tf-keras-skeleton.py 文件源码

def get_updates(self, params, constraints, loss):
        grads = self.get_gradients(loss, params)
        shapes = [K.int_shape(p) for p in params]
        accumulators = [K.zeros(shape) for shape in shapes]
        delta_accumulators = [K.zeros(shape) for shape in shapes]
        self.weights = accumulators + delta_accumulators
        self.updates = []

        lr = self.lr
        if self.initial_decay > 0:
          lr *= (1. / (1. + self.decay * self.iterations))
          self.updates.append(K.update_add(self.iterations, 1))

        for p, g, a, d_a in zip(params, grads, accumulators, delta_accumulators):
          # update accumulator
          new_a = self.rho * a + (1. - self.rho) * K.square(g)
          self.updates.append(K.update(a, new_a))

          # use the new accumulator and the *old* delta_accumulator
          update = g * K.sqrt(d_a + self.epsilon) / K.sqrt(new_a + self.epsilon)

          new_p = p - lr * update
          # apply constraints
          if p in constraints:
            c = constraints[p]
            new_p = c(new_p)
          self.updates.append(K.update(p, new_p))

          # update delta_accumulator
          new_d_a = self.rho * d_a + (1 - self.rho) * K.square(update)
          self.updates.append(K.update(d_a, new_d_a))
        return self.updates