File size: 15,669 Bytes
8edd1b4 |
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 0x7f7b07716290>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f7b07719a80>"}, "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": 1200000, "_total_timesteps": 1200000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685078109299661776, "learning_rate": 0.0007, "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": "[[ 0.3859569 -0.01140691 0.57812005]\n [ 0.3859569 -0.01140691 0.57812005]\n [ 0.3859569 -0.01140691 0.57812005]\n [ 0.3859569 -0.01140691 0.57812005]]", "desired_goal": "[[-1.4123622 0.7941294 0.26024103]\n [-0.9574925 0.7990496 -0.256834 ]\n [ 0.10849657 -1.7130446 1.364424 ]\n [ 0.3201655 -1.0415977 -1.5065879 ]]", "observation": "[[ 3.8595691e-01 -1.1406910e-02 5.7812005e-01 1.0279942e-02\n -5.3042633e-04 1.7889547e-03]\n [ 3.8595691e-01 -1.1406910e-02 5.7812005e-01 1.0279942e-02\n -5.3042633e-04 1.7889547e-03]\n [ 3.8595691e-01 -1.1406910e-02 5.7812005e-01 1.0279942e-02\n -5.3042633e-04 1.7889547e-03]\n [ 3.8595691e-01 -1.1406910e-02 5.7812005e-01 1.0279942e-02\n -5.3042633e-04 1.7889547e-03]]"}, "_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////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAh0a0vEDqD76kdes9UJ/cvX4s870ANEw+hf/fvNwmlL247IY+WDOgvdGwCr72LFs+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==", "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": "[[-0.02200629 -0.14054203 0.11497048]\n [-0.10772574 -0.11873721 0.19941711]\n [-0.02734352 -0.07233974 0.26352477]\n [-0.07822293 -0.13544013 0.2140387 ]]", "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": 60000, "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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}} |