Upload 2 files

app.py

@@ -8,7 +8,6 @@ from diffusers import FluxControlNetPipeline, FluxControlNetModel, FluxMultiCont
 from huggingface_hub import HfFileSystem, ModelCard
 import random
 import time
-import os
 
 from env import models, num_loras, num_cns
 from mod import (clear_cache, get_repo_safetensors, is_repo_name, is_repo_exists, get_model_trigger,
@@ -130,7 +129,6 @@ def update_selection(evt: gr.SelectData, width, height):
 
 @spaces.GPU(duration=70)
 def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scale, cn_on, progress=gr.Progress(track_tqdm=True)):
-    from diffusers.utils import load_image
     global pipe
     global taef1
     global good_vae
@@ -139,7 +137,7 @@ def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scal
     try:
         good_vae.to("cuda")
         taef1.to("cuda")
-        generator = torch.Generator(device="cuda").manual_seed(seed)
+        generator = torch.Generator(device="cuda").manual_seed(int(float(seed)))
         
         with calculateDuration("Generating image"):
             # Generate image
@@ -163,10 +161,10 @@ def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scal
                     yield img
             else:
                 pipe.to("cuda")
-                if controlnet is not None: controlnet.to("cuda")
-                if controlnet_union is not None: controlnet_union.to("cuda")
                 pipe.vae = good_vae
-                pipe.controlnet = controlnet
+                if controlnet_union is not None: controlnet_union.to("cuda")
+                if controlnet is not None: controlnet.to("cuda")
+                pipe.enable_model_cpu_offload()
                 progress(0, desc="Start Inference with ControlNet.")
                 for img in pipe(
                     prompt=prompt_mash,
@@ -443,7 +441,7 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css, delete_cache
                                     lora_download = [None] * num_loras
                                     for i in range(num_loras):
                                         lora_download[i] = gr.Button(f"Get and set LoRA to {int(i+1)}")
-                    with gr.Accordion("ControlNet (🚧Under construction...🚧)", open=False, visible=False):
+                    with gr.Accordion("ControlNet (extremely slow)", open=True, visible=True):
                         with gr.Column():
                             cn_on = gr.Checkbox(False, label="Use ControlNet")
                             cn_mode = [None] * num_cns

requirements.txt

@@ -16,4 +16,4 @@ deepspeed
 mediapipe
 openai==1.37.0
 translatepy
-xformers
+accelerate