saintzeno's picture
Initial commit!
395e560
{
"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 0x7f8cccb72710>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x7f8cccb78740>"
},
"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": 1688619782333553543,
"learning_rate": 0.0007,
"tensorboard_log": null,
"_last_obs": {
":type:": "<class 'collections.OrderedDict'>",
":serialized:": "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",
"achieved_goal": "[[ 0.23994422 0.00300574 0.4239661 ]\n [-0.99466556 1.4343172 0.7978886 ]\n [ 0.23994422 0.00300574 0.4239661 ]\n [ 0.23994422 0.00300574 0.4239661 ]]",
"desired_goal": "[[-0.5514607 0.75211996 0.42542195]\n [-0.20413288 1.4581455 1.0622305 ]\n [ 0.27912864 -0.15644181 -0.08246591]\n [-0.22648111 -1.4665655 -0.62208474]]",
"observation": "[[ 2.3994422e-01 3.0057372e-03 4.2396611e-01 4.8302075e-01\n 1.2121425e-03 3.8246080e-01]\n [-9.9466556e-01 1.4343172e+00 7.9788858e-01 4.2290118e-01\n 1.0621358e+00 2.0243561e+00]\n [ 2.3994422e-01 3.0057372e-03 4.2396611e-01 4.8302075e-01\n 1.2121425e-03 3.8246080e-01]\n [ 2.3994422e-01 3.0057372e-03 4.2396611e-01 4.8302075e-01\n 1.2121425e-03 3.8246080e-01]]"
},
"_last_episode_starts": {
":type:": "<class 'numpy.ndarray'>",
":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEAAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": "[[-0.06952778 -0.10344996 0.18423223]\n [-0.00217722 -0.01258012 0.01111972]\n [-0.06204122 0.07104181 0.06864521]\n [ 0.09156151 -0.05792348 0.1697909 ]]",
"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 '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": 4,
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuDQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz9G8AaNuLrHhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
}
}