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.gitattributes +1 -0
README.md +1 -1
a2c-PandaPickAndPlace-v3.zip +2 -2
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a2c-PandaPickAndPlace-v3/policy.pth +1 -1
a2c-PandaPickAndPlace-v3/pytorch_variables.pth +1 -1
config.json +1 -1
replay.mp4 +0 -0
results.json +1 -1
vec_normalize.pkl +2 -2

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@@ -16,7 +16,7 @@ model-index:
       type: PandaPickAndPlace-v3
     metrics:
     - type: mean_reward
-      value: -8.20 +/- 1.78
       name: mean_reward
       verified: false
 ---

       type: PandaPickAndPlace-v3
     metrics:
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       name: mean_reward
       verified: false
 ---

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         "bounded_below": "[ True  True  True  True]",
         "bounded_above": "[ True  True  True  True]",
@@ -84,7 +78,7 @@
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         "_np_random": "Generator(PCG64)"
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     "batch_size": 2048,
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         "activation_fn": "<class 'torch.nn.modules.activation.GELU'>",
         "use_sde": false
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     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
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     "learning_rate": 0.0005,
     "tensorboard_log": null,
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space\n :param action_space: Action space\n :param env: The training environment\n :param device: PyTorch device\n :param n_envs: Number of parallel environments\n :param optimize_memory_usage: Enable a memory efficient variant\n Disabled for now (see https://github.com/DLR-RM/stable-baselines3/pull/243#discussion_r531535702)\n :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n separately and treat the task as infinite horizon task.\n https://github.com/DLR-RM/stable-baselines3/issues/284\n :param n_sampled_goal: Number of virtual transitions to create per real transition,\n by sampling new goals.\n :param goal_selection_strategy: Strategy for sampling goals for replay.\n One of ['episode', 'final', 'future']\n :param copy_info_dict: Whether to copy the info dictionary and pass it to\n ``compute_reward()`` method.\n Please note that the copy may cause a slowdown.\n False by default.\n ", "__init__": "<function HerReplayBuffer.__init__ at 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