1.placeholder 占位符 可以通过run方法传入值
测试代码如下:
1 # encoding:utf-8 2 3 import tensorflow as tf 4 5 # placeholder 占位符 可以由用户输入 6 data1 = tf.placeholder(tf.float32) 7 data2 = tf.placeholder(tf.float32) 8 dataAdd = tf.add(data1,data2) 9 with tf.Session() as sess: 10 print(sess.run(dataAdd,feed_dict={data1:6, data2:2})) 11 print("end!")
运行结果如下:
2.矩阵的定义
类似于二维数组,测试代码如下:
1 # encoding:utf-8 2 3 import tensorflow as tf 4 5 # 类比 数组M行N列 6 data1 = tf.constant([[6,6]]) # M=1 N=1 7 data2 = tf.constant([[2], 8 [2]]) # M=2 N=1 9 data3 = tf.constant([[3,3]]) # M=1 N=1 10 data4 = tf.constant([[1,2], 11 [3,4], 12 [5,6]]) # M=3 N=2 13 print(data4.shape) # 打印该矩阵的维度 14 with tf.Session() as sess: 15 print(sess.run(data4)) 16 print(sess.run(data4[0])) # 打印第一行 17 print(sess.run(data4[:,0])) # 打印第一列 18 print(sess.run(data4[0,0])) # 打印一行一列的数 19 print("end!")
运行结果如下:
3.矩阵的基本运算
同维度矩阵相加减,内积,外积等,测试代码如下:
1 # encoding:utf-8 2 3 import tensorflow as tf 4 5 data1 = tf.constant([[6,6]]) 6 data2 = tf.constant([[2], 7 [2]]) 8 data3 = tf.constant([[3,3]]) 9 data4 = tf.constant([[1,2], 10 [3,4], 11 [5,6]]) 12 matMul = tf.matmul(data1,data2) 13 matMul2 = tf.multiply(data1,data2) 14 matAdd = tf.add(data1,data3) 15 with tf.Session() as sess: 16 print(sess.run(matMul)) # 矩阵内积 17 print("---------------------------") 18 print(sess.run(matAdd)) # 矩阵相加 矩阵相减类似 19 print("---------------------------") 20 print(sess.run(matMul2)) # 矩阵外积 21 print("---------------------------") 22 print(sess.run([matMul,matAdd])) #打印多个内容 23 print("end!")
运行结果如下:
4.特殊矩阵
特殊矩阵的测试代码如下:
1 # encoding:utf-8 2 3 import tensorflow as tf 4 5 # 特殊矩阵的测试 6 # 全零矩阵的两种定义方式 7 mat0 = tf.constant([[0,0,0],[0,0,0]]) 8 mat1 = tf.zeros([2,3]) 9 # 全1矩阵 10 mat2 = tf.ones([3,2]) 11 # 填充矩阵 12 mat3 = tf.fill([2,2],16) 13 # 归零矩阵 14 mat4 = tf.constant([[2],[3],[4]]) 15 mat5 = tf.zeros_like(mat4) 16 # 等间隔矩阵 17 mat6 = tf.linspace(0.0,2.0,11) 18 # 随机矩阵 19 mat7 = tf.random_uniform([2,3],-1,2) 20 with tf.Session() as sess: 21 print(sess.run(mat0)) # 22 print("---------------------------") 23 print(sess.run(mat1)) 24 print("---------------------------") 25 print(sess.run(mat2)) 26 print("---------------------------") 27 print(sess.run(mat3)) 28 print("---------------------------") 29 print(sess.run(mat4)) 30 print("---------------------------") 31 print(sess.run(mat5)) 32 print("---------------------------") 33 print(sess.run(mat6)) 34 print("---------------------------") 35 print(sess.run(mat7)) 36 print("---------------------------") 37 print("end!")
运行结果如下: