(batch_size)
| 560 | return (input_tensor, target_tensor) |
| 561 | |
| 562 | def get_dataloader(batch_size): |
| 563 | input_lang, output_lang, pairs = prepareData('eng', 'fra', True) |
| 564 | |
| 565 | n = len(pairs) |
| 566 | input_ids = np.zeros((n, MAX_LENGTH), dtype=np.int32) |
| 567 | target_ids = np.zeros((n, MAX_LENGTH), dtype=np.int32) |
| 568 | |
| 569 | for idx, (inp, tgt) in enumerate(pairs): |
| 570 | inp_ids = indexesFromSentence(input_lang, inp) |
| 571 | tgt_ids = indexesFromSentence(output_lang, tgt) |
| 572 | inp_ids.append(EOS_token) |
| 573 | tgt_ids.append(EOS_token) |
| 574 | input_ids[idx, :len(inp_ids)] = inp_ids |
| 575 | target_ids[idx, :len(tgt_ids)] = tgt_ids |
| 576 | |
| 577 | train_data = TensorDataset(torch.LongTensor(input_ids).to(device), |
| 578 | torch.LongTensor(target_ids).to(device)) |
| 579 | |
| 580 | train_sampler = RandomSampler(train_data) |
| 581 | train_dataloader = DataLoader(train_data, sampler=train_sampler, batch_size=batch_size) |
| 582 | return input_lang, output_lang, train_dataloader |
| 583 | |
| 584 | |
| 585 | ###################################################################### |
no test coverage detected