Fix datasets missing versions (#318)
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## Using / Updating `CODEBASE_VERSION` (for maintainers)
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Since our dataset pushed to the hub are decoupled with the evolution of this repo, we ensure compatibility of
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the datasets with our code, we use a `CODEBASE_VERSION` (defined in
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lerobot/common/datasets/lerobot_dataset.py) variable.
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For instance, [`lerobot/pusht`](https://huggingface.co/datasets/lerobot/pusht) has many versions to maintain backward compatibility between LeRobot codebase versions:
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- [v1.0](https://huggingface.co/datasets/lerobot/pusht/tree/v1.0)
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- [v1.1](https://huggingface.co/datasets/lerobot/pusht/tree/v1.1)
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- [v1.2](https://huggingface.co/datasets/lerobot/pusht/tree/v1.2)
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- [v1.3](https://huggingface.co/datasets/lerobot/pusht/tree/v1.3)
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- [v1.4](https://huggingface.co/datasets/lerobot/pusht/tree/v1.4)
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- [v1.5](https://huggingface.co/datasets/lerobot/pusht/tree/v1.5) <-- last version
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- [main](https://huggingface.co/datasets/lerobot/pusht/tree/main) <-- points to the last version
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Starting with v1.6, every dataset pushed to the hub or saved locally also have this version number in their
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`info.json` metadata.
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### Uploading a new dataset
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If you are pushing a new dataset, you don't need to worry about any of the instructions below, nor to be
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compatible with previous codebase versions. The `push_dataset_to_hub.py` script will automatically tag your
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dataset with the current `CODEBASE_VERSION`.
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### Updating an existing dataset
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If you want to update an existing dataset, you need to change the `CODEBASE_VERSION` from `lerobot_dataset.py`
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before running `push_dataset_to_hub.py`. This is especially useful if you introduce a breaking change
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intentionally or not (i.e. something not backward compatible such as modifying the reward functions used,
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deleting some frames at the end of an episode, etc.). That way, people running a previous version of the
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codebase won't be affected by your change and backward compatibility is maintained.
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However, you will need to update the version of ALL the other datasets so that they have the new
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`CODEBASE_VERSION` as a branch in their hugging face dataset repository. Don't worry, there is an easy way
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that doesn't require to run `push_dataset_to_hub.py`. You can just "branch-out" from the `main` branch on HF
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dataset repo by running this script which corresponds to a `git checkout -b` (so no copy or upload needed):
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```python
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from huggingface_hub import HfApi
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from lerobot import available_datasets
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from lerobot.common.datasets.lerobot_dataset import CODEBASE_VERSION
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api = HfApi()
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for repo_id in available_datasets:
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dataset_info = api.list_repo_refs(repo_id, repo_type="dataset")
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branches = [b.name for b in dataset_info.branches]
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if CODEBASE_VERSION in branches:
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# First check if the newer version already exists.
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print(f"Found existing branch for {repo_id}. Please contact a member of the core LeRobot team.")
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print("Exiting early")
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break
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else:
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# Now create a branch named after the new version by branching out from "main"
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# which is expected to be the preceding version
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api.create_branch(repo_id, repo_type="dataset", branch=CODEBASE_VERSION, revision="main")
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print(f"{repo_id} successfully updated")
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```
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