Rename Aloha2 to Aloha
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@ -4,7 +4,7 @@ fps: 30
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env:
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name: dora
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task: DoraAloha2-v0
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task: DoraAloha-v0
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state_dim: 14
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action_dim: 14
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fps: ${fps}
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@ -1,7 +1,21 @@
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# @package _global_
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# Use `act_real.yaml` to train on real-world Aloha/Aloha2 datasets.
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# Compared to `act.yaml`, it contains 4 cameras (i.e. cam_right_wrist, cam_left_wrist, images,
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# cam_low) instead of 1 camera (i.e. top). Also, `training.eval_freq` is set to -1. This config is used
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# to evaluate checkpoints at a certain frequency of training steps. When it is set to -1, it deactivates evaluation.
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# This is because real-world evaluation is done through [dora-lerobot](https://github.com/dora-rs/dora-lerobot).
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# Look at its README for more information on how to evaluate a checkpoint in the real-world.
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#
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# Example of usage for training:
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# ```bash
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# python lerobot/scripts/train.py \
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# policy=act_real \
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# env=aloha_real
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# ```
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seed: 1000
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dataset_repo_id: cadene/wrist_gripper
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dataset_repo_id: lerobot/aloha_static_vinh_cup
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override_dataset_stats:
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observation.images.cam_right_wrist:
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@ -9,7 +9,7 @@
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# ```bash
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# python lerobot/scripts/train.py \
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# policy=act_real_no_state \
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# env=dora_aloha_real
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# env=aloha2_real
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# ```
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seed: 1000
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