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@@ -19,6 +19,8 @@
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title: Multi GPU training
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- local: peft_training
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title: Training with PEFT (e.g., LoRA)
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- local: rename_map
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title: Using Rename Map and Empty Cameras
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title: "Tutorials"
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- sections:
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- local: lerobot-dataset-v3
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@@ -110,7 +110,7 @@ LeRobot supports this with **empty cameras**: the config declares extra “slots
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</p>
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- In the policy config (e.g. [xvla-base config.json](https://huggingface.co/lerobot/xvla-base/blob/main/config.json)), `empty_cameras` is the number of these extra slots (default `0`).
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- For each slot, the config adds an observation key of the form:
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- For each slot, the config adds an observation key of the form:
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`observation.images.empty_camera_0`, `observation.images.empty_camera_1`, …
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Example: XVLA-base has three visual inputs and `empty_cameras=0`. Your dataset has only two images. Set **`empty_cameras=1`**. Then:
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@@ -135,11 +135,11 @@ If you see a feature mismatch error (“Missing features” / “Extra features
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## Quick reference
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| Goal | What to do |
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|------|------------|
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| Dataset keys ≠ policy keys (training) | `--rename_map='{"dataset_key": "policy_key", ...}'` |
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| Env keys ≠ policy keys (eval) | `--rename_map='{"env_key": "policy_key", ...}'` |
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| Fewer cameras than policy expects | Set `empty_cameras` in the policy config (e.g. `1` when you have 2 real cameras and the policy expects 3). |
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| Avoid passing a rename map | Edit the policy’s `config.json` so its observation keys match your dataset or env. |
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| Goal | What to do |
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| ------------------------------------- | ---------------------------------------------------------------------------------------------------------- |
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| Dataset keys ≠ policy keys (training) | `--rename_map='{"dataset_key": "policy_key", ...}'` |
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| Env keys ≠ policy keys (eval) | `--rename_map='{"env_key": "policy_key", ...}'` |
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| Fewer cameras than policy expects | Set `empty_cameras` in the policy config (e.g. `1` when you have 2 real cameras and the policy expects 3). |
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| Avoid passing a rename map | Edit the policy’s `config.json` so its observation keys match your dataset or env. |
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The rename map keeps your pipeline flexible: one policy, many data sources, no code changes—just a small dictionary on the command line or in your config.
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