Fetch是获取计算图中的数据的操作

# input1 = tf.constant(1.0)
# input2 = tf.constant(2.0)
# input3 = tf.constant(3.0)
#
# add = tf.add(input1, input3)
#
# mul = tf.multiply(input2, add)
#
# with tf.Session() as sess:
#     mul_res = sess.run(mul)
#     add_res = sess.run(add)

Feed是赋值操作，是将数据赋值到占位符操作

num1 = tf.placeholder(tf.float32)
num2 = tf.placeholder(tf.float32)

output = tf.multiply(num1, num2)

with tf.Session() as sess:
    res = sess.run(output, feed_dict={num1: [0.2], num2: [0.8]})
    print(type(res))