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README.md
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Contents of datasets.
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'param': All the parameters in the policy network as a flattened vector.
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'traj': prior trajectories in first 60 steps, as 's_0, a_0, a_1, a_2, s_3, a_3, a_4, a_5'.
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If you want to train with your dataset or task, you can privately design the trajectory dimensions and encode them to the same dimension (for example we used 128).
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You can use our pretrained model with the same behavior dimensions to finetune on your dataset.
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Contents of datasets.
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2 |
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3 |
'param': All the parameters in the policy network as a flattened vector.
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4 |
+
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5 |
'traj': prior trajectories in first 60 steps, as 's_0, a_0, a_1, a_2, s_3, a_3, a_4, a_5'.
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'task': the success three states 's_m, s_{m+1}, s_{m+2}'
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If you want to train with your dataset or task, you can privately design the trajectory dimensions and encode them to the same dimension (for example we used 128).
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10 |
You can use our pretrained model with the same behavior dimensions to finetune on your dataset.
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