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
def get_current_value ( self ) : if self . agent . training : 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
Return current annealing value

        # Returns
            Value to use in annealing