Update app.py

app.py

@@ -4,43 +4,11 @@ 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,
-)
-
-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)()
-
 
 
 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 = get_scheduler(pipe.scheduler.config, sampler)
 
 pipe.compile()
 
@@ -64,7 +32,6 @@ 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]