translate.py

from typing import Tuple

import torch
from torch import Tensor

from tokenizers import Tokenizer

from transformer import Transformer
from decode_method import greedy_decode, beam_search_decode

def translate(
    model: Transformer,
    src_tokenizer: Tokenizer,
    tgt_tokenizer: Tokenizer,
    text: str,
    decode_method: str = 'greedy',
    device = torch.device('cpu')
) -> Tuple[str, Tensor]:
    """
    Translation function.

    Supported `decode_method`: 'greedy' or 'beam-search'
    
    'beam-search' doesn't give attn scores.

    Output:
        - translation (str): the translated string.
        - attn (Tensor): The decoder's attention (for visualization)
    """
    model.eval()
    with torch.no_grad():
        sos_token = torch.tensor([src_tokenizer.token_to_id('<sos>')], dtype=torch.int64)
        eos_token = torch.tensor([src_tokenizer.token_to_id('<eos>')], dtype=torch.int64)
        pad_token = torch.tensor([src_tokenizer.token_to_id('<pad>')], dtype=torch.int64)
        
        encoder_input_tokens = src_tokenizer.encode(text).ids
        # <sos> + source_text + <eos> = encoder_input
        encoder_input = torch.cat(
            [
                sos_token,
                torch.tensor(encoder_input_tokens, dtype=torch.int64),
                eos_token,
            ]
        )
        encoder_mask = (encoder_input != pad_token).unsqueeze(0).unsqueeze(0).unsqueeze(0).int() # (1, 1, seq_len)

        encoder_input = encoder_input.unsqueeze(0)
        # encoder_mask = torch.tensor(encoder_mask)
        
        assert encoder_input.size(0) == 1

        if decode_method == 'greedy':
            model_out, attn = greedy_decode(
                model, encoder_input, encoder_mask, src_tokenizer, tgt_tokenizer, 349, device, 
                give_attn=True,
            )
        elif decode_method == 'beam-search':
            model_out = beam_search_decode(
                model, encoder_input, encoder_mask, src_tokenizer, tgt_tokenizer, 349, device, 
            )
            attn = None # Beam search doesn't give attention score
        else:
            raise ValueError("Unsuppored decode method")

        model_out_text = tgt_tokenizer.decode(model_out.detach().cpu().numpy())
        return model_out_text, attn
    

from config import load_config
from load_and_save_model import load_model_tokenizer
if __name__ == '__main__':
    config = load_config(file_name='config_huge.yaml')
    model, src_tokenizer, tgt_tokenizer = load_model_tokenizer(config)
    text = "ສະບາຍດີ" # Hello.
    translation, attn = translate(
        model, src_tokenizer, tgt_tokenizer, text,
        decode_method='beam-search',
    )
    print(translation)