>>> import torch
>>> a=torch.randn(3)
>>> b=torch.randn(3)
>>> a
tensor([ 0.4886, 0.1983, -1.8426])
>>> b
tensor([-0.5119, 0.6101, 0.9693])
>>> torch.cat((a,b))
tensor([ 0.4886, 0.1983, -1.8426, -0.5119, 0.6101, 0.9693])
2. Concatenating 2d tensors
>>> a=torch.randn(2,3)
>>> a
tensor([[-0.1045, 0.5538, -1.8206],
[-0.6275, 1.6419, 0.3089]])
>>> b=torch.randn(2,3)
>>> b
tensor([[ 0.4254, -0.1717, -0.2772],
[-0.1911, -0.9333, -1.3382]])
>>> torch.cat((a,b),1) # horizontal concatenation
tensor([[-0.1045, 0.5538, -1.8206, 0.4254, -0.1717, -0.2772],
[-0.6275, 1.6419, 0.3089, -0.1911, -0.9333, -1.3382]])
>>> torch.hstack((a,b))
tensor([[-0.1045, 0.5538, -1.8206, 0.4254, -0.1717, -0.2772],
[-0.6275, 1.6419, 0.3089, -0.1911, -0.9333, -1.3382]])
>>> torch.cat((a,b),0) # vertical concatenation
tensor([[-0.1045, 0.5538, -1.8206],
[-0.6275, 1.6419, 0.3089],
[ 0.4254, -0.1717, -0.2772],
[-0.1911, -0.9333, -1.3382]])
>>> torch.vstack((a,b))
tensor([[-0.1045, 0.5538, -1.8206],
[-0.6275, 1.6419, 0.3089],
[ 0.4254, -0.1717, -0.2772],
[-0.1911, -0.9333, -1.3382]])