File size: 14,509 Bytes
0c69fec 271ebcd 0c69fec 271ebcd 0c69fec 271ebcd 4fc7199 0c69fec 4fc7199 0c69fec 4fc7199 0c69fec 271ebcd 0c69fec 271ebcd 0c69fec 271ebcd 0c69fec 271ebcd 0c69fec |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
{
"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 0x7feb678aa310>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7feb678aa3a0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7feb678aa430>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7feb678aa4c0>",
"_build": "<function ActorCriticPolicy._build at 0x7feb678aa550>",
"forward": "<function ActorCriticPolicy.forward at 0x7feb678aa5e0>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7feb678aa670>",
"_predict": "<function ActorCriticPolicy._predict at 0x7feb678aa700>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7feb678aa790>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7feb678aa820>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7feb678aa8b0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7feb678b0660>"
},
"verbose": 1,
"policy_kwargs": {},
"observation_space": {
":type:": "<class 'gym.spaces.box.Box'>",
":serialized:": "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",
"dtype": "float32",
"_shape": [
8
],
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
"high": "[inf inf inf inf inf inf inf inf]",
"bounded_below": "[False False False False False False False False]",
"bounded_above": "[False False False False False False False False]",
"_np_random": null
},
"action_space": {
":type:": "<class 'gym.spaces.discrete.Discrete'>",
":serialized:": "gAWViAAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
"n": 4,
"_shape": [],
"dtype": "int64",
"_np_random": null
},
"n_envs": 16,
"num_timesteps": 5013504,
"_total_timesteps": 5000000.0,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1652608229.6440349,
"learning_rate": 0.0003,
"tensorboard_log": "./logs",
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "gAWVlgIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjGYvaG9tZS9yb2JlcnQxMDAzLy5weWVudi92ZXJzaW9ucy9kZWVwLXJsL2xpYi9weXRob24zLjgvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UaA11Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoF2gOjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoGIwHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
},
"_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": -0.0027007999999999477,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 1224,
"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
} |