def METHOD_NAME(cls, sample: dict, flatten_arrays=True):
    columns = []
    ndarray_columns = set()
    for name, value in sample.items():
        if isinstance(value, np.ndarray):
            if value.ndim > 1:
                ndarray_columns.add(name)
        columns.append(name)
    return cls(
        columns=columns,
        ndarray_columns=ndarray_columns,
        flatten_arrays=flatten_arrays,
    )