a2c-PandaReachDense-v2 / config.json
jjhonny's picture
Initial commit
2c82912
{"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 0x7fb09c791360>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fb09c787880>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1686335645294122136, "learning_rate": 0.0001, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[0.13865466 0.02350399 0.53290206]\n [0.13865466 0.02350399 0.53290206]\n [0.13865466 0.02350399 0.53290206]\n [0.13865466 0.02350399 0.53290206]]", "desired_goal": "[[ 0.09113 -1.3520343 -1.2920316 ]\n [-1.298023 -1.0841117 0.21689503]\n [-0.5362582 1.1762043 1.5096208 ]\n [-0.09774249 -0.52937776 -0.4983788 ]]", "observation": "[[0.13865466 0.02350399 0.53290206 0.00151704 0.00253231 0.02592507]\n [0.13865466 0.02350399 0.53290206 0.00151704 0.00253231 0.02592507]\n [0.13865466 0.02350399 0.53290206 0.00151704 0.00253231 0.02592507]\n [0.13865466 0.02350399 0.53290206 0.00151704 0.00253231 0.02592507]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAwLfJvQWlDT0Zous89+oFvuRYvD2kruQ7SwGzPYrMGD7cngY+VY1GPD8KnT2kN7o9lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==", "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": "[[-0.09849501 0.0345812 0.02876382]\n [-0.13077913 0.09196642 0.00697883]\n [ 0.08740481 0.14921775 0.13146538]\n [ 0.01211866 0.0766797 0.09092644]]", "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": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "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": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "gAWVWAMAAAAAAACMD2d5bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwOZ3ltLnNwYWNlcy5ib3iUjANCb3iUk5QpgZR9lCiMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowGX3NoYXBllEsDhZSMA2xvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZSMAUOUdJRSlIwEaGlnaJRoHiiWDAAAAAAAAAAAACBBAAAgQQAAIEGUaBZLA4WUaCF0lFKUjA1ib3VuZGVkX2JlbG93lGgeKJYDAAAAAAAAAAEBAZRoE4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksDhZRoIXSUUpSMDWJvdW5kZWRfYWJvdmWUaB4olgMAAAAAAAAAAQEBlGgtSwOFlGghdJRSlIwKX25wX3JhbmRvbZROdWKMDGRlc2lyZWRfZ29hbJRoDSmBlH2UKGgQaBZoGUsDhZRoG2geKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZRoIXSUUpRoJGgeKJYMAAAAAAAAAAAAIEEAACBBAAAgQZRoFksDhZRoIXSUUpRoKWgeKJYDAAAAAAAAAAEBAZRoLUsDhZRoIXSUUpRoM2geKJYDAAAAAAAAAAEBAZRoLUsDhZRoIXSUUpRoOE51YowLb2JzZXJ2YXRpb26UaA0pgZR9lChoEGgWaBlLBoWUaBtoHiiWGAAAAAAAAAAAACDBAAAgwQAAIMEAACDBAAAgwQAAIMGUaBZLBoWUaCF0lFKUaCRoHiiWGAAAAAAAAAAAACBBAAAgQQAAIEEAACBBAAAgQQAAIEGUaBZLBoWUaCF0lFKUaCloHiiWBgAAAAAAAAABAQEBAQGUaC1LBoWUaCF0lFKUaDNoHiiWBgAAAAAAAAABAQEBAQGUaC1LBoWUaCF0lFKUaDhOdWJ1aBlOaBBOaDhOdWIu", "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:": "gAWVcwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLA4WUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWDAAAAAAAAAAAAIC/AACAvwAAgL+UaAtLA4WUjAFDlHSUUpSMBGhpZ2iUaBMolgwAAAAAAAAAAACAPwAAgD8AAIA/lGgLSwOFlGgWdJRSlIwNYm91bmRlZF9iZWxvd5RoEyiWAwAAAAAAAAABAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLA4WUaBZ0lFKUjA1ib3VuZGVkX2Fib3ZllGgTKJYDAAAAAAAAAAEBAZRoIksDhZRoFnSUUpSMCl9ucF9yYW5kb22UTnViLg==", "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, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}