optimization

app.py

@@ -1,5 +1,4 @@
 import os
-#import random
 import datetime
 import spaces
 import torch
@@ -8,7 +7,7 @@ import gradio as gr
 import traceback
 from transformers import pipeline
 from huggingface_hub import login
-from diffusers import FluxPipeline, PNDMScheduler
+from diffusers import FluxPipeline
 from aura_sr import AuraSR
 from deep_translator import GoogleTranslator
 
@@ -60,7 +59,7 @@ pipe = FluxPipeline.from_pretrained(
 print(f"{datetime.datetime.now()} Загрузка модели FLUX.1-dev успешно завершена")
 
 # Планировщик для 25 шагов
-pipe.scheduler = PNDMScheduler.from_config(pipe.scheduler.config)
+# pipe.scheduler = PNDMScheduler.from_config(pipe.scheduler.config)
 
 print(f"{datetime.datetime.now()} Загрузка LoRA")
 pipe.load_lora_weights("Shakker-Labs/FLUX.1-dev-LoRA-add-details", weight_name="FLUX-dev-lora-add_details.safetensors")
@@ -118,16 +117,15 @@ def generate_image(object_name, remove_bg=True, upscale=True):
         return None
 
 def generate_image_stable(prompt, steps):
-    with torch.inference_mode():
-        return pipe(
-            prompt,
-            height=1024,
-            width=1024,
-            guidance_scale=4.0,
-            num_inference_steps=steps,
-            generator=torch.Generator(device).manual_seed(42),
-            num_images_per_prompt=1
-        ).images[0]
+    return pipe(
+        prompt,
+        height=1024,
+        width=1024,
+        guidance_scale=4.0,
+        num_inference_steps=steps,
+        generator=torch.Generator(device).manual_seed(42),
+        num_images_per_prompt=1
+    ).images[0]
 
 def create_template_prompt(object_name):
     template = load_text("prompt.txt")