tensorflow使用不同的学习率

var_list1 = [variables from first 5 layers]var_list2 = [the rest of variables]train_op1 = GradientDescentOptimizer(0.00001).minimize(loss, var_list=var_list1)train_op2 = GradientDescentOptimizer(0.0001).minimize(loss, var_list=var_list2)train_op = tf.group(train_op1, train_op2)

但是上面的代码片段对于有些变量的梯度计算了两次

var_list1 = [variables from first 5 layers]var_list2 = [the rest of variables]opt1 = tf.train.GradientDescentOptimizer(0.00001)opt2 = tf.train.GradientDescentOptimizer(0.0001)grads = tf.gradients(loss, var_list1 + var_list2)grads1 = grads[:len(var_list1)]grads2 = grads[len(var_list1):]tran_op1 = opt1.apply_gradients(zip(grads1, var_list1))train_op2 = opt2.apply_gradients(zip(grads2, var_list2))train_op = tf.group(train_op1, train_op2)