python中矩阵加法_矩阵创建及加法运算-PyTorch

程序代码：

importtorch

# 构建一个未初始化的4 * 5的矩阵

x1 = torch.empty(4, 5)

print("x1 :",x1)

# 构建一个随机初始化的4 * 5的矩阵

x2 = torch.rand(4, 5)

print("x2 :",x2)

# 获取矩阵的大小

print("x2的大小:", x2.size())

# 加法

# 方法一: 使用+运算符实现加法

y2 = torch.rand(4, 5)

print("y2 : ", y2)

print("x2 + y2 :", x2 + y2)

# 加法

# 方法二: 使用函数torch.add()实现加法

print("x2 + y2 :", torch.add(x2, y2))

# 加法

# 方法三: 输出到一个向量

result = torch.Tensor(4, 5)

torch.add(x2, y2, out=result)

print("result :",result)

# 加法

# 方法四: 把x加到y上

y2.add_(x2)

print("y2 :", y2)

运行结果：

x1 : tensor([[0.0000, 0.0000, 0.0000, 0.0000, 0.0000],

[0.0000, 0.0000, 0.0000, 0.0000, 0.0000],

[0.0000, 0.0000, 0.0000, 0.0000, 0.0000],

[0.0000, 0.0000, 0.0000, 0.0000, 0.0000]])

x2 : tensor([[0.8977, 0.5756, 0.1564, 0.7000, 0.5113],

[0.6446, 0.0310, 0.7990, 0.1205, 0.6459],

[0.9925, 0.9360, 0.3241, 0.9435, 0.7958],

[0.9179, 0.7885, 0.3862, 0.9539, 0.7838]])

x2的大小: torch.Size([4, 5])

y2 : tensor([[0.7996, 0.0030, 0.2026, 0.3782, 0.7135],

[0.8308, 0.1337, 0.1978, 0.8895, 0.8733],

[0.4892, 0.8054, 0.5245, 0.9167, 0.0088],

[0.7138, 0.9085, 0.6481, 0.9722, 0.2863]])

x2 + y2 : tensor([[1.6973, 0.5785, 0.3590, 1.0782, 1.2248],

[1.4754, 0.1647, 0.9968, 1.0100, 1.5193],

[1.4817, 1.7414, 0.8486, 1.8602, 0.8046],

[1.6317, 1.6970, 1.0343, 1.9262, 1.0701]])

x2 + y2 : tensor([[1.6973, 0.5785, 0.3590, 1.0782, 1.2248],

[1.4754, 0.1647, 0.9968, 1.0100, 1.5193],

[1.4817, 1.7414, 0.8486, 1.8602, 0.8046],

[1.6317, 1.6970, 1.0343, 1.9262, 1.0701]])

result : tensor([[1.6973, 0.5785, 0.3590, 1.0782, 1.2248],

[1.4754, 0.1647, 0.9968, 1.0100, 1.5193],

[1.4817, 1.7414, 0.8486, 1.8602, 0.8046],

[1.6317, 1.6970, 1.0343, 1.9262, 1.0701]])

y2 : tensor([[1.6973, 0.5785, 0.3590, 1.0782, 1.2248],

[1.4754, 0.1647, 0.9968, 1.0100, 1.5193],

[1.4817, 1.7414, 0.8486, 1.8602, 0.8046],

[1.6317, 1.6970, 1.0343, 1.9262, 1.0701]])