File size: 14,862 Bytes
bea3b42 |
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 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()`` 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 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 0x7f25b7182040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f25b71820d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f25b7182160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f25b71821f0>", "_build": "<function ActorCriticPolicy._build at 0x7f25b7182280>", "forward": "<function ActorCriticPolicy.forward at 0x7f25b7182310>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f25b71823a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f25b7182430>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f25b71824c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f25b7182550>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f25b71825e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f25b717ad80>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWViwIAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWHAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlGgHjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxyFlIwBQ5R0lFKUjA1ib3VuZGVkX2Fib3ZllGgQKJYcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUaBRLHIWUaBh0lFKUjAZfc2hhcGWUSxyFlIwDbG93lGgQKJZwAAAAAAAAAAAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP+UaApLHIWUaBh0lFKUjARoaWdolGgQKJZwAAAAAAAAAAAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH+UaApLHIWUaBh0lFKUjAhsb3dfcmVwcpSMBC1pbmaUjAloaWdoX3JlcHKUjANpbmaUjApfbnBfcmFuZG9tlE51Yi4=", "dtype": "float32", "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\n 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\n False False False False]", "_shape": [28], "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 -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 inf inf inf inf]", "low_repr": "-inf", "high_repr": "inf", "_np_random": null}, "action_space": {":type:": "<class 'gym.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": "[-1. -1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": "RandomNumberGenerator(PCG64)"}, "n_envs": 4, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1658701308.641238, "learning_rate": 0.00096, "tensorboard_log": "./tensorboard", "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 0, "use_sde": true, "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": 62500, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.15.0-41-generic-x86_64-with-glibc2.29 #44~20.04.1-Ubuntu SMP Fri Jun 24 13:27:29 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.6.0", "PyTorch": "1.8.2+cu111", "GPU Enabled": "True", "Numpy": "1.23.1", "Gym": "0.24.0"}} |