import torch
from torch.utils.data import Dataset, DataLoader

class TextDataset(Dataset):
    def __init__(self, data, block_size):
        self.data = data
        self.block_size = block_size
    
    def __len__(self):
        return len(self.data) - self.block_size
    
    def __getitem__(self, idx):
        x = self.data[idx:idx + self.block_size]
        y = self.data[idx + 1:idx + self.block_size + 1]
        return x, y

def create_dataloaders(text, tokenizer, config, device):
    data = torch.tensor(tokenizer.encode(text), dtype=torch.long)
    n = int(0.9 * len(data))
    train_data = data[:n]
    val_data = data[n:]
    
    train_dataset = TextDataset(train_data, config.block_size)
    val_dataset = TextDataset(val_data, config.block_size)
    
    train_loader = DataLoader(
        train_dataset, 
        batch_size=config.batch_size, 
        shuffle=True,
        pin_memory=True
    )
    val_loader = DataLoader(
        val_dataset, 
        batch_size=config.batch_size, 
        shuffle=False,
        pin_memory=True
    )
    
    return train_loader, val_loader