class_docstr: Tracks the progress of training and checks if training should stop.
class_docstr_tok: ["Tracks","the","progress","of","training","and","checks","if","training","should","stop","."]
code: def __init__(
      self, label, save_path, sign=-1, patience=5, decay_op=None
  ):
      self.label = label
      self.sign = sign
      self.best = np.inf
      self.saver = tf.train.Saver()
      self.save_path = save_path
      self.patience = patience
      # NOTE: age is reset with decay, but true_age is not
      self.age = 0
      self.true_age = 0
      self.decay_op = decay_op
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import time
  from magenta.models.coconet import lib_data
  from magenta.models.coconet import lib_graph
  from magenta.models.coconet import lib_hparams
  from magenta.models.coconet import lib_util
  import numpy
  import six
  from six.moves import range
  from six.moves import zip
  import tensorflow.compat.v1
label_desc: Use image node_id 1 to create a new Tracker object from inherited base classes: object with example: obj = Tracker(label, save_path, sign, patience, decay_op)