toastedshibe's picture
First model
2d54bb8
raw
history blame
No virus
14.7 kB
{
"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 0x7f69e0ebfca0>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f69e0ebfd30>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f69e0ebfdc0>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f69e0ebfe50>",
"_build": "<function ActorCriticPolicy._build at 0x7f69e0ebfee0>",
"forward": "<function ActorCriticPolicy.forward at 0x7f69e0ebff70>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f69e0ec3040>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f69e0ec30d0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f69e0ec3160>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f69e0ec31f0>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f69e0ec3280>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f69e0ebb450>"
},
"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:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
"n": 4,
"_shape": [],
"dtype": "int64",
"_np_random": null
},
"n_envs": 16,
"num_timesteps": 1015808,
"_total_timesteps": 1000000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1671319359957674245,
"learning_rate": 0.0003,
"tensorboard_log": null,
"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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
},
"_last_original_obs": null,
"_episode_num": 0,
"use_sde": false,
"sde_sample_freq": -1,
"_current_progress_remaining": -0.015808000000000044,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVdhAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIARdky3LvYUCUhpRSlIwBbJRN6AOMAXSUR0CkGZoqkM1CdX2UKGgGaAloD0MI7X4V4LuPZUCUhpRSlGgVTegDaBZHQKQfD3225QR1fZQoaAZoCWgPQwhD44kgzs5hQJSGlFKUaBVN6ANoFkdApB8hQm/nGXV9lChoBmgJaA9DCPzHQnQI32RAlIaUUpRoFU3oA2gWR0CkH26nR9gGdX2UKGgGaAloD0MII6MDkrDzYkCUhpRSlGgVTegDaBZHQKQgBZ13dKx1fZQoaAZoCWgPQwhyv0NRoAFiQJSGlFKUaBVN6ANoFkdApCAL7qIJq3V9lChoBmgJaA9DCFhUxOkkf2NAlIaUUpRoFU3oA2gWR0CkIJr433pOdX2UKGgGaAloD0MIw4Nm171nZECUhpRSlGgVTegDaBZHQKQs7x1gYxd1fZQoaAZoCWgPQwgFGmzqPPphQJSGlFKUaBVN6ANoFkdApC1hYPoV23V9lChoBmgJaA9DCPgyUYRUtmFAlIaUUpRoFU3oA2gWR0CkLmXgk1MudX2UKGgGaAloD0MIr3d/vFfaWUCUhpRSlGgVTegDaBZHQKQyakN4JNV1fZQoaAZoCWgPQwj35jdMNCVkQJSGlFKUaBVN6ANoFkdApDKpjz7MxHV9lChoBmgJaA9DCNpWs874cWVAlIaUUpRoFU3oA2gWR0CkM/I5YHPedX2UKGgGaAloD0MITwgddAlfYUCUhpRSlGgVTegDaBZHQKQ51BRhttR1fZQoaAZoCWgPQwgUsYhhh2RhQJSGlFKUaBVN6ANoFkdApDyun62v0XV9lChoBmgJaA9DCBTRr60feGJAlIaUUpRoFU3oA2gWR0CkPPAaNuLrdX2UKGgGaAloD0MIFqQZi6ZOZ0CUhpRSlGgVTegDaBZHQKQ+VhUBGQV1fZQoaAZoCWgPQwiA8KFES/dgQJSGlFKUaBVN6ANoFkdApERIXqJMx3V9lChoBmgJaA9DCJm5wOWxIl5AlIaUUpRoFU3oA2gWR0CkRFxxcVxkdX2UKGgGaAloD0MI5lyKq8oXYUCUhpRSlGgVTegDaBZHQKREtn2ZiNN1fZQoaAZoCWgPQwgcsoF0MfRkQJSGlFKUaBVN6ANoFkdApEVgKtxMnXV9lChoBmgJaA9DCHOCNjn8GGJAlIaUUpRoFU3oA2gWR0CkRWhyKekIdX2UKGgGaAloD0MIOzlDcUdGYUCUhpRSlGgVTegDaBZHQKRGDaV2Rq51fZQoaAZoCWgPQwh+VMN+T9FmQJSGlFKUaBVN6ANoFkdApEmC6QNkOXV9lChoBmgJaA9DCK0yU1p/p2VAlIaUUpRoFU3oA2gWR0CkU2cOkLx7dX2UKGgGaAloD0MIWW5pNaQQZECUhpRSlGgVTegDaBZHQKRUjAqur6t1fZQoaAZoCWgPQwg5Kcx7nM5dQJSGlFKUaBVN6ANoFkdApFkmMERranV9lChoBmgJaA9DCLZnlgQoNGBAlIaUUpRoFU3oA2gWR0CkWW6Ei+tbdX2UKGgGaAloD0MIdLaA0Hp1WUCUhpRSlGgVTegDaBZHQKRazO/tY0V1fZQoaAZoCWgPQwghlPdxNMljQJSGlFKUaBVN6ANoFkdApGFX6KtPpXV9lChoBmgJaA9DCLYTJSGR7GJAlIaUUpRoFU3oA2gWR0CkZARbr1M/dX2UKGgGaAloD0MI5J6u7tjEYkCUhpRSlGgVTegDaBZHQKRkQh/y5I91fZQoaAZoCWgPQwhAbVSng3VkQJSGlFKUaBVN6ANoFkdApGWgHZ9NOHV9lChoBmgJaA9DCGjPZWoS5k1AlIaUUpRoFUu3aBZHQKRqnOj7AL11fZQoaAZoCWgPQwjvqDEh5kJlQJSGlFKUaBVN6ANoFkdApGrNM495hXV9lChoBmgJaA9DCDzAkxauzWdAlIaUUpRoFU3oA2gWR0Ckat0hV2iddX2UKGgGaAloD0MI6GhVSzqtYkCUhpRSlGgVTegDaBZHQKRrJG2kSEl1fZQoaAZoCWgPQwik4CnkSr39v5SGlFKUaBVL+mgWR0Ckaysdkrf+dX2UKGgGaAloD0MInrZGBGORZkCUhpRSlGgVTegDaBZHQKRroy+HrQh1fZQoaAZoCWgPQwgLl1XYDKNlQJSGlFKUaBVN6ANoFkdApGupLIxQBXV9lChoBmgJaA9DCBNIiV3b7GBAlIaUUpRoFU3oA2gWR0CkbCJrk8zRdX2UKGgGaAloD0MIq1/pfPiGZkCUhpRSlGgVTegDaBZHQKRulPY4ACJ1fZQoaAZoCWgPQwjpYP2fw7hfQJSGlFKUaBVN6ANoFkdApG73trsSkHV9lChoBmgJaA9DCAUyO4tezGNAlIaUUpRoFU3oA2gWR0CkeUL433pOdX2UKGgGaAloD0MIiGTIsfVUW0CUhpRSlGgVTegDaBZHQKR9DH9WIXV1fZQoaAZoCWgPQwhMVdriGndkQJSGlFKUaBVN6ANoFkdApH1IRChN/XV9lChoBmgJaA9DCLuZ0Y+GoUhAlIaUUpRoFUvzaBZHQKR+QiX6ZYx1fZQoaAZoCWgPQwjXTL7Z5oNkQJSGlFKUaBVN6ANoFkdApH6KBPKuCHV9lChoBmgJaA9DCLqkarsJGklAlIaUUpRoFUvRaBZHQKSD4SNfgJl1fZQoaAZoCWgPQwi37BD/MC5kQJSGlFKUaBVN6ANoFkdApIRUfT1CgXV9lChoBmgJaA9DCO0MU1vqFFJAlIaUUpRoFUv4aBZHQKSFSjB2wFF1fZQoaAZoCWgPQwiFzJVBtVRmQJSGlFKUaBVN6ANoFkdApIbEbDMvAXV9lChoBmgJaA9DCCI17WIaR2VAlIaUUpRoFU3oA2gWR0CkjXvhAGB4dX2UKGgGaAloD0MIl6q0xbVwZUCUhpRSlGgVTegDaBZHQKSNrhVlwtJ1fZQoaAZoCWgPQwjvqZz2lKFnQJSGlFKUaBVN6ANoFkdApI3AqXnhbXV9lChoBmgJaA9DCGnjiLX4HWJAlIaUUpRoFU3oA2gWR0Ckjgc4xUNsdX2UKGgGaAloD0MIM9/BTxxwY0CUhpRSlGgVTegDaBZHQKSODYU34sV1fZQoaAZoCWgPQwikcD0KV19lQJSGlFKUaBVN6ANoFkdApI6LA1vVE3V9lChoBmgJaA9DCCVbXU6J82lAlIaUUpRoFU3oA2gWR0CkjpCYCyQgdX2UKGgGaAloD0MIsU6V75mlaECUhpRSlGgVTegDaBZHQKSPCP9UCJZ1fZQoaAZoCWgPQwhAwcWKmuNlQJSGlFKUaBVN6ANoFkdApJFvpyIYWXV9lChoBmgJaA9DCMOdCyO9PkhAlIaUUpRoFUvUaBZHQKSSCo86mwd1fZQoaAZoCWgPQwhNLVvrC4NmQJSGlFKUaBVN6ANoFkdApJKhzaK1onV9lChoBmgJaA9DCHjsZ7GUsmVAlIaUUpRoFU3oA2gWR0Ckn+USRKYidX2UKGgGaAloD0MI8gwa+icFZ0CUhpRSlGgVTegDaBZHQKSgJ1EmY0F1fZQoaAZoCWgPQwjJrx9iA0xkQJSGlFKUaBVN6ANoFkdApKgRREWqLnV9lChoBmgJaA9DCOuqQC0GDWhAlIaUUpRoFU3oA2gWR0CkqJyXD3uedX2UKGgGaAloD0MI5/9VR46AZECUhpRSlGgVTegDaBZHQKSpqZiNKiB1fZQoaAZoCWgPQwgmqOFb2ExkQJSGlFKUaBVN6ANoFkdApKtO+PBBRnV9lChoBmgJaA9DCM3MzMxMI2JAlIaUUpRoFU3oA2gWR0Cksq6NMoMKdX2UKGgGaAloD0MI0zHnGfvWX0CUhpRSlGgVTegDaBZHQKSy/ltCRfZ1fZQoaAZoCWgPQwhYPPVIA/1gQJSGlFKUaBVN6ANoFkdApLNRqIrOJXV9lChoBmgJaA9DCIkl5e7zQmZAlIaUUpRoFU3oA2gWR0Cks1hNVR1pdX2UKGgGaAloD0MIqb7zixL5ZECUhpRSlGgVTegDaBZHQKSz6VqveP91fZQoaAZoCWgPQwi3Qe239uRjQJSGlFKUaBVN6ANoFkdApLPwCyQgcXV9lChoBmgJaA9DCPopjgOvL19AlIaUUpRoFU3oA2gWR0CktHwMhHLBdX2UKGgGaAloD0MIxLKZQ1IGZUCUhpRSlGgVTegDaBZHQKS3EnRb8m91fZQoaAZoCWgPQwii68IPTllgQJSGlFKUaBVN6ANoFkdApLe9lXiiqXV9lChoBmgJaA9DCDwUBfpE1klAlIaUUpRoFUu6aBZHQKS3/LteD4B1fZQoaAZoCWgPQwjncoOhDpxiQJSGlFKUaBVN6ANoFkdApLhf3ai9I3V9lChoBmgJaA9DCDbIJCPneGJAlIaUUpRoFU3oA2gWR0CkxajTSb6QdX2UKGgGaAloD0MISu6wicxSZECUhpRSlGgVTegDaBZHQKTF57PY4AF1fZQoaAZoCWgPQwjicyfYf/9gQJSGlFKUaBVN6ANoFkdApM0n7SApa3V9lChoBmgJaA9DCHTU0XE15GRAlIaUUpRoFU3oA2gWR0CkzaOerdWRdX2UKGgGaAloD0MIPZrqyXxxZUCUhpRSlGgVTegDaBZHQKTOn3V09yN1fZQoaAZoCWgPQwiuRnalZQNfQJSGlFKUaBVN6ANoFkdApNAemWMS9XV9lChoBmgJaA9DCDXtYprp21RAlIaUUpRoFUvRaBZHQKTTS+/xlQN1fZQoaAZoCWgPQwhNZyeDo6pJQJSGlFKUaBVL0GgWR0Ck1CnJtBOYdX2UKGgGaAloD0MIWOGWjyQCY0CUhpRSlGgVTegDaBZHQKTWcuM+/xl1fZQoaAZoCWgPQwhSKXY0DkdhQJSGlFKUaBVN6ANoFkdApNa2ez2OAHV9lChoBmgJaA9DCAEvM2wUCGBAlIaUUpRoFU3oA2gWR0Ck1vvva11GdX2UKGgGaAloD0MICMvY0M3mZUCUhpRSlGgVTegDaBZHQKTXAm8/Uvx1fZQoaAZoCWgPQwjSbvQxH9RjQJSGlFKUaBVN6ANoFkdApNeFMCcPOXV9lChoBmgJaA9DCNEEiljE3mBAlIaUUpRoFU3oA2gWR0Ck2A0oScsldX2UKGgGaAloD0MIZtr+lRXRZUCUhpRSlGgVTegDaBZHQKTan2Dg62h1fZQoaAZoCWgPQwi858ByhFdlQJSGlFKUaBVN6ANoFkdApNtTWsijcnV9lChoBmgJaA9DCJ+tg4O990VAlIaUUpRoFUvVaBZHQKTbZsKsuFp1fZQoaAZoCWgPQwgPgSOBhqhiQJSGlFKUaBVN6ANoFkdApNuVknTiKnV9lChoBmgJaA9DCPWB5J1D2SDAlIaUUpRoFUvWaBZHQKTbrDu0CzV1fZQoaAZoCWgPQwhOgGH589ZkQJSGlFKUaBVN6ANoFkdApNv2bAk9lnVlLg=="
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 248,
"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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
},
"clip_range_vf": null,
"normalize_advantage": true,
"target_kl": null
}