2-14 矩阵基础1

#placehold
import tensorflow as tf
data1 = tf.placeholder(tf.float32)
data2 = tf.placeholder(tf.float32)
dataAdd = tf.add(data1,data2)
with tf.Session() as sess:
    print(sess.run(dataAdd,feed_dict={data1:6,data2:2}))
    # 1 dataAdd 2 data (feed_dict = {1:6,2:2})
print('end!')

#类比 数组 M行N列 [] 内部[] [里面 列数据] [] 中括号整体 行数
#[[6,6]] [[6,6]]
import tensorflow as tf
data1 = tf.constant([[6,6]])
data2 = tf.constant([[2],
                     [2]])
data3 = tf.constant([[3,3]])
data4 = tf.constant([[1,2],
                     [3,4],
                     [5,6]])
print(data4.shape)# 维度
with tf.Session() as sess:
    print(sess.run(data4)) # 打印整体
    print(sess.run(data4[0]))# 打印某一行
    print(sess.run(data4[:,0]))#MN 列
    print(sess.run(data4[0,0]))# 1 1
    print(sess.run(data4[0,1]))# 1 2  MN = 0  32 = M012 N01