self, batch, logs=None):
    logs = logs or {}
    self.trn_iterations += 1
    self.clr_iterations += 1

    self.history.setdefault(&#34;lr&#34;, []).append(K.get_value(self.model.optimizer.lr))
    self.history.setdefault(&#34;iterations&#34;, []).append(self.trn_iterations)

    for k, v in logs.items():
        self.history.setdefault(k, []).append(v)

    K.set_value(self.model.optimizer.lr, self.clr())

    # annihilate learning rate
    prev_overhump = self.overhump
    iterations = (self.clr_iterat