code: def fraction_read_support(channels: List[np.ndarray]) -> float:
      """Gets fraction of reads that support the variant.
  
      Args:
          channels: A list of channels of a DeepVariant pileup image. This only uses
            channels[4], the 'read supports variant' channel.
  
      Returns:
          Fraction of reads supporting the alternate allele(s), ranging from [0, 1].
      """
      support_channel = remove_ref_band(channels[4])
      max_row_values = np.amax(support_channel, axis=1)
  
      non_zero_values = max_row_values[max_row_values > 0]
      num_non_zero = non_zero_values.shape[0]
      if num_non_zero == 0:
          return 0.0
      return sum(non_zero_values == 254) * 1.0 / num_non_zero
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import enum
  import math
  from typing import List, NamedTuple, Tuple
  from etils import epath
  from IPython import display
  import numpy
  from PIL import Image
  from PIL import ImageDraw
  from third_party.nucleus.protos import variants_pb2
label_desc: Use image node_id 23 for calling a global function with example usage: fraction_read_support(channels) and returns: unknown, int