如何在Tensorflow 1.x中打印训练期间的值

import tensorflow as tf

# 定义输入张量
input_tensor = tf.placeholder(tf.float32, shape=[None, input_size], name='input_tensor')

# 定义模型
# ...

# 定义损失函数
# ...

# 定义优化器
# ...

# 定义打印操作
print_op = tf.Print(loss, [loss], "Loss:")

# 定义训练操作
train_op = optimizer.minimize(loss)

with tf.Session() as sess:
    # 初始化变量
    sess.run(tf.global_variables_initializer())

    # 开始训练
    for i in range(num_epochs):
        # 执行训练操作，并同时执行打印操作
        _, loss_value = sess.run([train_op, print_op], feed_dict={input_tensor: input_data})

        # 打印训练期间的损失值
        print("Step: {}, Loss: {}".format(i, loss_value))