def transform_dataset(dataset: Dataset, data_config: _config.DataConfig, *, skip_norm_stats: bool = False) -> Dataset:
    """Transform the dataset by applying the data transforms."""
    norm_stats = {}
    if data_config.repo_id != "fake" and not skip_norm_stats:
        if data_config.norm_stats is None:
            raise ValueError(
                "Normalization stats not found. "
                "Make sure to run `scripts/compute_norm_stats.py --config-name=<your-config>`."
            )
        norm_stats = data_config.norm_stats

    return TransformedDataset(
        dataset,
        [
            *data_config.repack_transforms.inputs,
            *data_config.data_transforms.inputs,
            _transforms.Normalize(norm_stats, use_quantiles=data_config.use_quantile_norm),
            *data_config.model_transforms.inputs,
        ],
    )
Transform the dataset by applying the data transforms.
policy/openpi/src/openpi/training/data_loader.py