modules/translation/translation_base.py

import os
import torch
import gradio as gr
from abc import ABC, abstractmethod
from typing import List
from datetime import datetime

from modules.whisper.whisper_parameter import *
from modules.utils.subtitle_manager import *


class TranslationBase(ABC):
    def __init__(self,
                 model_dir: str,
                 output_dir: str):
        super().__init__()
        self.model = None
        self.model_dir = model_dir
        self.output_dir = output_dir
        os.makedirs(self.model_dir, exist_ok=True)
        os.makedirs(self.output_dir, exist_ok=True)
        self.current_model_size = None
        self.device = self.get_device()

    @abstractmethod
    def translate(self,
                  text: str
                  ):
        pass

    @abstractmethod
    def update_model(self,
                     model_size: str,
                     src_lang: str,
                     tgt_lang: str,
                     progress: gr.Progress
                     ):
        pass

    def translate_file(self,
                       fileobjs: list,
                       model_size: str,
                       src_lang: str,
                       tgt_lang: str,
                       add_timestamp: bool,
                       progress=gr.Progress()) -> list:
        """
        Translate subtitle file from source language to target language

        Parameters
        ----------
        fileobjs: list
            List of files to transcribe from gr.Files()
        model_size: str
            Whisper model size from gr.Dropdown()
        src_lang: str
            Source language of the file to translate from gr.Dropdown()
        tgt_lang: str
            Target language of the file to translate from gr.Dropdown()
        add_timestamp: bool
            Boolean value from gr.Checkbox() that determines whether to add a timestamp at the end of the filename.
        progress: gr.Progress
            Indicator to show progress directly in gradio.
            I use a forked version of whisper for this. To see more info : https://github.com/jhj0517/jhj0517-whisper/tree/add-progress-callback

        Returns
        ----------
        A List of
        String to return to gr.Textbox()
        Files to return to gr.Files()
        """
        try:
            self.update_model(model_size=model_size,
                              src_lang=src_lang,
                              tgt_lang=tgt_lang,
                              progress=progress)

            files_info = {}
            for fileobj in fileobjs:
                file_path = fileobj.name
                file_name, file_ext = os.path.splitext(os.path.basename(fileobj.name))
                if file_ext == ".srt":
                    parsed_dicts = parse_srt(file_path=file_path)
                    total_progress = len(parsed_dicts)
                    for index, dic in enumerate(parsed_dicts):
                        progress(index / total_progress, desc="Translating..")
                        translated_text = self.translate(dic["sentence"])
                        dic["sentence"] = translated_text
                    subtitle = get_serialized_srt(parsed_dicts)

                    timestamp = datetime.now().strftime("%m%d%H%M%S")
                    if add_timestamp:
                        output_path = os.path.join("outputs", "", f"{file_name}-{timestamp}.srt")
                    else:
                        output_path = os.path.join("outputs", "", f"{file_name}.srt")

                elif file_ext == ".vtt":
                    parsed_dicts = parse_vtt(file_path=file_path)
                    total_progress = len(parsed_dicts)
                    for index, dic in enumerate(parsed_dicts):
                        progress(index / total_progress, desc="Translating..")
                        translated_text = self.translate(dic["sentence"])
                        dic["sentence"] = translated_text
                    subtitle = get_serialized_vtt(parsed_dicts)

                    timestamp = datetime.now().strftime("%m%d%H%M%S")
                    if add_timestamp:
                        output_path = os.path.join(self.output_dir, "", f"{file_name}-{timestamp}.vtt")
                    else:
                        output_path = os.path.join(self.output_dir, "", f"{file_name}.vtt")

                write_file(subtitle, output_path)
                files_info[file_name] = subtitle

            total_result = ''
            for file_name, subtitle in files_info.items():
                total_result += '------------------------------------\n'
                total_result += f'{file_name}\n\n'
                total_result += f'{subtitle}'

            gr_str = f"Done! Subtitle is in the outputs/translation folder.\n\n{total_result}"
            return [gr_str, output_path]
        except Exception as e:
            print(f"Error: {str(e)}")
        finally:
            self.release_cuda_memory()
            self.remove_input_files([fileobj.name for fileobj in fileobjs])

    @staticmethod
    def get_device():
        if torch.cuda.is_available():
            return "cuda"
        elif torch.backends.mps.is_available():
            return "mps"
        else:
            return "cpu"

    @staticmethod
    def release_cuda_memory():
        if torch.cuda.is_available():
            torch.cuda.empty_cache()
            torch.cuda.reset_max_memory_allocated()

    @staticmethod
    def remove_input_files(file_paths: List[str]):
        if not file_paths:
            return

        for file_path in file_paths:
            if file_path and os.path.exists(file_path):
                os.remove(file_path)