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import argparse |
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import json |
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import os |
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from tqdm import tqdm |
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from utils.simple_bleu import simple_score |
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def load_json(filename): |
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json_data = [] |
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with open(filename, "r", encoding="utf-8") as f: |
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if os.path.splitext(filename)[1] != ".jsonl": |
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json_data = json.load(f) |
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else: |
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for line in f: |
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json_data.append(json.loads(line)) |
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return json_data |
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def save_json(json_data, filename, option="a"): |
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directory, _ = os.path.split(filename) |
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if not os.path.exists(directory): |
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os.makedirs(directory) |
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filename = filename.replace(" ", "_") |
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with open(filename, option, encoding="utf-8") as f: |
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if not filename.endswith(".jsonl"): |
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json.dump(json_data, f, ensure_ascii=False, indent=4) |
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else: |
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for data in json_data: |
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json.dump(data, f, ensure_ascii=False) |
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f.write("\n") |
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def main(): |
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parser = argparse.ArgumentParser("argument") |
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parser.add_argument( |
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"--input_file", |
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default="./data/komt-1810k-test.jsonl", |
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type=str, |
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help="input_file", |
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) |
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parser.add_argument( |
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"--model_path", |
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default=None, |
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type=str, |
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help="model path", |
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) |
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parser.add_argument("--output", default="", type=str, help="model path") |
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parser.add_argument("--model", default="iris_7b", type=str, help="model") |
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args = parser.parse_args() |
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json_data = load_json(args.input_file) |
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if args.model == "squarelike/Gugugo-koen-7B-V1.1": |
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from models.gugugo import translate_en2ko, translate_ko2en |
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elif args.model == "jbochi/madlad400-10b-mt": |
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from models.madlad400 import translate_ko2en, translate_en2ko |
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elif args.model == "facebook/mbart-large-50-many-to-many-mmt": |
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from models.mbart50 import translate_en2ko, translate_ko2en |
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elif args.model == "facebook/nllb-200-distilled-1.3B": |
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from models.nllb200 import translate_ko2en, translate_en2ko |
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elif args.model == "Unbabel/TowerInstruct-7B-v0.1": |
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from models.TowerInstruct import translate_ko2en, translate_en2ko |
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elif args.model == "maywell/Synatra-7B-v0.3-Translation": |
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from models.synatra import translate_ko2en, translate_en2ko |
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elif args.model == "davidkim205/iris-7b": |
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from models.iris_7b import translate_ko2en, translate_en2ko |
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if args.model_path: |
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from models.iris_7b import load_model |
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load_model(args.model_path) |
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for index, data in tqdm(enumerate(json_data)): |
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chat = data["conversations"] |
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src = data["src"] |
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input = chat[0]["value"] |
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reference = chat[1]["value"] |
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def clean_text(text): |
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if chat[0]["value"].find("νκΈλ‘ λ²μνμΈμ.") != -1: |
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cur_lang = "en" |
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else: |
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cur_lang = "ko" |
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text = text.split("λ²μνμΈμ.\n", 1)[-1] |
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return text, cur_lang |
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input, cur_lang = clean_text(input) |
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def do_translation(text, cur_lang): |
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trans = "" |
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try: |
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if cur_lang == "en": |
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trans = translate_en2ko(text) |
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else: |
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trans = translate_ko2en(text) |
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except Exception as e: |
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trans = "" |
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return trans |
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generation = do_translation(input, cur_lang) |
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bleu = simple_score(reference, generation) |
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bleu = round(bleu, 3) |
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result = { |
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"index": index, |
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"reference": reference, |
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"generation": generation, |
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"bleu": bleu, |
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"lang": cur_lang, |
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"model": args.model, |
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"src": src, |
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'conversations':chat |
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} |
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print(json.dumps(result, ensure_ascii=False, indent=2)) |
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if args.output: |
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output = args.output |
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else: |
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if args.model_path: |
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filename = args.model.split("/")[-1] |
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model_num = args.model_path.split("/")[-1] |
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output = f"results_bleu/{filename}-{model_num}-result.jsonl" |
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else: |
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filename = args.model.split("/")[-1] |
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output = f"results_bleu/{filename}-result.jsonl" |
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save_json([result], output) |
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if __name__ == "__main__": |
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main() |
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