def get_label_names():
    """Returns labels as a list of strings with indices matching training data.

    Reference:

    - [Reuters Dataset](https://martin-thoma.com/nlp-reuters/)
    """
    return (
        "cocoa",
        "grain",
        "veg-oil",
        "earn",
        "acq",
        "wheat",
        "copper",
        "housing",
        "money-supply",
        "coffee",
        "sugar",
        "trade",
        "reserves",
        "ship",
        "cotton",
        "carcass",
        "crude",
        "nat-gas",
        "cpi",
        "money-fx",
        "interest",
        "gnp",
        "meal-feed",
        "alum",
        "oilseed",
        "gold",
        "tin",
        "strategic-metal",
        "livestock",
        "retail",
        "ipi",
        "iron-steel",
        "rubber",
        "heat",
        "jobs",
        "lei",
        "bop",
        "zinc",
        "orange",
        "pet-chem",
        "dlr",
        "gas",
        "silver",
        "wpi",
        "hog",
        "lead",
    )
Returns labels as a list of strings with indices matching training data.

    Reference:

    - [Reuters Dataset](https://martin-thoma.com/nlp-reuters/)
    
keras/src/datasets/reuters.py