| {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnNhYy5wb2xpY2llc5SMCVNBQ1BvbGljeZSTlC4=", "__module__": "stable_baselines3.sac.policies", "__doc__": "\n Policy class (with both actor and critic) for SAC.\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 use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\n :param use_expln: Use ``expln()`` function instead of ``exp()`` when using gSDE 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 clip_mean: Clip the mean output when using gSDE to avoid numerical instability.\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 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 :param n_critics: Number of critic networks to create.\n :param share_features_extractor: Whether to share or not the features extractor\n between the actor and the critic (this saves computation time)\n ", "__init__": "<function SACPolicy.__init__ at 0x7f1542924550>", "_build": "<function SACPolicy._build at 0x7f15429245e0>", "_get_constructor_parameters": "<function SACPolicy._get_constructor_parameters at 0x7f1542924670>", "reset_noise": "<function SACPolicy.reset_noise at 0x7f1542924700>", "make_actor": "<function SACPolicy.make_actor at 0x7f1542924790>", "make_critic": "<function SACPolicy.make_critic at 0x7f1542924820>", "forward": "<function SACPolicy.forward at 0x7f15429248b0>", "_predict": "<function SACPolicy._predict at 0x7f1542924940>", "set_training_mode": "<function SACPolicy.set_training_mode at 0x7f15429249d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f1542a11d40>"}, "verbose": 0, "policy_kwargs": {"use_sde": false}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [24], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "bounded_below": "[ True True True True]", "bounded_above": "[ True True True True]", "_np_random": "RandomState(MT19937)"}, "n_envs": 1, "num_timesteps": 500000, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": 3578334683, "action_noise": null, "start_time": 1654335548.3293495, "learning_rate": 0.0003, "tensorboard_log": "./logs/", "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV1QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZgAAAAAAAAAAlxvj6YfqW8dzADP2Q9y7uSttI9/f9/P+iwpr5/LNG+AAAAAN+1Jz/+/3+/UNaPvQEAgD8AAAAAt1nePo0x4z5hYO8+amYBPz8zDj/BSCE/QPo+PxF9ZT8AAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsYhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV1QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZgAAAAAAAAAFeUwz6IOoe8deYCP4+n+TsqV8E8AwCAP8Rtj77sWmC/AAAAABFNPD8BAIC/EDRGvv3/fz8AAAAAW1fePgd34j4Rie4+vzsBP89ODj/dGSE/8m4/PwmeZj8AAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsYhpSMAUOUdJRSlC4="}, "_episode_num": 491, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 499900, "buffer_size": 1000000, "batch_size": 256, "learning_starts": 100, "tau": 0.005, "gamma": 0.99, "gradient_steps": 1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==", "__module__": "stable_baselines3.common.buffers", "__doc__": "\n Replay buffer used in off-policy algorithms like SAC/TD3.\n\n :param buffer_size: Max number of element in the buffer\n :param observation_space: Observation space\n :param action_space: Action space\n :param device:\n :param n_envs: Number of parallel environments\n :param optimize_memory_usage: Enable a memory efficient variant\n of the replay buffer which reduces by almost a factor two the memory used,\n at a cost of more complexity.\n See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n separately and treat the task as infinite horizon task.\n https://github.com/DLR-RM/stable-baselines3/issues/284\n ", "__init__": "<function ReplayBuffer.__init__ at 0x7f154296d3a0>", "add": "<function ReplayBuffer.add at 0x7f154296d430>", "sample": "<function ReplayBuffer.sample at 0x7f154296d4c0>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7f154296d550>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f1542a1ec00>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "target_entropy": {":type:": "<class 'numpy.float32'>", ":serialized:": "gAWVZQAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMEAACAwJSGlFKULg=="}, "ent_coef": "auto", "target_update_interval": 1, "system_info": {"OS": "Linux-5.13.0-44-generic-x86_64-with-glibc2.31 #49~20.04.1-Ubuntu SMP Wed May 18 18:44:28 UTC 2022", "Python": "3.9.12", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu102", "GPU Enabled": "True", "Numpy": "1.21.5", "Gym": "0.21.0"}} |