class_docstr: Represents a histogram of real-valued events.
  
  A histogram is a list of counts, each over a range of values.
  For example, given this list of values [0.5, 0.0, 1.0, 0.6, 1.5, 2.4, 0.1],
  a histogram over 3 ranges [0, 1), [1, 2), [2, 3) would be:
    [0, 1): 4
    [1, 2): 2
    [2, 3): 1
  Each range is inclusive in the lower bound and exclusive in the upper bound
  (hence the square open bracket but curved close bracket).
  
  Usage examples:
      A distribution over input/output lengths.
      A distribution over compute times.
docstr: Increment the bucket containing the given value.
  
  The bucket count for which ever range `value` falls in will be incremented.
  
  Args:
    value: Any number.
    inc: An integer. How much to increment the bucket count by.
docstr_tok: ["Increment","the","bucket","containing","the","given","value",".","The","bucket","count","for","which","ever","range","`","value","`","falls","in","will","be","incremented",".","Args",":","value",":","Any","number",".","inc",":","An","integer",".","How","much","to","increment","the","bucket","count","by","."]
code: def increment(self, value, inc=1):
      """Increment the bucket containing the given value.
  
      The bucket count for which ever range `value` falls in will be incremented.
  
      Args:
        value: Any number.
        inc: An integer. How much to increment the bucket count by.
      """
      bucket_lower = self._find_le(value)
      self.counters[bucket_lower] += inc
  
imports: import abc
  import bisect
  import copy
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the Histogram obj's underlying member method code with example usage: obj.increment(value, inc) without return types