Update app.py

app.py

@@ -4,13 +4,23 @@ import random
 from diffusers import DiffusionPipeline
 from optimum.intel.openvino import OVStableDiffusionPipeline
 import torch
+from typing import Callable, Dict, Optional, Tuple
+from diffusers import (
+    DDIMScheduler,
+    DPMSolverMultistepScheduler,
+    DPMSolverSinglestepScheduler,
+    EulerAncestralDiscreteScheduler,
+    EulerDiscreteScheduler,
+)
 
 
 model_id = "helenai/Linaqruf-anything-v3.0-ov"
+num_inference_steps = 25
+sampler = "Euler a"
 
 pipe = OVStableDiffusionPipeline.from_pretrained(model_id, compile=False)
 pipe.reshape( batch_size=1, height=256, width=256, num_images_per_prompt=1)
-pipe.scheduler = utils.get_scheduler(pipe.scheduler.config, "Euler a")
+pipe.scheduler = get_scheduler(pipe.scheduler.config, sampler)
 
 pipe.compile()
 
@@ -34,12 +44,35 @@ def infer(prompt,negative_prompt):
             (((mutation))), ((mutilated)), (out of frame), ((poorly drawn face)), poorly drawn feet, \
             ((poorly drawn hands)), tiling, (too many fingers), ((ugly)), wierd colors, (((long neck))), \
             ugly, words, wrinkles, writing",
+        num_inference_steps=num_inference_steps,
         width = 256, 
         height = 256,
     ).images[0] 
     
     return image
 
+
+def get_scheduler(scheduler_config: Dict, name: str) -> Optional[Callable]:
+    scheduler_factory_map = {
+        "DPM++ 2M Karras": lambda: DPMSolverMultistepScheduler.from_config(
+            scheduler_config, use_karras_sigmas=True
+        ),
+        "DPM++ SDE Karras": lambda: DPMSolverSinglestepScheduler.from_config(
+            scheduler_config, use_karras_sigmas=True
+        ),
+        "DPM++ 2M SDE Karras": lambda: DPMSolverMultistepScheduler.from_config(
+            scheduler_config, use_karras_sigmas=True, algorithm_type="sde-dpmsolver++"
+        ),
+        "Euler": lambda: EulerDiscreteScheduler.from_config(scheduler_config),
+        "Euler a": lambda: EulerAncestralDiscreteScheduler.from_config(
+            scheduler_config
+        ),
+        "DDIM": lambda: DDIMScheduler.from_config(scheduler_config),
+    }
+    return scheduler_factory_map.get(name, lambda: None)()
+
+
+
 examples = [
     "A cute kitten, Japanese cartoon style.",
     "A sweet family, dad stands next to mom, mom holds baby girl.",