【深度学习】python矩阵乘积运算(multiply/maumul/*/@)

a &＃61; np.array([[1,2],[3,4]])
b &＃61; np.array([5,6])
c &＃61; np.array([[5,6],[7,8]])
print(‘a:’&＃43;’\n’,a)
print(‘b:’&＃43;’\n’,b)
print(‘c:’&＃43;’\n’,c)
#叉乘
d1&＃61;a&＃64;c
d2&＃61;tf.matmul(a,c)
d3&＃61;np.dot(a,c)
#点乘
f1&＃61;a*c
f2&＃61;tf.multiply(a,c)

with tf.compat.v1.Session() as sess:
print(‘d1:叉乘a&＃64;c’ &＃43; ‘\n’, d1)
print(‘d2:叉乘matmul(a,c)’ &＃43; ‘\n’, sess.run(d2))
print(‘d3:叉乘dot(a,c)’ &＃43; ‘\n’, d3)
print(‘f1:点乘a*c’ &＃43; ‘\n’, f1)
print(‘f2:点乘multiply(a,c)’ &＃43; ‘\n’, sess.run(f2))

测试结果如下&＃xff1a;

import torch
from torch import nnclass MyLinear(nn.Module):def __init__(self, in_features, out_features):super().__init__()self.weight &＃61; nn.Parameter(torch.randn(in_features, out_features))self.bias &＃61; nn.Parameter(torch.randn(out_features))def forward(self, input):return (input &＃64; self.weight) &＃43; 2*self.bias # 其中的&＃64;&＃xff0c;torch.matmul, torch.dot,numpy.dot.# torch.mul(), torch.multipy(), *, 是点乘积。m &＃61; MyLinear(4, 3)
sample_input &＃61; torch.randn(4)
k &＃61; m(sample_input)
print(k)