TensorFlow：四则运算

1.常量四则运算

data1 = tf.constant(6)
data2 = tf.constant(2)
dataAdd = tf.add(data1,data2)    # 加
dataMul = tf.multiply(data1,data2)    # 乘
dataSub = tf.subtract(data1,data2)    # 减
dataDiv = tf.divide(data1,data2)    # 除
with tf.Session() as sess:
    print(sess.run(dataAdd))
    print(sess.run(dataMul))
    print(sess.run(dataSub))
    print(sess.run(dataDiv))

2.变量四则运算

data1 = tf.constant(6)
data2 = tf.Variable(2)
dataAdd = tf.add(data1,data2)    # 加
dataMul = tf.multiply(data1,data2)    # 乘
dataSub = tf.subtract(data1,data2)    # 减
dataDiv = tf.divide(data1,data2)    # 除
init = tf.global_variables_initializer()
with tf.Session() as sess:
    sess.run(init)
    print(sess.run(dataAdd))
    print(sess.run(dataMul))
    print(sess.run(dataSub))
    print(sess.run(dataDiv))

3.其他用法

data1 = tf.constant(6)
data2 = tf.Variable(2)
dataAdd = tf.add(data1,data2)    # 加
dataCopy = tf.assign(data2,dataAdd)
init = tf.global_variables_initializer()
with tf.Session() as sess:
    sess.run(init)
    print('sess.run(dataCopy)',sess.run(dataCopy))
    print('dataCopy.eval()',dataCopy.eval())
    print('tf.get_default_session().run(dataCopy)',tf.get_default_session().run(dataCopy))

tf.assign(data2,dataAdd) 指的是将dataAdd赋值给data2，所以此时data2的值为8
dataCopy.eval() ： .eval()的作用类似于.run()，所以dataCopy.eval() 同等于dataAdd = tf.add(data1,data2) 即6与8的合为14，再讲14重新赋值给data2，所以结果为14
同样道理tf.get_default_session().run(dataCopy) 为14+6 =20