Tensorflow入門筆記——一、常量與變量 操作數與佔位符

開發者峯會：TensorflowLite

中文官網：https：//tensorflow.google.cn/

中文社區：http://www.tensorfly.cn/

 

一、常量與變量

import tensorflow as tf
import numpy as np
print(tf.__version__)

#變量定義的幾種方法
def var_demo():
    # 1th
    a = tf.Variable(tf.linspace(-5.,5.,10),dtype=tf.float32)
    # 2th
    b = tf.Variable(tf.random_normal([3,3], mean=1.0,stddev=2.0, dtype=tf.float32), dtype=tf.float32)
    # 3th
    c = tf.Variable(b.initialized_value(), dtype=tf.float32)
    # 4th
    d = tf.Variable(tf.zeros([3,3], dtype=tf.float32), dtype=tf.float32)
    # 5th
    e = tf.assign(a, tf.linspace(-1.,1.,10))

    f = tf.cast(e, dtype=tf.int32)

    c1 = tf.constant(3)
    c2 = tf.constant([2,3])

    # 初始化方式
    init = tf.global_variables_initializer()
    sess = tf.Session()
    sess.run(init)
    print(sess.run(a))
    print(sess.run(b))
    print(sess.run(c))
    print(sess.run(d))
    print(sess.run(e))
    print(sess.run(f))

    print(sess.run(c1))
    print(sess.run(c2))

var_demo()

 

二、操作數與佔位符

import tensorflow as tf
import numpy as np
print(tf.__version__)

def ops_demo():
    a = tf.constant([[1, 2, 3], [4, 5, 6]])
    b = tf.constant(4)
    c = tf.Variable(tf.random_normal([2,3], 1.0,3.0), dtype=tf.float32)
    d = tf.add(c, tf.cast(tf.divide(a, b), dtype=tf.float32))

    m1 = tf.Variable(tf.random_normal([3, 3], 1.0, 3), dtype=tf.float32)
    m2 = tf.Variable(tf.random_normal([3, 3], 3.0, 1), dtype=tf.float32)
    m3 = tf.add(m1, m2)
    m4 = tf.subtract(m1, m2)
    m5 = tf.divide(m1, m2)
    m6 = tf.multiply(m1, m2)

    mm = tf.matmul(m1, m2)

    x = tf.placeholder(shape=[3,3], dtype=tf.float32)
    y = tf.placeholder(shape=[3,2], dtype=tf.float32)

    xy = tf.matmul(x, y)

    #初始化
    init = tf.global_variables_initializer()
    sess = tf.Session()
    sess.run(init)

    xy_result = sess.run(xy, feed_dict={x: [[1,1,1], [2,2,2],[3,3,3]], y:[[4,4],[5,5],[6,6]]})
    print(xy_result)


ops_demo()