def get_hf_features_from_features()

in lerobot/common/datasets/utils.py [0:0]

• 24 lines of code
• 10 McCabe index (conditional complexity)

def get_hf_features_from_features(features: dict) -> datasets.Features:
    hf_features = {}
    for key, ft in features.items():
        if ft["dtype"] == "video":
            continue
        elif ft["dtype"] == "image":
            hf_features[key] = datasets.Image()
        elif ft["shape"] == (1,):
            hf_features[key] = datasets.Value(dtype=ft["dtype"])
        elif len(ft["shape"]) == 1:
            hf_features[key] = datasets.Sequence(
                length=ft["shape"][0], feature=datasets.Value(dtype=ft["dtype"])
            )
        elif len(ft["shape"]) == 2:
            hf_features[key] = datasets.Array2D(shape=ft["shape"], dtype=ft["dtype"])
        elif len(ft["shape"]) == 3:
            hf_features[key] = datasets.Array3D(shape=ft["shape"], dtype=ft["dtype"])
        elif len(ft["shape"]) == 4:
            hf_features[key] = datasets.Array4D(shape=ft["shape"], dtype=ft["dtype"])
        elif len(ft["shape"]) == 5:
            hf_features[key] = datasets.Array5D(shape=ft["shape"], dtype=ft["dtype"])
        else:
            raise ValueError(f"Corresponding feature is not valid: {ft}")

    return datasets.Features(hf_features)