python 中的@运算符使用

n=100
x = torch.ones(n,2) 
x[:,0].unifORM_(-1.,1)
x[:5]
a = tensor(3.,2)
y = x@a + torch.rand(n)

import Tensorflow as tf
import numpy as np

a = np.array([[1,2],[3,4]])
b = np.array([5,6])
c = np.array([[5,6],[7,8]])
print('a:'+'\n',a)
print('b:'+'\n',b)
print('c:'+'\n',c)
#叉乘
d1=a@c
d2=tf.matmul(a,c)
d3=np.dot(a,c)
#点乘
f1=a*c
f2=tf.multiply(a,c)

with tf.compat.v1.Session() as sess:
    print('d1:叉乘a@c' + '\n', d1)
    print('d2:叉乘matmul(a,c)' + '\n', sess.run(d2))
    print('d3:叉乘dot(a,c)' + '\n', d3)
    print('f1:点乘a*c' + '\n', f1)
    print('f2:点乘multiply(a,c)' + '\n', sess.run(f2))