Type Error: only integer tensors of a single element can be converted to an index

1

I wrote a dataloader and dataset class that below

class Dataset():
    def __init__(self, x, y,z,u): 
        self.x = x+z
        self.y = torch.tensor([y] * len(x)+[u] * len(z) )
    def __len__(self): 
        return len(self.x)
    def __getitem__(self, i): 
        return self.x[i],self.y[i]

class DataLoader():
    def __init__(self, ds, bs): 
        self.ds, self.bs = ds, bs
    def __iter__(self):
        n = len(self.ds)
        l = torch.randperm(n) 
        for i in range(0, n, self.bs): 
            idxs_l = l[i:i+self.bs]
            yield self.ds[idxs_l]

And I get this error for yield self.ds[idxs_l]

*TypeError Traceback (most recent call last)
in
----> 1 batch = next(iter(dataloader))

in iter(self)
7 for i in range(0, n, self.bs):
8 idxs_l = l[i:i+self.bs]
----> 9 yield self.ds[idxs_l]

in getitem(self, i)
8 return len(self.x)
9 def getitem(self, i):
—> 10 return self.x[i],self.y[i]

TypeError: only integer tensors of a single element can be converted to an index*

What should I do?

2

I’m and not 100% sure if this is what you want but you could try

yield self.ds.gather(DIM, torch.tensor(idxs_l))

where dim is the dimension that you want to index on.