Update space

app.py

@@ -1,6 +1,8 @@
 import gradio as gr
 import numpy as np
 import random
+from utils import generation_sdxl
+import functools
 from diffusers import DiffusionPipeline, UNet2DConditionModel
 import torch
 
@@ -28,17 +30,34 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
         
     generator = torch.Generator().manual_seed(seed)
     
-    image = pipe(
-        prompt = prompt, 
-        negative_prompt = negative_prompt,
-        guidance_scale = guidance_scale, 
-        num_inference_steps = num_inference_steps, 
-        width = width, 
-        height = height,
-        generator = generator
-    ).images[0] 
     
-    return image
+    prompt = ['Long-exposure night photography of a starry sky over a mountain range, with light trails.']
+
+
+    text_encoders = [pipe.text_encoder, pipe.text_encoder_2]
+    tokenizers = [pipe.tokenizer, pipe.tokenizer_2]
+
+    compute_embeddings_fn = functools.partial(
+        generation_sdxl.compute_embeddings,
+        proportion_empty_prompts=0,
+        text_encoders=text_encoders,
+        tokenizers=tokenizers,
+    )
+    images = generation_sdxl.sample_deterministic(
+            pipe,
+            prompt,
+            num_inference_steps=4,
+            generator=generator,
+            guidance_scale=7.0,
+            is_sdxl=True,
+            timesteps=[249, 499, 699, 999],
+            use_dynamic_guidance=False,
+            tau1=1.0,
+            tau2=1.0,
+            compute_embeddings_fn=compute_embeddings_fn
+        )[0]
+
+    return images
 
 examples = [
     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",