a2c-PandaReachDense-v2 / config.json
taoist's picture
Initial commit
a754627
{"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 0x7fddd1e4c3a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fddd1e4d300>"}, "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": 1681988085875497960, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/RvAGjbi6x4WUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.40291974 -0.02652646 0.5738108 ]\n [ 0.40291974 -0.02652646 0.5738108 ]\n [ 0.40291974 -0.02652646 0.5738108 ]\n [ 0.40291974 -0.02652646 0.5738108 ]]", "desired_goal": "[[-1.0495932 -1.2659492 0.08244027]\n [ 1.0036919 0.5202433 1.3394775 ]\n [-0.3180706 -1.2932965 0.07959805]\n [-1.3662211 1.5339736 -0.035757 ]]", "observation": "[[ 0.40291974 -0.02652646 0.5738108 -0.01786557 -0.00437002 -0.00797547]\n [ 0.40291974 -0.02652646 0.5738108 -0.01786557 -0.00437002 -0.00797547]\n [ 0.40291974 -0.02652646 0.5738108 -0.01786557 -0.00437002 -0.00797547]\n [ 0.40291974 -0.02652646 0.5738108 -0.01786557 -0.00437002 -0.00797547]]"}, "_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": "[[ 0.01634372 -0.13050544 0.2308379 ]\n [ 0.04079172 0.09543671 0.27191588]\n [ 0.0090065 0.01048753 0.23353498]\n [-0.03796219 -0.02505756 0.15002497]]", "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": 50000, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "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:": "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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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}