import pandas as pd
from torch.utils.data import Dataset, DataLoader
from utils.esm_utils import get_latents, load_esm2_model

class ProteinDataset(Dataset):
    def __init__(self, csv_file, tokenizer, model):
        self.data = pd.read_csv(csv_file)
        self.tokenizer = tokenizer
        self.model = model

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

    def __getitem__(self, idx):
        sequence = self.data.iloc[idx]['sequence']
        latents = get_latents(self.model, self.tokenizer, sequence)
        return latents

def get_dataloaders(config):
    tokenizer, model = load_esm2_model(config.model_name)
    
    train_dataset = ProteinDataset(config.data_path + "train.csv", tokenizer, model)
    val_dataset = ProteinDataset(config.data_path + "val.csv", tokenizer, model)
    test_dataset = ProteinDataset(config.data_path + "test.csv", tokenizer, model)
    
    train_loader = DataLoader(train_dataset, batch_size=config.training["batch_size"], shuffle=True)
    val_loader = DataLoader(val_dataset, batch_size=config.training["batch_size"], shuffle=False)
    test_loader = DataLoader(test_dataset, batch_size=config.training["batch_size"], shuffle=False)
    
    return train_loader, val_loader, test_loader