class_docstr: This class is used for updating the value of β during the annealing process.
  When β reaches the value of anneal_cap, it stops increasing.
docstr: At the end of each epoch save the value of beta in _beta list.
code: def on_epoch_end(self, epoch, logs={}):
      """At the end of each epoch save the value of beta in _beta list."""
      tmp = K.eval(self.beta)
      self._beta.append(tmp)
  
imports: import numpy
  import matplotlib.pyplot
  import seaborn
  import tensorflow
  from tensorflow.keras.layers import *
  from tensorflow.keras.models import Model
  from tensorflow.keras.losses import binary_crossentropy
  from tensorflow.keras import backend
  from tensorflow.keras.callbacks import ReduceLROnPlateau, Callback
  from recommenders.evaluation.python_evaluation import ndcg_at_k
label_desc: Use image node_id 4 for calling the AnnealingCallback obj's underlying member method code with example usage: obj.on_epoch_end(epoch, logs) without return types