Update app_quant_latent1.py

app_quant_latent1.py

@@ -251,49 +251,49 @@ from PIL import Image
 import torch
 
 def safe_generate_with_latents(
-transformer,
-vae,
-text_encoder,
-tokenizer,
-scheduler,
-pipe,
-prompt,
-height,
-width,
-steps,
-guidance_scale,
-negative_prompt,
-num_images_per_prompt,
-generator,
-cfg_normalization,
-cfg_truncation,
-max_sequence_length,
-):
+ transformer,
+ vae,
+ text_encoder,
+ tokenizer,
+ scheduler,
+ pipe,
+ prompt,
+ height,
+ width,
+ steps,
+ guidance_scale,
+ negative_prompt,
+ num_images_per_prompt,
+ generator,
+ cfg_normalization,
+ cfg_truncation,
+ max_sequence_length,
+ ):
 
  try:
 
- latents_or_images = generate(
-  transformer=transformer,
-  vae=vae,
-  text_encoder=text_encoder,
-  tokenizer=tokenizer,
-  scheduler=scheduler,
-  prompt=prompt,
-  height=height,
-  width=width,
-  num_inference_steps=steps,
-  guidance_scale=guidance_scale,
-  negative_prompt=negative_prompt,
-  num_images_per_prompt=num_images_per_prompt,
-  generator=generator,
-  cfg_normalization=cfg_normalization,
-  cfg_truncation=cfg_truncation,
-  max_sequence_length=max_sequence_length,
-  output_type="latent",  # IMPORTANT
-  )
-
-
-  return latents_or_images, None
+   latents_or_images = generate(
+   transformer=transformer,
+   vae=vae,
+   text_encoder=text_encoder,
+   tokenizer=tokenizer,
+   scheduler=scheduler,
+   prompt=prompt,
+   height=height,
+   width=width,
+   num_inference_steps=steps,
+   guidance_scale=guidance_scale,
+   negative_prompt=negative_prompt,
+   num_images_per_prompt=num_images_per_prompt,
+   generator=generator,
+   cfg_normalization=cfg_normalization,
+   cfg_truncation=cfg_truncation,
+   max_sequence_length=max_sequence_length,
+   output_type="latent",  # IMPORTANT
+   )
+
+
+ return latents_or_images, None
 
  except Exception as e:
     return None, e