code: def GetLikeChangeFromPruningNgram(self, hist, word):
      counts_for_hist = self.counts[len(hist)][hist]
      counts_for_backoff_hist = self.counts[len(hist) - 1][hist[1:]]
      assert (
          word != self.backoff_symbol
          and word in counts_for_hist.word_to_count
      )
      count = counts_for_hist.word_to_count[word]
      discount = counts_for_hist.word_to_count[self.backoff_symbol]
      backoff_total = counts_for_backoff_hist.total_count
      # backoff_count is a pseudo-count: it's like the count of 'word' in the
      # backoff history-state, but adding something to account for further
      # levels of backoff.
      try:
          backoff_count = self.GetProb(hist[1:], word) * backoff_total
      except Exception:
          print(
              "problem getting backoff count: hist = {0}, word = {1}".format(
                  hist, word
              ),
              file=sys.stderr,
          )
          sys.exit(1)
  
      return self.PruningLogprobChange(
          float(count),
          float(discount),
          backoff_count,
          float(backoff_total),
      )
  
imports: import argparse
  import math
  import sys
  from collections import defaultdict
label_desc: Use image node_id 15 for calling the NgramCounts obj's underlying member method code with example usage: obj.GetLikeChangeFromPruningNgram(hist, word) and returns: self