File size: 16,004 Bytes
e151aa4 |
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 95 96 |
{
"policy_class": {
":type:": "<class 'abc.ABCMeta'>",
":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=",
"__module__": "stable_baselines3.common.policies",
"__doc__": "\n MultiInputActorClass 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 (Tuple)\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: Uses the CombinedExtractor\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 MultiInputActorCriticPolicy.__init__ at 0x7fe0a49c0f70>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x7fe0a49c6600>"
},
"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.dict.Dict'>",
":serialized:": "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",
"spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])",
"_shape": null,
"dtype": null,
"_np_random": null
},
"action_space": {
":type:": "<class 'gym.spaces.box.Box'>",
":serialized:": "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",
"dtype": "float32",
"_shape": [
3
],
"low": "[-1. -1. -1.]",
"high": "[1. 1. 1.]",
"bounded_below": "[ True True True]",
"bounded_above": "[ True True True]",
"_np_random": null
},
"n_envs": 4,
"num_timesteps": 1000000,
"_total_timesteps": 1000000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1678608982071079812,
"learning_rate": 0.00096,
"tensorboard_log": null,
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/T3UQTVUdaYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
},
"_last_obs": {
":type:": "<class 'collections.OrderedDict'>",
":serialized:": "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",
"achieved_goal": "[[0.42323112 0.009193 0.55800956]\n [0.42323112 0.009193 0.55800956]\n [0.42323112 0.009193 0.55800956]\n [0.42323112 0.009193 0.55800956]]",
"desired_goal": "[[ 0.37439784 -1.0713502 1.5974844 ]\n [-1.2732115 -0.22081712 0.99808866]\n [-1.081657 -1.248552 -1.5707419 ]\n [-1.1083747 0.42088178 0.37963083]]",
"observation": "[[ 0.42323112 0.009193 0.55800956 0.08075987 -0.00070955 0.0645056 ]\n [ 0.42323112 0.009193 0.55800956 0.08075987 -0.00070955 0.0645056 ]\n [ 0.42323112 0.009193 0.55800956 0.08075987 -0.00070955 0.0645056 ]\n [ 0.42323112 0.009193 0.55800956 0.08075987 -0.00070955 0.0645056 ]]"
},
"_last_episode_starts": {
":type:": "<class 'numpy.ndarray'>",
":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
},
"_last_original_obs": {
":type:": "<class 'collections.OrderedDict'>",
":serialized:": "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",
"achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]",
"desired_goal": "[[-0.03303458 -0.06665558 0.26075318]\n [-0.00422351 -0.00225181 0.10195413]\n [-0.06132492 0.10022148 0.21222456]\n [-0.11137662 -0.00669259 0.05941276]]",
"observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"
},
"_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": 31250,
"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
} |