def METHOD_NAME(phred_qualities):
    """Converts raw phred quality scores into base-calling error probabilities.
    For each ASCII encoded phred quality score (X), the probability that there
    was an error calling that base is computed by:
    P = 10 ^ (-(X - 33) / 10)
    This is assuming an "ASCII base" of 33.
    The input is a tf.string tensor of ASCII encoded phred qualities,
    one string per DNA sequence, with each character representing the quality
    of a nucelotide.
    For example:
    phred_qualities = [["BB<"], ["BBBB"]]
    Args:
        phred_qualities: A tf.string tensor where each string represents the phred
                        quality of a DNA sequence. Each character in the string
                        is the ASCII representation of the phred quality number.
    Returns:
        tf.RaggedTensor: The quality scores for each base in each sequence provided.
    """
    return tf.ragged.map_flat_values(
        _phred_sequence_to_probability, tf.strings.bytes_split(phred_qualities)
    )