File size: 16,843 Bytes
176f060 |
1 |
{"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 0x7c04346f31c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c04346e78c0>"}, "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": 100000, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1699956015514666505, "learning_rate": 0.001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 1.0131204 0.65246 0.09613826]\n [-1.0647786 1.2641424 0.09612502]\n [-0.9569316 0.7762045 0.09614781]\n [ 0.10646102 0.43933895 0.09614013]]", "desired_goal": "[[ 0.32533327 1.1495657 1.2207608 ]\n [ 0.3641693 -0.09886481 -1.0680615 ]\n [ 0.79944146 1.5528954 0.890744 ]\n [ 0.7672398 0.88864666 -0.06288737]]", "observation": "[[-2.49877200e-02 -1.65018928e+00 2.67355633e+00 -6.74841052e-04\n -5.44881046e-01 -5.55607736e-01 1.08634949e+00 1.01312041e+00\n 6.52459979e-01 9.61382613e-02 1.75960101e-02 -4.74587409e-03\n -2.15755533e-02 3.01601365e-02 -2.34746709e-02 4.37211581e-02\n 7.58658163e-03 -1.45833828e-02 -6.95723342e-03]\n [ 3.17193806e-01 8.03514123e-01 -8.26891720e-01 6.89840317e-01\n 1.60606372e+00 2.71086283e-02 -8.57730806e-01 -1.06477857e+00\n 1.26414239e+00 9.61250216e-02 1.79469772e-02 -4.95756324e-03\n -2.15394702e-02 2.99018007e-02 -2.33570356e-02 4.37211581e-02\n 7.58658163e-03 -1.45833837e-02 -6.97299140e-03]\n [ 7.91415989e-01 -1.97480842e-01 1.59428328e-01 1.01524115e-01\n -1.32420731e+00 -7.79548109e-01 -8.65536511e-01 -9.56931591e-01\n 7.76204526e-01 9.61478129e-02 1.75930168e-02 -5.17507782e-03\n -2.19210014e-02 3.06696352e-02 -2.36881655e-02 4.34689187e-02\n 9.31731239e-03 -1.19818216e-02 -6.98422687e-03]\n [ 3.27338517e-01 -8.28469872e-01 1.85437381e+00 6.52808249e-01\n -5.04097819e-01 1.76992774e-01 -6.06765270e-01 1.06461018e-01\n 4.39338952e-01 9.61401314e-02 1.77440401e-02 -4.88892337e-03\n -2.07924247e-02 3.06169800e-02 -2.37557348e-02 4.37214598e-02\n 7.58720562e-03 -1.45856412e-02 -6.28469279e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.1031069 -0.07460346 0.02 ]\n [-0.03153889 -0.09806556 0.02 ]\n [-0.1452734 0.11326393 0.02 ]\n [-0.06804081 0.06569903 0.02 ]]", "desired_goal": "[[ 0.00373425 -0.05589372 0.02 ]\n [-0.10333369 -0.07600621 0.13447206]\n [ 0.01467175 0.14698918 0.07781588]\n [ 0.12834817 -0.1231351 0.16896348]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00 0.0000000e+00 1.0310690e-01\n -7.4603461e-02 2.0000000e-02 0.0000000e+00 -0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n 0.0000000e+00 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 0.0000000e+00 -3.1538885e-02\n -9.8065555e-02 2.0000000e-02 0.0000000e+00 -0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n 0.0000000e+00 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 0.0000000e+00 -1.4527340e-01\n 1.1326393e-01 2.0000000e-02 0.0000000e+00 -0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n 0.0000000e+00 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 0.0000000e+00 -6.8040811e-02\n 6.5699026e-02 2.0000000e-02 0.0000000e+00 -0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n 0.0000000e+00 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": 5000, "n_steps": 5, "gamma": 0.95, "gae_lambda": 0.96, "ent_coef": 0.004, "vf_coef": 0.1, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gymnasium.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (19,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True]", "bounded_above": "[ True True True True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuDQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz9QYk3S8an8hZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}} |