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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_current_value(self):
 """Return current annealing value # Returns Value to use in annealing """

        if self.agent.training:
            # Linear annealed: f(x) = ax + b.
            a = -float(self.value_max - self.value_min) / float(self.nb_steps)
            b = float(self.value_max)
            value = max(self.value_min, a * float(self.agent.step) + b)
        else:
            value = self.value_test
        return value