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| import torch | |
| def prepare_position_embeddings(opt, encoder_vocab, sequences): | |
| vocab_size = len(encoder_vocab) | |
| num_positions = sequences.size(-2) | |
| position_embeddings = torch.LongTensor( | |
| range(vocab_size, vocab_size + num_positions)).to(sequences.device) | |
| sequences = sequences.repeat(1, 1, 2) | |
| sequences[:, :, 1] = position_embeddings | |
| return sequences | |