You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I am trying to convert a dataset I collected for finetuning the RT-1-X model. For the transformation step, I am confused by discrepancies between this repository and the RT-1-X training example:
In the specified Target Config in transform.py, 'action' is defined as a tensor of shape (8,), while to my understanding, RT-1 expects 'action' to contain four separate components, namely 'world_vector', 'rotation_delta', 'gripper_closedness_action', and 'terminate_episode'. Further, you specify a separate field for 'language_embedding', while RT-1 expects the field 'natural_language_embedding' within the 'observation' field.
For my project, I changed the transformation so the converted dataset can be used for training in a similar manner as the datasets already used in the training example. However, I am curious what the reason for this discrepancy is.
The text was updated successfully, but these errors were encountered:
jonathansalzer
changed the title
Regarding transform for X Embodiment
Transformation for Open X Embodiment
Jun 21, 2024
Hi, thanks for making this code available!
I am trying to convert a dataset I collected for finetuning the RT-1-X model. For the transformation step, I am confused by discrepancies between this repository and the RT-1-X training example:
In the specified Target Config in
transform.py
, 'action' is defined as a tensor of shape (8,), while to my understanding, RT-1 expects 'action' to contain four separate components, namely 'world_vector', 'rotation_delta', 'gripper_closedness_action', and 'terminate_episode'. Further, you specify a separate field for 'language_embedding', while RT-1 expects the field 'natural_language_embedding' within the 'observation' field.For my project, I changed the transformation so the converted dataset can be used for training in a similar manner as the datasets already used in the training example. However, I am curious what the reason for this discrepancy is.
The text was updated successfully, but these errors were encountered: