Update pipeline_glide.py

pipeline_glide.py

@@ -792,9 +792,7 @@ class GLIDE(DiffusionPipeline):
             frac = (model_var_values + 1) / 2
             model_log_variance = frac * max_log + (1 - frac) * min_log
 
-            pred_prev_image = self.text_noise_scheduler.step(
-                noise_residual, image, t, num_inference_steps_upscale, eta, use_clipped_residual=True
-            )
+            pred_prev_image = self.text_noise_scheduler.step(noise_residual, image, t)
             noise = torch.randn(image.shape, generator=generator).to(torch_device)
             variance = torch.exp(0.5 * model_log_variance) * noise