# utils/data_loader.py
import torch
from torch.utils.data import Dataset, DataLoader

class CustomDataset(Dataset):
    def __init__(self, data):
        self.data = data

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

    def __getitem__(self, idx):
        return self.data[idx]

def load_data(batch_size=32):
    # Dummy data
    data = [torch.randn(10) for _ in range(1000)]
    dataset = CustomDataset(data)
    loader = DataLoader(dataset, batch_size=batch_size, shuffle=True)
    return loader