add default params for GradTTS

src/diffusers/pipelines/pipeline_grad_tts.py

@@ -396,7 +396,7 @@ class GradTTS(DiffusionPipeline):
         self.register_modules(unet=unet, text_encoder=text_encoder, noise_scheduler=noise_scheduler, tokenizer=tokenizer)
     
     @torch.no_grad()
-    def __call__(self, text, num_inference_steps, generator, temperature, length_scale, speaker_id=None, torch_device=None):
+    def __call__(self, text, num_inference_steps=50, temperature=1.3, length_scale=0.91, speaker_id=15, torch_device=None):
         if torch_device is None:
             torch_device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
         
@@ -427,7 +427,6 @@ class GradTTS(DiffusionPipeline):
         # Align encoded text and get mu_y
         mu_y = torch.matmul(attn.squeeze(1).transpose(1, 2), mu_x.transpose(1, 2))
         mu_y = mu_y.transpose(1, 2)
-        encoder_outputs = mu_y[:, :, :y_max_length]
 
         # Sample latent representation from terminal distribution N(mu_y, I)
         z = mu_y + torch.randn_like(mu_y, device=mu_y.device) / temperature