How to use the anndata.utils function in anndata

cache_compression=_empty,
):
    """
    Read mex from output from Cell Ranger v3 or later versions
    """
    path = Path(path)
    adata = read(
        path / 'matrix.mtx.gz',
        cache=cache,
        cache_compression=cache_compression
    ).T  # transpose the data
    genes = pd.read_csv(path / 'features.tsv.gz', header=None, sep='\t')
    if var_names == 'gene_symbols':
        var_names = genes[1]
        if make_unique:
            var_names = anndata.utils.make_index_unique(pd.Index(var_names))
        adata.var_names = var_names
        adata.var['gene_ids'] = genes[0].values
    elif var_names == 'gene_ids':
        adata.var_names = genes[0]
        adata.var['gene_symbols'] = genes[1].values
    else:
        raise ValueError("`var_names` needs to be 'gene_symbols' or 'gene_ids'")
    adata.var['feature_types'] = genes[2].values
    adata.obs_names = pd.read_csv(path / 'barcodes.tsv.gz', header=None)[0]
    return adata

cache_compression=_empty,
):
    """
    Read mex from output from Cell Ranger v2 or earlier versions
    """
    path = Path(path)
    adata = read(
        path / 'matrix.mtx',
        cache=cache,
        cache_compression=cache_compression,
    ).T  # transpose the data
    genes = pd.read_csv(path / 'genes.tsv', header=None, sep='\t')
    if var_names == 'gene_symbols':
        var_names = genes[1]
        if make_unique:
            var_names = anndata.utils.make_index_unique(pd.Index(var_names))
        adata.var_names = var_names
        adata.var['gene_ids'] = genes[0].values
    elif var_names == 'gene_ids':
        adata.var_names = genes[0]
        adata.var['gene_symbols'] = genes[1].values
    else:
        raise ValueError("`var_names` needs to be 'gene_symbols' or 'gene_ids'")
    adata.obs_names = pd.read_csv(path / 'barcodes.tsv', header=None)[0]
    return adata