diff --git a/scripts/tilediffusion.py b/scripts/tilediffusion.py
index a8285eb..d7c3aec 100644
--- a/scripts/tilediffusion.py
+++ b/scripts/tilediffusion.py
@@ -60,7 +60,6 @@
 import os
 import json
 import torch
-import modules
 import numpy as np
 import gradio as gr
 
@@ -75,12 +74,11 @@ from tile_methods.mixtureofdiffusers import MixtureOfDiffusers
 from tile_utils.utils import *
 from tile_utils.typing import *
 
-
 CFG_PATH = os.path.join(scripts.basedir(), 'region_configs')
 BBOX_MAX_NUM = min(getattr(shared.cmd_opts, 'md_max_regions', 8), 16)
 
-class Script(modules.scripts.Script):
-    
+
+class Script(scripts.Script):
     
     def __init__(self):
         self.controlnet_script: ModuleType = None
@@ -92,7 +90,7 @@ class Script(modules.scripts.Script):
         return 'Tiled Diffusion'
 
     def show(self, is_img2img):
-        return modules.scripts.AlwaysVisible
+        return scripts.AlwaysVisible
 
     def ui(self, is_img2img):
         tab    = 't2i'  if not is_img2img else 'i2i'
@@ -358,11 +356,8 @@ class Script(modules.scripts.Script):
                     break
 
         ''' hijack inner APIs '''
-        if not hasattr(Script, "create_sampler_original_md"):
+        if getattr(Script, "create_sampler_original_md", None) is None:
             Script.create_sampler_original_md = sd_samplers.create_sampler
-        else:
-            if Script.create_sampler_original_md is None:
-                Script.create_sampler_original_md = sd_samplers.create_sampler
         sd_samplers.create_sampler = lambda name, model: self.create_sampler_hijack(
             name, model, p, Method(method), 
             tile_width, tile_height, overlap, tile_batch_size,
@@ -433,10 +428,8 @@ class Script(modules.scripts.Script):
             print('warn: noise inversion only supports the Euler sampler, switch to it sliently...')
             name = 'Euler'
             p.sampler_name = 'Euler'
-        if name is None:
-            print('name is empty')
-        if model is None:
-            print('model is empty')
+        if name is None: print('>> name is empty')
+        if model is None: print('>> model is empty')
         sampler = Script.create_sampler_original_md(name, model)
         if method == Method.MULTI_DIFF: delegate_cls = MultiDiffusion
         elif method == Method.MIX_DIFF: delegate_cls = MixtureOfDiffusers
@@ -600,6 +593,8 @@ class Script(modules.scripts.Script):
             mem = psutil.Process(os.getpid()).memory_info()
             print(f'[Mem] rss: {mem.rss/2**30:.3f} GB, vms: {mem.vms/2**30:.3f} GB')
             from modules.shared import mem_mon as vram_mon
+            from modules.memmon import MemUsageMonitor
+            vram_mon: MemUsageMonitor
             free, total = vram_mon.cuda_mem_get_info()
             print(f'[VRAM] free: {free/2**30:.3f} GB, total: {total/2**30:.3f} GB')
         except: