a2c-PandaReachDense-v2 / config.json
ReadyP1's picture
Initial commit
8886af2
{"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 0x7fc339e091b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fc339e01f40>"}, "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": 1684557884774759546, "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": "[[ 0.44535992 -0.01908942 0.5724 ]\n [ 0.44535992 -0.01908942 0.5724 ]\n [ 0.44535992 -0.01908942 0.5724 ]\n [ 0.44535992 -0.01908942 0.5724 ]]", "desired_goal": "[[ 1.4983776 -1.4056573 0.2725874 ]\n [-0.49900824 -1.282023 -0.35461825]\n [-0.83208877 -0.5670779 -1.3557414 ]\n [-1.3211708 0.39918938 -1.1031525 ]]", "observation": "[[ 0.44535992 -0.01908942 0.5724 0.00834651 -0.00187304 -0.0027924 ]\n [ 0.44535992 -0.01908942 0.5724 0.00834651 -0.00187304 -0.0027924 ]\n [ 0.44535992 -0.01908942 0.5724 0.00834651 -0.00187304 -0.0027924 ]\n [ 0.44535992 -0.01908942 0.5724 0.00834651 -0.00187304 -0.0027924 ]]"}, "_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////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAOZH5vaQqGb7maeE9LnKbvea5/b2O/8g8CesbvWk4p7kAGmE+OPz+vc6Uxr3goY0+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": "[[-0.12185902 -0.14957672 0.11006527]\n [-0.07590137 -0.12388973 0.02453592]\n [-0.03806594 -0.00031895 0.21982574]\n [-0.12450451 -0.09696351 0.27662563]]", "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-5.15.107+-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"}}