| {"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 0x7f1ef682d3a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f1ef682bd40>"}, "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": 1681416945721107148, "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": "[[ 0.40694824 -0.02106396 0.5558769 ]\n [ 0.40694824 -0.02106396 0.5558769 ]\n [ 0.40694824 -0.02106396 0.5558769 ]\n [ 0.40694824 -0.02106396 0.5558769 ]]", "desired_goal": "[[ 1.1512549 1.131528 -0.89865154]\n [ 0.94948786 1.2772167 -0.99465626]\n [ 1.5370598 0.9742752 1.4800866 ]\n [ 0.9362186 -0.48348987 1.4734225 ]]", "observation": "[[ 0.40694824 -0.02106396 0.5558769 0.00497153 -0.00246939 0.0043431 ]\n [ 0.40694824 -0.02106396 0.5558769 0.00497153 -0.00246939 0.0043431 ]\n [ 0.40694824 -0.02106396 0.5558769 0.00497153 -0.00246939 0.0043431 ]\n [ 0.40694824 -0.02106396 0.5558769 0.00497153 -0.00246939 0.0043431 ]]"}, "_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": "[[ 0.05204189 0.09456232 0.01453768]\n [-0.14605519 -0.04778624 0.04605196]\n [ 0.0823647 0.10122812 0.11957801]\n [-0.00964177 -0.030865 0.17487894]]", "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-5.19.0-38-generic-x86_64-with-glibc2.35 # 39~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Mar 17 21:16:15 UTC 2", "Python": "3.9.16", "Stable-Baselines3": "1.8.0", "PyTorch": "1.11.0+cu102", "GPU Enabled": "True", "Numpy": "1.21.2", "Gym": "0.21.0"}} |