Add inference_mode

TTS/tts/models/xtts.py

@@ -363,6 +363,7 @@ class Xtts(BaseTTS):
     def device(self):
         return next(self.parameters()).device
 
+    @torch.inference_mode()
     def get_gpt_cond_latents(self, audio_path: str, length: int = 3):
         """Compute the conditioning latents for the GPT model from the given audio.
 
@@ -377,6 +378,7 @@ class Xtts(BaseTTS):
         cond_latent = self.gpt.get_style_emb(mel.to(self.device), sample=False)
         return cond_latent.transpose(1, 2)
 
+    @torch.inference_mode()
     def get_diffusion_cond_latents(
         self,
         audio_path,
@@ -399,6 +401,7 @@ class Xtts(BaseTTS):
         diffusion_latent = self.diffusion_decoder.get_conditioning(diffusion_conds)
         return diffusion_latent
 
+    @torch.inference_mode()
     def get_speaker_embedding(
         self,
         audio_path
@@ -468,7 +471,7 @@ class Xtts(BaseTTS):
         settings.update(kwargs)  # allow overriding of preset settings with kwargs
         return self.full_inference(text, ref_audio_path, language, **settings)
 
-    @torch.no_grad()
+    @torch.inference_mode()
     def full_inference(
         self,
         text,
@@ -569,7 +572,7 @@ class Xtts(BaseTTS):
             **hf_generate_kwargs,
         )
     
-    @torch.no_grad()
+    @torch.inference_mode()
     def inference(
         self,
         text,
@@ -675,6 +678,7 @@ class Xtts(BaseTTS):
         wav_gen_prev = wav_gen
         return wav_chunk, wav_gen_prev, wav_overlap
 
+    @torch.inference_mode()
     def inference_stream(
         self,
         text,