The third iteration of the numbers dataset now with multiple data output types

numbers-dataset-3.py

from torch.utils.data import Dataset
import torch

class NumbersDataset(Dataset):
    def __init__(self, low, high):
        self.samples = list(range(low, high))

    def __len__(self):
        return len(self.samples)

    def __getitem__(self, idx):
        n = self.samples[idx]
        successors = torch.arange(4).float() + n + 1
        noisy = torch.randn(4) + successors
        return str(n), successors, noisy


if __name__ == '__main__':
    from torch.utils.data import DataLoader

    dataset = NumbersDataset(100, 120)
    dataloader = DataLoader(dataset, batch_size=10, shuffle=True)
    print(next(iter(dataloader)))

Please run this code again, it ain't returning a string pal.

@susheemmaurya 💯 You're right! Must've slipped past the radar 😅. Updated the code. Hope you're enjoying the article.

Yes @syaffers! I loved it, never seen a code which is so elegant. Also the article alongside was beautifully crafted.
Kudos pal!

@abhirupkamath Thanks dude! Much appreciated 😁