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dataset.py
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dataset.py
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import os
import json
import torch
from torch.utils.data import Dataset
from pytorch_transformers import GPT2Tokenizer
from prepare_data import add_special_tokens
class GPT21024Dataset(Dataset):
def __init__(self, root_dir, ids_file, mode='train',length=None):
self.root_dir = root_dir
self.tokenizer = add_special_tokens()
with open(ids_file,'r') as f:
if mode=='train':
self.idxs = json.load(f)['train_ids']
elif mode=='valid':
self.idxs = json.load(f)['valid_ids']
else:
self.idxs = json.load(f)['test_ids']
if len == None:
self.len = len(self.idxs)
else:
self.len = length
def __len__(self):
return self.len
def __getitem__(self,idx):
idx = self.idxs[idx]
file_name = os.path.join(self.root_dir,str(idx)+".json")
with open(file_name,'r') as f:
data = json.load(f)
text = self.tokenizer.encode(self.tokenizer.pad_token)*1024
content = data['article'] + self.tokenizer.encode(self.tokenizer.sep_token) + data['abstract']
text[:len(content)] = content
text = torch.tensor(text)
sample = {'article': text, 'sum_idx': len(data['article'])}
return sample