輸出矩陣的基本信息
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]])
# 輸出矩陣的維度
print("矩陣的維度:", data4.shape)
with tf.Session() as sess:
print("----------------------")
print("運行結果")
# 打印整個矩陣
print(sess.run(data4))
# 打印第一行
print(sess.run(data4[0]))
# 打印第一列
print(sess.run(data4[:,0]))
# 打印第一行第一列
print(sess.run(data4[0,0]))
矩陣的乘法
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]])
# 輸出矩陣的維度
print("矩陣的維度:", data4.shape)
matMul = tf.matmul(data1,data2) # 矩陣1 乘以 矩陣2
matMul2 = tf.multiply(data1,data2) # 將矩陣中各個元素相乘
matAdd = tf.add(data1,data3) # 矩陣相加
with tf.Session() as sess:
print("運算結果")
print(sess.run(matMul))
print(sess.run(matAdd))
print(sess.run(matMul2))
print("中括號一次打印多個內容")
print(sess.run([matMul, matAdd]))
矩陣的維度: (3, 2)
運算結果
[[24]]
[[9 9]]
[[12 12]
[12 12]]
中括號一次打印多個內容
[array([[24]]), array([[9, 9]])]