Pytorch中的torch.cat()函数 按维数0拼接 按维数1拼接

cat( )的用法

按维数0拼接（竖着拼）
C = torch.cat( (A,B),0 )

按维数1拼接（横着拼）
C = torch.cat( (A,B),1 )

按维数0拼接

A=torch.ones(2,3)    #2x3的张量（矩阵）
print("A:\n",A,"\nA.shape:\n",A.shape,"\n")

B=2*torch.ones(4,3)  #4x3的张量（矩阵）
print("B:\n",B,"\nB.shape:\n",B.shape,"\n")

C=torch.cat((A,B),0)  #按维数0（行）拼接
print("C:\n",C,"\nC.shape:\n",C.shape,"\n")

A:
 tensor([[1., 1., 1.],
        [1., 1., 1.]]) 
A.shape:
 torch.Size([2, 3]) 

B:
 tensor([[2., 2., 2.],
        [2., 2., 2.],
        [2., 2., 2.],
        [2., 2., 2.]]) 
B.shape:
 torch.Size([4, 3]) 

C:
 tensor([[1., 1., 1.],
        [1., 1., 1.],
        [2., 2., 2.],
        [2., 2., 2.],
        [2., 2., 2.],
        [2., 2., 2.]]) 
C.shape:
 torch.Size([6, 3]) 

按维数1拼接

A=torch.ones(2,3)    #2x3的张量（矩阵）
print("A:\n",A,"\nA.shape:\n",A.shape,"\n")

B=2*torch.ones(2,4)  #4x3的张量（矩阵）
print("B:\n",B,"\nB.shape:\n",B.shape,"\n")

C=torch.cat((A,B),1)  #按维数0（行）拼接
print("C:\n",C,"\nC.shape:\n",C.shape,"\n")

A:
 tensor([[1., 1., 1.],
        [1., 1., 1.]]) 
A.shape:
 torch.Size([2, 3]) 

B:
 tensor([[2., 2., 2., 2.],
        [2., 2., 2., 2.]]) 
B.shape:
 torch.Size([2, 4]) 

C:
 tensor([[1., 1., 1., 2., 2., 2., 2.],
        [1., 1., 1., 2., 2., 2., 2.]]) 
C.shape:
 torch.Size([2, 7])