class_docstr: Represents a count of occurrences of events or objects.
  
  `Counter` can help debug Pipeline computations. For example, by counting
  objects (consumed, produced, etc...) by the Pipeline, or occurrences of
  certain cases in the Pipeline.
docstr: Constructs a Counter.
  
  Args:
    name: String name of this counter.
    start_value: What value to start the count at.
docstr_tok: ["Constructs","a","Counter",".","Args",":","name",":","String","name","of","this","counter",".","start_value",":","What","value","to","start","the","count","at","."]
code: def __init__(self, name, start_value=0):
      """Constructs a Counter.
  
      Args:
        name: String name of this counter.
        start_value: What value to start the count at.
      """
      super(Counter, self).__init__(name)
      self.count = start_value
  
imports: import abc
  import bisect
  import copy
  import tensorflow.compat.v1
label_desc: Use image node_id 1 to create a new Counter object from inherited base classes: Statistic with example: obj = Counter(name, start_value)