Hello,
I now have two point sets (tensor) A and B that shape like
A.size() >>(50, 3) , example: [ [0, 0, 0], [0, 1, 2], …, [1, 1, 1]]
B.size() >>(10, 3)
where the first dimension stands for number of points and the second dim stands for coordinates (x,y,z)
To some extent, the question could also be simplified into " Finding common elements between two tensors ". Is there a quick way to do this without nested loop like :
def is_corr(a, b):
    corr = []
    index = []
    for idx, ele_b in enumerate(b):
        cur_b = ele_b
        for ids, ele_a in enumerate(a):
            if torch.equal(ele_a, cur_b):
                corr.append(ele_a)
                index.append(ids)

    return corr, index

Thanks