深度学习之tensorflow框架（中）

会话

• 开启会话
  • tf.Session用于完整的程序中
  • tf.InteractiveSession用于交互式上下文中的tensorflow
• 查看张量的值
  • 都必须在会话里面
  • c_new_value=new_sess.run(c_new)
  • print("c_new_value:\n",c_new_value)
  • print("a_new_value:\n",a_new.eval())

  •  1 def session_demo():
     2     """
     3     会话的演示
     4     :return:
     5     """
     6     a_t = tf.constant(2, name="a_t")
     7     b_t = tf.constant(3, name="b_t")
     8     c_t = tf.add(a_t, b_t, name="c_t")
     9     print("a_t:\n", a_t)
    10     print("b_t:\n", b_t)
    11     print("tensorflow加法运算的结果：\n", c_t)
    12 
    13     # 查看默认图
    14     # 方法1：调用方法
    15     default_g = tf.compat.v1.get_default_graph()
    16     print("default_g:\n", default_g)
    17     # 方法2：查看属性
    18     print("a_t的图属性：\n", a_t.graph)
    19     print("c_t的图属性：\n", c_t.graph)
    20 
    21     # 开启会话
    22     with tf.compat.v1.Session(config=tf.compat.v1.ConfigProto(allow_soft_placement=True,log_device_placement=True)) as sess:
    23         # c_t_value = sess.run(c_t)
    24         # print("c_t_value:\n", c_t_value)
    25         abc = sess.run([a_t,b_t,c_t])
    26         print("abc:\n",abc)
    27         print("sess的图属性：\n", sess.graph)
    28     return None
    29 
    30 
    31 def feed_demo():
    32     """
    33     feed操作
    34     :return:
    35     """
    36     a=tf.compat.v1.placeholder(dtype=tf.float32)
    37     b=tf.compat.v1.placeholder(dtype=tf.float32)
    38     sum_ab=tf.add(a,b)
    39     print("a:\n",a)
    40     print("b:\n",b)
    41     print("sum_ab:\n",sum_ab)
    42 
    43     with tf.compat.v1.Session() as sess:
    44         sum_ab_value=sess.run(sum_ab,feed_dict={a:3.9,b:3.5})
    45         print("sum_ab_value:\n",sum_ab_value)
    46 
    47     return None