You want to give it a collection of tensors, rather than an existing tensor.
You can either:
A = torch.autograd.Variable(torch.FloatTensor([[1, 2, 3], [1, 2, 3]]))
B = torch.autograd.Variable(torch.FloatTensor([[4, 5, 6], [4, 5, 6]]))
C = torch.autograd.Variable(torch.FloatTensor([[7, 8, 9], [7, 8, 9]]))
torch.cat((A, B, C), 1)

or just use the same A, get the (roughly) same result by
A.transpose(0, 1).view(2, 9)