Update back-cod.py

back-cod.py

@@ -17,7 +17,10 @@ from transformers import CLIPTextModel, T5EncoderModel, AutoModel, T5Tokenizer,
 from typing import Union
 from diffusers.utils.torch_utils import randn_tensor
 from tqdm import tqdm
+from transformers import pipeline
+translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
 
+    
 class Tango2Pipeline(DiffusionPipeline):
     def __init__(
         self,
@@ -243,9 +246,14 @@ pipe = Tango2Pipeline(vae=tango.vae,
     
 @spaces.GPU(duration=60)
 def gradio_generate(prompt, output_format, steps, guidance):
-    output_wave = pipe(prompt,steps,guidance) ## Using pipeliine automatically uses flash attention for torch2.0 above
-    #output_wave = tango.generate(prompt, steps, guidance)
-    # output_filename = f"{prompt.replace(' ', '_')}_{steps}_{guidance}"[:250] + ".wav"
+    # 한글이 포함되어 있는지 확인
+    if any(ord('가') <= ord(char) <= ord('힣') for char in prompt):
+        # 한글을 영어로 번역
+        translation = translator(prompt)[0]['translation_text']
+        prompt = translation
+        print(f"Translated prompt: {prompt}")
+    
+    output_wave = pipe(prompt,steps,guidance)
     output_wave = output_wave.audios[0]
     output_filename = "temp.wav"
     wavio.write(output_filename, output_wave, rate=16000, sampwidth=2)