class_docstr: Holds statistics about a Pipeline run.
  
  Pipelines produce statistics on each call to `transform`.
  `Statistic` objects can be merged together to aggregate
  statistics over the course of many calls to `transform`.
  
  A `Statistic` also has a string name which is used during merging. Any two
  `Statistic` instances with the same name may be merged together. The name
  should also be informative about what the `Statistic` is measuring. Names
  do not need to be unique globally (outside of the `Pipeline` objects that
  produce them) because a `Pipeline` that returns statistics will prepend
  its own name, effectively creating a namespace for each `Pipeline`.
docstr: Constructs a `Statistic`.
  
  Subclass constructors are expected to call this constructor.
  
  Args:
    name: The string name for this `Statistic`. Any two `Statistic` objects
        with the same name will be merged together. The name should also
        describe what this Statistic is measuring.
docstr_tok: ["Constructs","a","`","Statistic","`",".","Subclass","constructors","are","expected","to","call","this","constructor",".","Args",":","name",":","The","string","name","for","this","`","Statistic","`",".","Any","two","`","Statistic","`","objects","with","the","same","name","will","be","merged","together",".","The","name","should","also","describe","what","this","Statistic","is","measuring","."]
code: def __init__(self, name):
      """Constructs a `Statistic`.
  
      Subclass constructors are expected to call this constructor.
  
      Args:
        name: The string name for this `Statistic`. Any two `Statistic` objects
            with the same name will be merged together. The name should also
            describe what this Statistic is measuring.
      """
      self.name = name
  
imports: import abc
  import bisect
  import copy
  import tensorflow.compat.v1
label_desc: Use image node_id 1 to create a new Statistic object from inherited base classes: object with example: obj = Statistic(name)