File size: 17,529 Bytes
3d2f920
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 0x7d32b127d750>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d32b1278d00>"}, "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": 500000, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711590786873136456, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.26245347  0.00312591  0.40373594]\n [ 0.26245347  0.00312591  0.40373594]\n [-0.4984757   0.41053808  0.31300306]\n [ 0.26245347  0.00312591  0.40373594]\n [ 0.26245347  0.00312591  0.40373594]\n [-0.8094812  -0.8257434  -1.1423858 ]\n [-0.8001809   1.2849263  -1.1706898 ]\n [-0.7981599  -1.2934102  -1.1704981 ]\n [ 0.56277585 -0.38771552  0.6201542 ]\n [-0.07374546 -0.42581198 -0.16793387]]", "desired_goal": "[[ 1.0883684   1.0269275  -1.4481654 ]\n [ 0.81907445 -0.14312682 -0.5148218 ]\n [-1.1616064   0.425331    1.6403923 ]\n [ 1.3845443  -1.4485507   1.2456533 ]\n [-0.18067448  1.0635656   0.4647158 ]\n [-1.3289162  -0.32270473 -1.0622543 ]\n [-0.56251043  1.3876916  -1.4212973 ]\n [-1.2692778  -0.7399478  -0.67749536]\n [ 1.2174852  -0.9500786   1.5361966 ]\n [-1.4525789  -0.48679328 -1.0068806 ]]", "observation": "[[ 2.6245347e-01  3.1259141e-03  4.0373594e-01  4.4339895e-01\n  -1.4949878e-03  3.6877233e-01]\n [ 2.6245347e-01  3.1259141e-03  4.0373594e-01  4.4339895e-01\n  -1.4949878e-03  3.6877233e-01]\n [-4.9847570e-01  4.1053808e-01  3.1300306e-01 -7.6759213e-01\n   1.6338071e+00  8.6505604e-01]\n [ 2.6245347e-01  3.1259141e-03  4.0373594e-01  4.4339895e-01\n  -1.4949878e-03  3.6877233e-01]\n [ 2.6245347e-01  3.1259141e-03  4.0373594e-01  4.4339895e-01\n  -1.4949878e-03  3.6877233e-01]\n [-8.0948120e-01 -8.2574338e-01 -1.1423858e+00 -8.6623007e-01\n   8.0509759e-02 -9.2229015e-01]\n [-8.0018091e-01  1.2849263e+00 -1.1706898e+00 -8.7502545e-01\n   1.0300614e+00 -9.6382797e-01]\n [-7.9815990e-01 -1.2934102e+00 -1.1704981e+00 -7.5687385e-01\n  -9.6620977e-01 -9.6413022e-01]\n [ 5.6277585e-01 -3.8771552e-01  6.2015420e-01  1.6018580e+00\n  -1.5670265e+00  1.1186805e+00]\n [-7.3745459e-02 -4.2581198e-01 -1.6793387e-01 -1.7855872e+00\n  -1.6672264e+00 -1.3942246e+00]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVfQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYKAAAAAAAAAAEBAAEBAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwqFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWV2wIAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolngAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksKSwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcolngAAAAAAAAAjwQFPuBerz0uMXk990r1vYXiHT1o4o89wgOfvV+smD15nu49LZODOzt8Cr74a1w+yzkSvv9Ltz1h/Hw+uEjYPd/pMj06DkE+EYuuvRzSYb1QY4E+9DLMPV/3Br167eU9wYvLveM2kTtrK0o9gt6AOTvHqr0YTIs+lGgOSwpLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiW8AAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LCksGhpRoEnSUUpR1Lg==", "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]\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]\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": "[[ 1.2990020e-01  8.5630178e-02  6.0837917e-02]\n [-1.1977189e-01  3.8546104e-02  7.0256054e-02]\n [-7.7643886e-02  7.4547522e-02  1.1651320e-01]\n [ 4.0153475e-03 -1.3523953e-01  2.1525562e-01]\n [-1.4279859e-01  8.9500420e-02  2.4705650e-01]\n [ 1.0560745e-01  4.3680068e-02  1.8853083e-01]\n [-8.5226186e-02 -5.5132017e-02  2.5271082e-01]\n [ 9.9706560e-02 -3.2950755e-02  1.1226936e-01]\n [-9.9387653e-02  4.4315918e-03  4.9357813e-02]\n [ 2.4579844e-04 -8.3387814e-02  2.7206492e-01]]", "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]\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]\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": 10000, "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 '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, (6,), 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]", "bounded_above": "[ True  True  True]", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 10, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.5.0-26-generic-x86_64-with-glibc2.35 # 26~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Tue Mar 12 10:22:43 UTC 2", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "3.0.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.26.2"}}