tensorflow 只恢复部分模型参数的实例
人气:0我就废话不多说了,直接上代码吧!
import tensorflow as tf def model_1(): with tf.variable_scope("var_a"): a = tf.Variable(initial_value=[1, 2, 3], name="a") vars = [var for var in tf.trainable_variables() if var.name.startswith("var_a")] print(len(vars)) return vars def model_2(): vars1 = model_1() with tf.variable_scope("var_b"): a = tf.Variable(initial_value=[1, 2, 3], name="a") vars2 = [var for var in tf.trainable_variables() if var.name.startswith("var")] print(len(vars2)) return vars1 def pretrain_model1(): print("-------- model 1 ------") vars = model_1() with tf.Session() as sess: sess.run(tf.global_variables_initializer()) saver = tf.train.Saver() saver.save(sess, "./model.ckpt") def train_model2(): print("-------- model 2 ------") model1_vars = model_2() with tf.Session() as sess: sess.run(tf.global_variables_initializer()) saver = tf.train.Saver(var_list=model1_vars) saver.restore(sess, "./model.ckpt") vars = sess.run([model1_vars]) for var in vars: print(var) step = 2 if step == 1: pretrain_model1() else: train_model2()
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