPgjNzj6rIbu9EVBUvkvCqztywuu8AAAAAAAAAADNeSY9w5cuvBWrqLunkbo8aLGaPSMmmL0AAIA/AACAP+C0BL4nMlo/pP47vXNHkb4rUq69i0acvQAAAAAAAAAAQ6DGPvkhWj+drTE+uUWdvsSyQT46wDi9AAAAAAAAAAANcw4+JJIKPD4khr3JYSu+/l8tOzLGCz8AAIA/AAAAADPTFTovVdg+0iZFPnuOcL7yvZs9NbEyPQAAAAAAAAAAw06vPqcdHj8zcV69U/Frvl0HID2Ghru9AAAAAAAAAABmPJw8gsP/Progqjy+BUi+/JnDPEUDkz0AAAAAAAAAACYCwz1VpGM+QGWXvXMfdL7N7tG8XNcfvQAAAAAAAAAABlowvgAkrj7lkkc+5P6BvkxG/rzKy0e9AAAAAAAAAADaVts9w/kpurin+rZqsEKyKQb6ORTaEjYAAIA/AACAP0Y8NL5RbTU/94qOPorldr4Ah/w7clnXPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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:": "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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"}} |