Dataset.py

import pandas as pd
from transformers import AutoTokenizer

class MyDataset:
    def __init__(self, data_file, tokenizer):
        self.data = pd.read_csv(data_file)
        self.tokenizer = tokenizer

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

    def __getitem__(self, idx):
        text = self.data.iloc[idx, 0]
        agents = self.data.iloc[idx, 1]
        actions = self.data.iloc[idx, 2]

        encoding = self.tokenizer.encode_plus(
            text,
            max_length=512,
            padding='max_length',
            truncation=True,
            return_attention_mask=True,
            return_tensors='pt'
        )

        return {
            'input_ids': encoding['input_ids'].flatten(),
            'attention_mask': encoding['attention_mask'].flatten(),
            'labels_agents': torch.tensor(agents),
            'labels_actions': torch.tensor(actions)
        }