Getting tensor values of a dataset

1

Is there a direct way to get tensors of a dataset? To do so, I’m currently wrapping the dataset with a dataloader, iterating over it and extracting tensors for data and the label.

I was wondering whether there’s a more straightforward way of doing this.

2

You should be able to just iterate over the dataset directly, without requiring a dataloader.

class MyDataset(torch.utils.data.Dataset):
    def __init__(self, n):
        self.data = list(range(n))
    def __len__(self):
        return len(self.data)
    def __getitem__(self, idx):
        return self.data[idx]

my_dataset = MyDataset(100)
for i in my_dataset:
    print(i, end=",")

Output:
0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,
1 Like