{"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 0x7f308fad9630>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f308fad6f80>"}, "verbose": 2, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVlAAAAAAAAAB9lCiMCG5ldF9hcmNolF2UKEtAS0BljA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "net_arch": [64, 64], "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 1040000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688847109613312815, "learning_rate": 0.001, "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": "[[0.7168043  0.01338592 1.2227521 ]\n [0.7168043  0.01338592 1.2227521 ]\n [0.7168043  0.01338592 1.2227521 ]\n [0.7168043  0.01338592 1.2227521 ]]", "desired_goal": "[[ 0.0376953   0.6216533   1.2449838 ]\n [-1.4025266   0.61889446  1.1548936 ]\n [-1.3054752  -0.82119256  1.0256162 ]\n [ 0.45761174 -1.4360691  -0.8153772 ]]", "observation": "[[ 7.1680433e-01  1.3385922e-02  1.2227521e+00  7.8009680e-02\n  -8.5839606e-04  8.7119780e-02]\n [ 7.1680433e-01  1.3385922e-02  1.2227521e+00  7.8009680e-02\n  -8.5839606e-04  8.7119780e-02]\n [ 7.1680433e-01  1.3385922e-02  1.2227521e+00  7.8009680e-02\n  -8.5839606e-04  8.7119780e-02]\n [ 7.1680433e-01  1.3385922e-02  1.2227521e+00  7.8009680e-02\n  -8.5839606e-04  8.7119780e-02]]"}, "_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": "[[-0.14064297  0.03924853  0.29915485]\n [-0.03702001 -0.13993889  0.27145293]\n [-0.09115793 -0.07134382  0.01522954]\n [ 0.05035605  0.08289871  0.05868492]]", "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": -0.040000000000000036, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIb/JbdLL0HMCUhpRSlIwBbJRLMowBdJRHQKXWxGViWmh1fZQoaAZoCWgPQwgexqS/l/IQwJSGlFKUaBVLMmgWR0Cl1mC8e0XxdX2UKGgGaAloD0MIDkxuFFnrFMCUhpRSlGgVSzJoFkdApdYNfu1F6XV9lChoBmgJaA9DCFr1udqKzRLAlIaUUpRoFUsyaBZHQKXVtLHuJDV1fZQoaAZoCWgPQwjTad0GtX8awJSGlFKUaBVLMmgWR0Cl15wxnFo+dX2UKGgGaAloD0MI1PIDV3lSF8CUhpRSlGgVSzJoFkdApdc4PNFBp3V9lChoBmgJaA9DCKBTkJ+N3A/AlIaUUpRoFUsyaBZHQKXW5PpIMBp1fZQoaAZoCWgPQwjw+WGE8AgVwJSGlFKUaBVLMmgWR0Cl1owL3K0VdX2UKGgGaAloD0MIATJ07KCiG8CUhpRSlGgVSzJoFkdApdiD7oB7u3V9lChoBmgJaA9DCNEi2/l+ChnAlIaUUpRoFUsyaBZHQKXYICvovBd1fZQoaAZoCWgPQwiM9nghHb4bwJSGlFKUaBVLMmgWR0Cl18zXarWAdX2UKGgGaAloD0MI3T8WokOQEsCUhpRSlGgVSzJoFkdApdd0Vk+X7nV9lChoBmgJaA9DCGVVhJuMihrAlIaUUpRoFUsyaBZHQKXZVWOp84R1fZQoaAZoCWgPQwhLsaNxqD8XwJSGlFKUaBVLMmgWR0Cl2PGOEM9bdX2UKGgGaAloD0MIpKgz95CQGsCUhpRSlGgVSzJoFkdApdieRRuTA3V9lChoBmgJaA9DCP+ye/KwQBTAlIaUUpRoFUsyaBZHQKXYRZUT+Nt1fZQoaAZoCWgPQwhhbYyd8EIWwJSGlFKUaBVLMmgWR0Cl2pQGfPHDdX2UKGgGaAloD0MIOkAwR48/FcCUhpRSlGgVSzJoFkdApdoxBsyi23V9lChoBmgJaA9DCIhITbuYVhzAlIaUUpRoFUsyaBZHQKXZ3k6tDD11fZQoaAZoCWgPQwhXYMjqVv8QwJSGlFKUaBVLMmgWR0Cl2YXjuKGddX2UKGgGaAloD0MIgQpHkEoxGMCUhpRSlGgVSzJoFkdApdwQkJKJ23V9lChoBmgJaA9DCA4sR8hADhTAlIaUUpRoFUsyaBZHQKXbrcCYCyR1fZQoaAZoCWgPQwhlOJ7PgFoLwJSGlFKUaBVLMmgWR0Cl21x8c+7ldX2UKGgGaAloD0MIXJNuS+SKIMCUhpRSlGgVSzJoFkdApdsEZFXq7nV9lChoBmgJaA9DCOUn1T4drxTAlIaUUpRoFUsyaBZHQKXdp9XLeRB1fZQoaAZoCWgPQwjIsmDij2IMwJSGlFKUaBVLMmgWR0Cl3UUpmVZ+dX2UKGgGaAloD0MIXvHUIw2+EMCUhpRSlGgVSzJoFkdApdz0m6XjVHV9lChoBmgJaA9DCEKvP4nPbRLAlIaUUpRoFUsyaBZHQKXcnHbRF7V1fZQoaAZoCWgPQwioHJPF/ScfwJSGlFKUaBVLMmgWR0Cl305yuIRAdX2UKGgGaAloD0MI+x9grdpFEsCUhpRSlGgVSzJoFkdApd7rn5i3HHV9lChoBmgJaA9DCO4JEtvdIxfAlIaUUpRoFUsyaBZHQKXemPQOWjZ1fZQoaAZoCWgPQwj9FTJXBnURwJSGlFKUaBVLMmgWR0Cl3kE0iyIIdX2UKGgGaAloD0MI71aW6CyTC8CUhpRSlGgVSzJoFkdApeEWwu/UOXV9lChoBmgJaA9DCCSBBps6zwzAlIaUUpRoFUsyaBZHQKXgs6fapP11fZQoaAZoCWgPQwiILqhvmQMTwJSGlFKUaBVLMmgWR0Cl4GFuvUz9dX2UKGgGaAloD0MIcm4T7pU5EMCUhpRSlGgVSzJoFkdApeAJP/JeV3V9lChoBmgJaA9DCII5evzeBhLAlIaUUpRoFUsyaBZHQKXis9HMEA51fZQoaAZoCWgPQwgip6/na8YbwJSGlFKUaBVLMmgWR0Cl4lFAu7HydX2UKGgGaAloD0MIBRVVv9LJGcCUhpRSlGgVSzJoFkdApeH/PLPldXV9lChoBmgJaA9DCGFVvfxOoxzAlIaUUpRoFUsyaBZHQKXhp+fAbhp1fZQoaAZoCWgPQwh2pWWk3vMIwJSGlFKUaBVLMmgWR0Cl5F9fkWAPdX2UKGgGaAloD0MIVB9I3jn0CsCUhpRSlGgVSzJoFkdApeP8hkiD/XV9lChoBmgJaA9DCAa9N4YAcBDAlIaUUpRoFUsyaBZHQKXjqdU83dd1fZQoaAZoCWgPQwgvpS4Zx+gWwJSGlFKUaBVLMmgWR0Cl41GN70FsdX2UKGgGaAloD0MIZFkw8UcBFMCUhpRSlGgVSzJoFkdApeXn/aQFLXV9lChoBmgJaA9DCKCobFhTiRbAlIaUUpRoFUsyaBZHQKXlhAiV0Ld1fZQoaAZoCWgPQwgQ6bevA7cVwJSGlFKUaBVLMmgWR0Cl5TCx3V0+dX2UKGgGaAloD0MIYVJ8fEJWCsCUhpRSlGgVSzJoFkdApeTXsTnJT3V9lChoBmgJaA9DCGkewCK/XhTAlIaUUpRoFUsyaBZHQKXmzcKw6hh1fZQoaAZoCWgPQwhsCI7LuJkUwJSGlFKUaBVLMmgWR0Cl5mm65Gz9dX2UKGgGaAloD0MI2A3bFmUGFMCUhpRSlGgVSzJoFkdApeYWaKDTSnV9lChoBmgJaA9DCJj3ONOEXRfAlIaUUpRoFUsyaBZHQKXlvWjoIOZ1fZQoaAZoCWgPQwjeOv922d8VwJSGlFKUaBVLMmgWR0Cl56XAuZkTdX2UKGgGaAloD0MIZp/HKM8MFMCUhpRSlGgVSzJoFkdApedB6+nIhnV9lChoBmgJaA9DCI/9LJYiWRPAlIaUUpRoFUsyaBZHQKXm7pBX0Xh1fZQoaAZoCWgPQwj61LFK6RkRwJSGlFKUaBVLMmgWR0Cl5pWSMcZMdX2UKGgGaAloD0MINBKhEWyMEsCUhpRSlGgVSzJoFkdApeiSHmA9V3V9lChoBmgJaA9DCD9z1qccIxDAlIaUUpRoFUsyaBZHQKXoLiIcinp1fZQoaAZoCWgPQwj7JHfYRKYewJSGlFKUaBVLMmgWR0Cl59sC1Z1WdX2UKGgGaAloD0MIQwQcQpV6C8CUhpRSlGgVSzJoFkdApeeCAJ9iMHV9lChoBmgJaA9DCOik942vXRPAlIaUUpRoFUsyaBZHQKXpeYb83uN1fZQoaAZoCWgPQwh/oNy274EZwJSGlFKUaBVLMmgWR0Cl6RWUB4lhdX2UKGgGaAloD0MIjZqvko89D8CUhpRSlGgVSzJoFkdApejC3iJfpnV9lChoBmgJaA9DCBgjEoWWZRTAlIaUUpRoFUsyaBZHQKXoardWQwN1fZQoaAZoCWgPQwjXL9gN2zYawJSGlFKUaBVLMmgWR0Cl6lDaXa8IdX2UKGgGaAloD0MIvvkNEw3CF8CUhpRSlGgVSzJoFkdApentFlTWG3V9lChoBmgJaA9DCNP3GoLjsh3AlIaUUpRoFUsyaBZHQKXpmh3aBZp1fZQoaAZoCWgPQwivJeSDnk0MwJSGlFKUaBVLMmgWR0Cl6UEy1uzhdX2UKGgGaAloD0MI0uC2tvD8HcCUhpRSlGgVSzJoFkdApes8ophF3XV9lChoBmgJaA9DCKIMVTGVLh3AlIaUUpRoFUsyaBZHQKXq2LAHmih1fZQoaAZoCWgPQwjjF15J8swVwJSGlFKUaBVLMmgWR0Cl6oXNC7btdX2UKGgGaAloD0MIhdBBl3CIFcCUhpRSlGgVSzJoFkdApeotUuL743V9lChoBmgJaA9DCLNeDOVEGw3AlIaUUpRoFUsyaBZHQKXsN5ooNNJ1fZQoaAZoCWgPQwjUYYVbPmIVwJSGlFKUaBVLMmgWR0Cl69OzposadX2UKGgGaAloD0MIjLysiQU+DcCUhpRSlGgVSzJoFkdApeuAnlXA/XV9lChoBmgJaA9DCKpla32RACDAlIaUUpRoFUsyaBZHQKXrJ+vQnhN1fZQoaAZoCWgPQwhFnE6y1cUGwJSGlFKUaBVLMmgWR0Cl7TmNBF/hdX2UKGgGaAloD0MItwiM9Q1cFMCUhpRSlGgVSzJoFkdApezVijL0SXV9lChoBmgJaA9DCLt9VpkpzRDAlIaUUpRoFUsyaBZHQKXsgi+tbLV1fZQoaAZoCWgPQwiM22gAb2EbwJSGlFKUaBVLMmgWR0Cl7CmrCFbndX2UKGgGaAloD0MIZcIv9fPGGsCUhpRSlGgVSzJoFkdApe5+exwAEXV9lChoBmgJaA9DCMyyJ4HNWQjAlIaUUpRoFUsyaBZHQKXuHAqNIbx1fZQoaAZoCWgPQwgdc56xL/kSwJSGlFKUaBVLMmgWR0Cl7ck6tDD1dX2UKGgGaAloD0MIZAeVuI5xHsCUhpRSlGgVSzJoFkdApe1xHG0eEXV9lChoBmgJaA9DCKiQK/Us6BPAlIaUUpRoFUsyaBZHQKXwBpUPxx11fZQoaAZoCWgPQwgVAOMZNAQTwJSGlFKUaBVLMmgWR0Cl76NbcGkfdX2UKGgGaAloD0MIBYpYxLBzFcCUhpRSlGgVSzJoFkdApe9SDujRD3V9lChoBmgJaA9DCJUtknajPxHAlIaUUpRoFUsyaBZHQKXu+gwoLG91fZQoaAZoCWgPQwgo8E4+PTYQwJSGlFKUaBVLMmgWR0Cl8Z1zZHurdX2UKGgGaAloD0MIGa4OgLhrEMCUhpRSlGgVSzJoFkdApfE74i5d4XV9lChoBmgJaA9DCPhRDfs9kRbAlIaUUpRoFUsyaBZHQKXw6qEOAiF1fZQoaAZoCWgPQwgqO/2gLqIYwJSGlFKUaBVLMmgWR0Cl8JKk/KQrdX2UKGgGaAloD0MIVRaFXRQNE8CUhpRSlGgVSzJoFkdApfNBftx+8XV9lChoBmgJaA9DCBlYx/FDXSDAlIaUUpRoFUsyaBZHQKXy3l7MPjJ1fZQoaAZoCWgPQwh87gT7r0MWwJSGlFKUaBVLMmgWR0Cl8ovluFYddX2UKGgGaAloD0MIV3bB4Jp7D8CUhpRSlGgVSzJoFkdApfI0Dlo11nV9lChoBmgJaA9DCEZEMXkD3BPAlIaUUpRoFUsyaBZHQKX0swV0tAd1fZQoaAZoCWgPQwhL5ljeVX8ZwJSGlFKUaBVLMmgWR0Cl9E/OlfqpdX2UKGgGaAloD0MIBU62gTvAFMCUhpRSlGgVSzJoFkdApfP9qesgdXV9lChoBmgJaA9DCCEBo8ubww3AlIaUUpRoFUsyaBZHQKXzpcynDSB1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 13, "n_steps": 20000, "gamma": 0.95, "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": "3.10.12", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}