major refactoring of modules

Signed-off-by: Vladimir Mandic <mandic00@live.com>

.pylintrc

@@ -7,32 +7,27 @@ fail-on=
 fail-under=10
 ignore=CVS
 ignore-paths=/usr/lib/.*$,
+             venv,
+             .git,
+             .ruff_cache,
+             .vscode,
              modules/apg,
-             modules/consistory,
+             modules/cfgzero,
              modules/control/proc,
              modules/control/units,
-             modules/ctrlx,
              modules/dml,
-             modules/freescale,
+             modules/flash_attn_triton_amd,
              modules/ggml,
              modules/hidiffusion,
-             modules/hijack,
+             modules/hijack/ddpm_edit.py,
-             modules/instantir,
+             modules/intel,
              modules/intel/ipex,
-             modules/intel/openvino,
              modules/k-diffusion,
-             modules/flex2,
              modules/ldsr,
-             modules/hidream,
-             modules/meissonic,
-             modules/mod,
-             modules/omnigen,
-             modules/omnigen2,
              modules/onnx_impl,
              modules/pag,
-             modules/pixelsmith,
+             modules/postprocess/aurasr_arch.py,
              modules/prompt_parser_xhinker.py,
-             modules/pulid/eva_clip,
              modules/ras,
              modules/rife,
              modules/schedulers,
@@ -40,15 +35,26 @@ ignore-paths=/usr/lib/.*$,
              modules/teacache,
              modules/todo,
              modules/unipc,
-             modules/xadapter,
+             pipelines/flex2,
-             modules/cfgzero,
+             pipelines/hidream,
-             modules/infiniteyou,
+             pipelines/meissonic,
-             modules/flash_attn_triton_amd,
+             pipelines/omnigen2,
-             scripts/softfill.py,
+             pipelines/segmoe,
+             scripts/consistory,
+             scripts/ctrlx,
+             scripts/demofusion,
+             scripts/freescale,
+             scripts/infiniteyou,
+             scripts/instantir,
+             scripts/mod,
+             scripts/pixelsmith,
+             scripts/differential_diffusion.py,
+             scripts/pulid,
+             scripts/xadapter,
              repositories,
              extensions-builtin/Lora,
-             extensions-builtin/sd-webui-agent-scheduler,
              extensions-builtin/sd-extension-chainner/nodes,
+             extensions-builtin/sd-webui-agent-scheduler,
              extensions-builtin/sdnext-modernui/node_modules,
 ignore-patterns=.*test*.py$,
                 .*_model.py$,
@@ -158,8 +164,8 @@ disable=abstract-method,
         consider-using-generator,
         consider-using-get,
         consider-using-in,
-        consider-using-min-builtin,
         consider-using-max-builtin,
+        consider-using-min-builtin,
         consider-using-sys-exit,
         cyclic-import,
         dangerous-default-value,
@@ -175,6 +181,7 @@ disable=abstract-method,
         missing-class-docstring,
         missing-function-docstring,
         missing-module-docstring,
+        no-else-raise,
         no-else-return,
         not-callable,
         pointless-string-statement,
@@ -185,16 +192,17 @@ disable=abstract-method,
         too-many-instance-attributes,
         too-many-locals,
         too-many-nested-blocks,
-        too-many-statements,
         too-many-positional-arguments,
+        too-many-statements,
         unidiomatic-typecheck,
+        unknown-option-value,
         unnecessary-dict-index-lookup,
         unnecessary-dunder-call,
-        unnecessary-lambda,
         unnecessary-lambda-assigment,
+        unnecessary-lambda,
+        unused-wildcard-import,
         use-dict-literal,
         use-symbolic-message-instead,
-        unknown-option-value,
         useless-suppression,
         wrong-import-position,
 enable=c-extension-no-member

.ruff.toml

@@ -3,44 +3,33 @@ exclude = [
     ".git",
     ".ruff_cache",
     ".vscode",
-    "modules/apg",
+
-    "modules/consistory",
+    "modules/cfgzero",
+    "modules/flash_attn_triton_amd",
+    "modules/hidiffusion",
+    "modules/intel/ipex",
+    "modules/k-diffusion",
+    "modules/pag",
+    "modules/schedulers",
+    "modules/teacache",
+
     "modules/control/proc",
     "modules/control/units",
-    "modules/freescale",
+    "modules/control/units/xs_pipe.py",
-    "modules/flex2",
-    "modules/ggml",
-    "modules/hidiffusion",
-    "modules/hijack",
-    "modules/instantir",
-    "modules/intel/ipex",
-    "modules/intel/openvino",
-    "modules/k-diffusion",
-    "modules/ldsr",
-    "modules/meissonic",
-    "modules/mod",
-    "modules/omnigen",
-    "modules/omnigen2",
-    "modules/hidream",
-    "modules/pag",
-    "modules/pixelsmith",
     "modules/postprocess/aurasr_arch.py",
-    "modules/prompt_parser_xhinker.py",
+
-    "modules/pulid/eva_clip",
+    "pipelines/meissonic",
-    "modules/ras",
+    "pipelines/omnigen2",
-    "modules/rife",
+    "pipelines/segmoe",
-    "modules/schedulers",
+
-    "modules/segmoe",
+    "scripts/xadapter",
-    "modules/taesd",
+    "scripts/pulid",
-    "modules/teacache",
+    "scripts/instantir",
-    "modules/todo",
+    "scripts/freescale",
-    "modules/unipc",
+    "scripts/consistory",
-    "modules/cfgzero",
+
-    "modules/xadapter",
-    "modules/infiniteyou",
-    "modules/flash_attn_triton_amd",
-    "scripts/softfill.py",
     "repositories",
+
     "extensions-builtin/Lora",
     "extensions-builtin/sd-extension-chainner/nodes",
     "extensions-builtin/sd-webui-agent-scheduler",

CHANGELOG.md

@@ -1,6 +1,6 @@
 # Change Log for SD.Next
 
-## Update for 2025-07-02
+## Update for 2025-07-03
 
 - **Models**
   - Add **FLUX.1-Kontext-Dev** inpaint workflow  
@@ -12,16 +12,20 @@
     enable in *settings -> compute settings -> sdp options*  
     *note*: SD.Next will use either SageAttention v1 or v2, depending which one is installed  
     until authors provide pre-build wheels for v2, you need to install it manually or SD.Next will auto-install v1  
-- **Core**  
-  - override `gradio` installer  
-  - major refactoring of requirements and dependencies to unblock `numpy>=2.1.0`  
-  - patch `insightface`  
-  - patch `k-diffusion`  
-  - better handle startup import errors  
 - **Fixes**
   - allow theme type `None` to be set in config  
   - installer dont cache installed state  
   - fix Cosmos-Predict2 retrying TAESD download  
+  - better handle startup import errors  
+- **Refactoring**  
+  - override `gradio` installer  
+  - major refactoring of requirements and dependencies to unblock `numpy>=2.1.0`  
+  - patch `insightface`  
+  - patch `k-diffusion`  
+  - cleanup `/modules`: move pipeline loaders to `/pipelines` root  
+  - cleanup `/modules`: move code folders used by scripts to `/scripts/<script>` folder  
+  - cleanup `/modules`: global rename `modules.scripts` to avoid conflict with `/scripts`  
+  - stronger lint rules  
 
 ## Update for 2025-06-30
 

TODO.md

@@ -8,9 +8,14 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
 
 - Refactor: Move `model_*` stuff into subfolder  
 - Refactor: sampler options  
-- Common repo for `T5` and `CLiP`  
+- Feature: Common repo for `T5` and `CLiP`  
+- Feature: LoRA add OMI format support for SD35/FLUX.1  
+- Feature: Merge FramePack into core  
+- Remove: legacy LoRA loader
+- Remove: Original backend
+- Remove: Agent Scheduler
 - Video: API support  
-- LoRA: add OMI format support for SD35/FLUX.1  
+- ModernUI: Lite vs Expert mode  
 
 ### Blocked items
 
@@ -66,11 +71,13 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
 
 ## Code TODO
 
-> pnpm lint | grep W0511 | awk -F'TODO ' '{print "- "$NF}' | sed 's/ (fixme)//g'
+> pnpm lint | grep W0511 | awk -F'TODO ' '{print "- "$NF}' | sed 's/ (fixme)//g' | sort
  
 - control: support scripts via api
 - fc: autodetect distilled based on model
 - fc: autodetect tensor format based on model
+- flux transformer from-single-file with quant
+- flux: loader for civitai nf4 models
 - hypertile: vae breaks when using non-standard sizes
 - install: enable ROCm for windows when available
 - loader: load receipe
@@ -78,11 +85,12 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
 - lora: add other quantization types
 - lora: add t5 key support for sd35/f1
 - lora: maybe force imediate quantization
+- lora: support pre-quantized flux
+- model fix: cogview4: balanced offload does not work for GlmModel
+- model load: add ChromaFillPipeline, ChromaControlPipeline, ChromaImg2ImgPipeline etc when available
+- model load: chroma transformer from-single-file with quant
 - model load: force-reloading entire model as loading transformers only leads to massive memory usage
-- model loader: implement model in-memory caching
+- model load: implement model in-memory caching
 - modernui: monkey-patch for missing tabs.select event
-- modules/lora/lora_extract.py:188:9: W0511: TODO: lora: support pre-quantized flux
-- nunchaku: batch support
-- nunchaku: cache-dir for transformer and t5 loader
 - processing: remove duplicate mask params
 - resize image: enable full VAE mode for resize-latent

extensions-builtin/Lora/networks.py

@@ -17,7 +17,7 @@ import network_overrides
 import lora_convert
 import torch
 import diffusers.models.lora
-from modules import shared, devices, sd_models, sd_models_compile, errors, scripts, files_cache, model_quant
+from modules import shared, devices, sd_models, sd_models_compile, errors, scripts_manager, files_cache, model_quant
 
 
 debug = os.environ.get('SD_LORA_DEBUG', None) is not None
@@ -580,7 +580,7 @@ def list_available_networks():
 
 
 def infotext_pasted(infotext, params): # pylint: disable=W0613
-    if "AddNet Module 1" in [x[1] for x in scripts.scripts_txt2img.infotext_fields]:
+    if "AddNet Module 1" in [x[1] for x in scripts_manager.scripts_txt2img.infotext_fields]:
         return  # if the other extension is active, it will handle those fields, no need to do anything
     added = []
     for k in params:

extensions-builtin/sdnext-modernui

@@ -1 +1 @@
-Subproject commit c2c0c27939e20303d63c30ea7a5e179697af8eaf
+Subproject commit c006b67aeabd8bd404de41a446e1a4f6ce4a892f

modules/api/generate.py

@@ -1,6 +1,6 @@
 from threading import Lock
 from fastapi.responses import JSONResponse
-from modules import errors, shared, scripts, ui
+from modules import errors, shared, scripts_manager, ui
 from modules.api import models, script, helpers
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
 
@@ -85,7 +85,7 @@ class APIGenerate():
 
     def post_text2img(self, txt2imgreq: models.ReqTxt2Img):
         self.prepare_face_module(txt2imgreq)
-        script_runner = scripts.scripts_txt2img
+        script_runner = scripts_manager.scripts_txt2img
         if not script_runner.scripts:
             script_runner.initialize_scripts(False)
             ui.create_ui(None)
@@ -113,10 +113,10 @@ class APIGenerate():
             script_args = script.init_script_args(p, txt2imgreq, self.default_script_arg_txt2img, selectable_scripts, selectable_script_idx, script_runner)
             p.script_args = tuple(script_args) # Need to pass args as tuple here
             if selectable_scripts is not None:
-                processed = scripts.scripts_txt2img.run(p, *script_args) # Need to pass args as list here
+                processed = scripts_manager.scripts_txt2img.run(p, *script_args) # Need to pass args as list here
             else:
                 processed = process_images(p)
-            processed = scripts.scripts_txt2img.after(p, processed, *script_args)
+            processed = scripts_manager.scripts_txt2img.after(p, processed, *script_args)
             p.close()
             shared.state.end(api=False)
         if processed is None or processed.images is None or len(processed.images) == 0:
@@ -135,7 +135,7 @@ class APIGenerate():
         mask = img2imgreq.mask
         if mask:
             mask = helpers.decode_base64_to_image(mask)
-        script_runner = scripts.scripts_img2img
+        script_runner = scripts_manager.scripts_img2img
         if not script_runner.scripts:
             script_runner.initialize_scripts(True)
             ui.create_ui(None)
@@ -165,10 +165,10 @@ class APIGenerate():
             script_args = script.init_script_args(p, img2imgreq, self.default_script_arg_img2img, selectable_scripts, selectable_script_idx, script_runner)
             p.script_args = tuple(script_args) # Need to pass args as tuple here
             if selectable_scripts is not None:
-                processed = scripts.scripts_img2img.run(p, *script_args) # Need to pass args as list here
+                processed = scripts_manager.scripts_img2img.run(p, *script_args) # Need to pass args as list here
             else:
                 processed = process_images(p)
-            processed = scripts.scripts_img2img.after(p, processed, *script_args)
+            processed = scripts_manager.scripts_img2img.after(p, processed, *script_args)
             p.close()
             shared.state.end(api=False)
         if processed is None or processed.images is None or len(processed.images) == 0:

modules/api/process.py

@@ -138,7 +138,7 @@ class APIProcess():
         seed = processing_helpers.get_fixed_seed(seed)
         prompt = ''
         if req.type == 'text':
-            from modules.scripts import scripts_txt2img
+            from modules.scripts_manager import scripts_txt2img
             model = 'google/gemma-3-1b-it' if req.model is None or len(req.model) < 4 else req.model
             instance = [s for s in scripts_txt2img.scripts if 'prompt_enhance.py' in s.filename][0]
             prompt = instance.enhance(
@@ -149,7 +149,7 @@ class APIProcess():
                 nsfw=req.nsfw,
             )
         elif req.type == 'image':
-            from modules.scripts import scripts_txt2img
+            from modules.scripts_manager import scripts_txt2img
             model = 'google/gemma-3-4b-it' if req.model is None or len(req.model) < 4 else req.model
             instance = [s for s in scripts_txt2img.scripts if 'prompt_enhance.py' in s.filename][0]
             prompt = instance.enhance(

modules/api/script.py

@@ -2,8 +2,8 @@ from typing import Optional
 from fastapi.exceptions import HTTPException
 import gradio as gr
 from modules.api import models
-from modules import scripts
 from modules.errors import log
+from modules import scripts_manager
 
 
 def script_name_to_index(name, scripts_list):
@@ -30,15 +30,15 @@ def get_selectable_script(script_name, script_runner):
 
 
 def get_scripts_list():
-    t2ilist = [script.name for script in scripts.scripts_txt2img.scripts if script.name is not None]
+    t2ilist = [script.name for script in scripts_manager.scripts_txt2img.scripts if script.name is not None]
-    i2ilist = [script.name for script in scripts.scripts_img2img.scripts if script.name is not None]
+    i2ilist = [script.name for script in scripts_manager.scripts_img2img.scripts if script.name is not None]
-    control = [script.name for script in scripts.scripts_control.scripts if script.name is not None]
+    control = [script.name for script in scripts_manager.scripts_control.scripts if script.name is not None]
     return models.ResScripts(txt2img = t2ilist, img2img = i2ilist, control = control)
 
 
 def get_script_info(script_name: Optional[str] = None):
     res = []
-    for script_list in [scripts.scripts_txt2img.scripts, scripts.scripts_img2img.scripts, scripts.scripts_control.scripts]:
+    for script_list in [scripts_manager.scripts_txt2img.scripts, scripts_manager.scripts_img2img.scripts, scripts_manager.scripts_control.scripts]:
         for script in script_list:
             if script.api_info is not None and (script_name is None or script_name == script.api_info.name):
                 res.append(script.api_info)

modules/control/run.py

@@ -13,7 +13,7 @@ from modules.control.units import xs # VisLearn ControlNet-XS
 from modules.control.units import lite # Kohya ControlLLLite
 from modules.control.units import t2iadapter # TencentARC T2I-Adapter
 from modules.control.units import reference # ControlNet-Reference
-from modules import devices, shared, errors, processing, images, sd_models, scripts, masking
+from modules import devices, shared, errors, processing, images, sd_models, scripts_manager, masking
 from modules.processing_class import StableDiffusionProcessingControl
 from modules.ui_common import infotext_to_html
 from modules.api import script
@@ -737,10 +737,10 @@ def control_run(state: str = '',
                         if sd_models.get_diffusers_task(pipe) != sd_models.DiffusersTaskType.TEXT_2_IMAGE: # force vae back to gpu if not in txt2img mode
                             sd_models.move_model(pipe.vae, devices.device)
 
-                        p.scripts = scripts.scripts_control
+                        p.scripts = scripts_manager.scripts_control
                         p.script_args = input_script_args or []
                         if len(p.script_args) == 0:
-                            script_runner = scripts.scripts_control
+                            script_runner = scripts_manager.scripts_control
                             if not script_runner.scripts:
                                 script_runner.initialize_scripts(False)
                             p.script_args = script.init_default_script_args(script_runner)

modules/extensions.py

@@ -77,7 +77,7 @@ class Extension:
                 self.remote = None
 
     def list_files(self, subdir, extension):
-        from modules import scripts
+        from modules import scripts_manager
         dirpath = os.path.join(self.path, subdir)
         if not os.path.isdir(dirpath):
             return []
@@ -89,7 +89,7 @@ class Extension:
             if os.path.isfile(os.path.join(dirpath, "..", ".priority")):
                 with open(os.path.join(dirpath, "..", ".priority"), "r", encoding="utf-8") as f:
                     priority = str(f.read().strip())
-            res.append(scripts.ScriptFile(self.path, filename, os.path.join(dirpath, filename), priority))
+            res.append(scripts_manager.ScriptFile(self.path, filename, os.path.join(dirpath, filename), priority))
             if priority != '50':
                 shared.log.debug(f'Extension priority override: {os.path.dirname(dirpath)}:{priority}')
         res = [x for x in res if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)]

modules/face/__init__.py

@@ -1,13 +1,13 @@
 import os
 import gradio as gr
 from PIL import Image
-from modules import scripts, processing, shared, images
+from modules import scripts_manager, processing, shared, images
 
 
 debug = shared.log.trace if os.environ.get('SD_FACE_DEBUG', None) is not None else lambda *args, **kwargs: None
 
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
     original_pipeline = None
     original_prompt_attention = None
 

modules/flash_attn_triton_amd/utils.py

@@ -42,7 +42,7 @@ class MetaData():
     rotary_cos: Optional[torch.Tensor] = None
     rotary_interleaved: bool = False
     rotary_conjunction: bool = False
-    
+
 
     def __repr__(self) -> str:
         return (f"MetaData(\n"
@@ -161,7 +161,7 @@ def generate_varlen_tensor(
     if batch_size is None:
         valid_batch_sizes = [bs for bs in [1, 2, 4, 8, 16, 32, 64] if bs <= total_seqlen]
         batch_size = random.choice(valid_batch_sizes)
-    
+
     # get seqlens
     if equal_seqlens:
         seqlens = torch.full(
@@ -241,14 +241,14 @@ def input_helper(
         TOTAL_SEQLENS_Q = BATCH * N_CTX_Q
         TOTAL_SEQLENS_K = BATCH * N_CTX_K
         equal_seqlens=False
-        
+
         # gen tensors
         # TODO: the gen functions should maybe have different gen modes like random, ones, increasing seqlen
         q, cu_seqlens_q, max_seqlen_q = generate_varlen_tensor(TOTAL_SEQLENS_Q, HQ, D_HEAD, batch_size=BATCH, dtype=dtype, device=device, equal_seqlens=equal_seqlens, DEBUG_INPUT=DEBUG_INPUT)
         k, cu_seqlens_k, max_seqlen_k = generate_varlen_tensor(TOTAL_SEQLENS_K, HK, D_HEAD, batch_size=BATCH, dtype=dtype, device=device, equal_seqlens=equal_seqlens, DEBUG_INPUT=DEBUG_INPUT)
         v, _, _ = generate_varlen_tensor(TOTAL_SEQLENS_K, HK, D_HEAD, batch_size=BATCH, dtype=dtype, device=device, equal_seqlens=equal_seqlens, DEBUG_INPUT=DEBUG_INPUT)
         do = torch.ones_like(q) if DEBUG_INPUT else torch.randn_like(q)
-        
+
         # setup metadata
         if DEBUG_INPUT:
             sm_scale = 1
@@ -369,7 +369,7 @@ def get_shape_from_layout(
             raise ValueError("cu_seqlens must be provided for varlen (thd) layout") 
         if max_seqlen is None:
             raise ValueError("max_seqlen must be provided for varlen (thd) layout")
-        
+
         batch, max_seqlen_final, num_heads, head_dim = len(cu_seqlens) - 1, max_seqlen, num_heads, head_dim
     else:
         assert False, "Got unsupported layout."
@@ -380,7 +380,7 @@ def get_shape_from_layout(
 def get_shapes_from_layout(q, k, layout, cu_seqlens_q = None, cu_seqlens_k = None, max_seqlen_q=None, max_seqlen_k=None):
     batch_q, seqlen_q, nheads_q, head_size_q = get_shape_from_layout(q, layout, cu_seqlens_q, max_seqlen_q)
     batch_k, seqlen_k, nheads_k, head_size_k = get_shape_from_layout(k, layout, cu_seqlens_k, max_seqlen_k)
-    
+
     # assert
     assert batch_q == batch_k
     assert head_size_q == head_size_k
@@ -458,22 +458,22 @@ def write_dropout_mask(x, tensor_name = "tensor"):
                 if True:
                     BLOCK_M = 64
                     BLOCK_N = 64
-                
+
                     # Calculate number of blocks in each dimension
                     m_blocks = math.ceil(seqlen_m / BLOCK_M)
                     n_blocks = math.ceil(seqlen_n / BLOCK_N)
-                    
+
                     # Process each block
                     for m_block in range(m_blocks):
                         # Calculate row range for current block
                         row_start = m_block * BLOCK_M
                         row_end = min(row_start + BLOCK_M, seqlen_m)
-                        
+
                         for n_block in range(n_blocks):
                             # Calculate column range for current block
                             col_start = n_block * BLOCK_N
                             col_end = min(col_start + BLOCK_N, seqlen_n)
-                            
+
                             # Extract and write the current block
                             for row_idx in range(row_start, row_end):
                                 row_data = dropout_mask[row_idx][col_start:col_end]

modules/gr_hijack.py

@@ -1,7 +1,7 @@
 from PIL import Image
 import gradio as gr
 import gradio.processing_utils
-from modules import scripts, patches, gr_tempdir
+from modules import scripts_manager, patches, gr_tempdir
 
 
 hijacked = False
@@ -44,14 +44,14 @@ def add_classes_to_gradio_component(comp):
 
 def IOComponent_init(self, *args, **kwargs):
     self.webui_tooltip = kwargs.pop('tooltip', None)
-    if scripts.scripts_current is not None:
+    if scripts_manager.scripts_current is not None:
-        scripts.scripts_current.before_component(self, **kwargs)
+        scripts_manager.scripts_current.before_component(self, **kwargs)
-    scripts.script_callbacks.before_component_callback(self, **kwargs)
+    scripts_manager.script_callbacks.before_component_callback(self, **kwargs)
     res = original_IOComponent_init(self, *args, **kwargs) # pylint: disable=assignment-from-no-return
     add_classes_to_gradio_component(self)
-    scripts.script_callbacks.after_component_callback(self, **kwargs)
+    scripts_manager.script_callbacks.after_component_callback(self, **kwargs)
-    if scripts.scripts_current is not None:
+    if scripts_manager.scripts_current is not None:
-        scripts.scripts_current.after_component(self, **kwargs)
+        scripts_manager.scripts_current.after_component(self, **kwargs)
     return res
 
 
@@ -65,14 +65,14 @@ def Block_get_config(self):
 
 
 def BlockContext_init(self, *args, **kwargs):
-    if scripts.scripts_current is not None:
+    if scripts_manager.scripts_current is not None:
-        scripts.scripts_current.before_component(self, **kwargs)
+        scripts_manager.scripts_current.before_component(self, **kwargs)
-    scripts.script_callbacks.before_component_callback(self, **kwargs)
+    scripts_manager.script_callbacks.before_component_callback(self, **kwargs)
     res = original_BlockContext_init(self, *args, **kwargs) # pylint: disable=assignment-from-no-return
     add_classes_to_gradio_component(self)
-    scripts.script_callbacks.after_component_callback(self, **kwargs)
+    scripts_manager.script_callbacks.after_component_callback(self, **kwargs)
-    if scripts.scripts_current is not None:
+    if scripts_manager.scripts_current is not None:
-        scripts.scripts_current.after_component(self, **kwargs)
+        scripts_manager.scripts_current.after_component(self, **kwargs)
     return res
 
 

modules/hidiffusion/utils.py

@@ -5,14 +5,14 @@ def isinstance_str(x: object, cls_name: str):
     """
     Checks whether x has any class *named* cls_name in its ancestry.
     Doesn't require access to the class's implementation.
-    
+
     Useful for patching!
     """
 
     for _cls in x.__class__.__mro__:
         if _cls.__name__ == cls_name:
             return True
-    
+
     return False
 
 
@@ -29,4 +29,3 @@ def init_generator(device: torch.device, fallback: torch.Generator=None):
             return init_generator(torch.device("cpu"))
         else:
             return fallback
-    

modules/img2img.py

@@ -3,8 +3,7 @@ import itertools # SBM Batch frames
 import numpy as np
 import filetype
 from PIL import Image, ImageOps, ImageFilter, ImageEnhance, ImageChops, UnidentifiedImageError
-import modules.scripts
+from modules import scripts_manager, shared, processing, images
-from modules import shared, processing, images
 from modules.generation_parameters_copypaste import create_override_settings_dict
 from modules.ui_common import plaintext_to_html
 from modules.memstats import memory_stats
@@ -100,7 +99,7 @@ def process_batch(p, input_files, input_dir, output_dir, inpaint_mask_dir, args)
 
         batch_image_files = batch_image_files * btcrept # List used for naming later.
 
-        processed = modules.scripts.scripts_img2img.run(p, *args)
+        processed = scripts_manager.scripts_img2img.run(p, *args)
         if processed is None:
             processed = processing.process_images(p)
 
@@ -124,7 +123,7 @@ def process_batch(p, input_files, input_dir, output_dir, inpaint_mask_dir, args)
             for k, v in items.items():
                 image.info[k] = v
             images.save_image(image, path=output_dir, basename=basename, seed=None, prompt=None, extension=ext, info=geninfo, short_filename=True, no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=image.info, forced_filename=forced_filename)
-        processed = modules.scripts.scripts_img2img.after(p, processed, *args)
+        processed = scripts_manager.scripts_img2img.after(p, processed, *args)
         shared.log.debug(f'Processed: images={len(batch_image_files)} memory={memory_stats()} batch')
 
 
@@ -289,7 +288,7 @@ def img2img(id_task: str, state: str, mode: int,
         # override
         override_settings=override_settings,
     )
-    p.scripts = modules.scripts.scripts_img2img
+    p.scripts = scripts_manager.scripts_img2img
     p.script_args = args
     p.state = state
     if mask:
@@ -304,10 +303,10 @@ def img2img(id_task: str, state: str, mode: int,
         process_batch(p, img2img_batch_files, img2img_batch_input_dir, img2img_batch_output_dir, img2img_batch_inpaint_mask_dir, args)
         processed = processing.Processed(p, [], p.seed, "")
     else:
-        processed = modules.scripts.scripts_img2img.run(p, *args)
+        processed = scripts_manager.scripts_img2img.run(p, *args)
         if processed is None:
             processed = processing.process_images(p)
-        processed = modules.scripts.scripts_img2img.after(p, processed, *args)
+        processed = scripts_manager.scripts_img2img.after(p, processed, *args)
     p.close()
     generation_info_js = processed.js() if processed is not None else ''
     if processed is None:

modules/ldsr/sd_hijack_autoencoder.py

@@ -137,7 +137,7 @@ class VQModel(pl.LightningModule):
                 # do the first few batches with max size to avoid later oom
                 new_resize = upper_size
             else:
-                new_resize = np.random.choice(np.arange(lower_size, upper_size+16, 16)) # noqa: NPY002
+                new_resize = np.random.choice(np.arange(lower_size, upper_size+16, 16))
             if new_resize != x.shape[2]:
                 x = F.interpolate(x, size=new_resize, mode="bicubic")
             x = x.detach()

modules/model_quant.py

@@ -347,7 +347,7 @@ def sdnq_quantize_model(model, op=None, sd_model=None, do_gc: bool = True, weigh
         return_device = None
 
     if getattr(model, "_keep_in_fp32_modules", None) is not None:
-        modules_to_not_convert.extend(model._keep_in_fp32_modules)
+        modules_to_not_convert.extend(model._keep_in_fp32_modules) # pylint: disable=protected-access
     if model.__class__.__name__ == "ChromaTransformer2DModel":
         modules_to_not_convert.append("distilled_guidance_layer")
 

modules/model_te.py

@@ -70,13 +70,13 @@ def load_t5(name=None, cache_dir=None):
 
     elif 'int8' in name.lower():
         from modules.model_quant import create_sdnq_config
-        quantization_config = create_sdnq_config(kwargs=None, allow_sdnq=True, module='any', weights_dtype='int8')
+        quantization_config = create_sdnq_config(kwargs=None, allow=True, module='any', weights_dtype='int8')
         if quantization_config is not None:
             t5 = transformers.T5EncoderModel.from_pretrained(repo_id, subfolder='text_encoder_3', quantization_config=quantization_config, cache_dir=cache_dir, torch_dtype=devices.dtype)
 
     elif 'uint4' in name.lower():
         from modules.model_quant import create_sdnq_config
-        quantization_config = create_sdnq_config(kwargs=None, allow_sdnq=True, module='any', weights_dtype='uint4')
+        quantization_config = create_sdnq_config(kwargs=None, allow=True, module='any', weights_dtype='uint4')
         if quantization_config is not None:
             t5 = transformers.T5EncoderModel.from_pretrained(repo_id, subfolder='text_encoder_3', quantization_config=quantization_config, cache_dir=cache_dir, torch_dtype=devices.dtype)
 

modules/postprocessing.py

@@ -4,7 +4,7 @@ from typing import List
 
 from PIL import Image
 
-from modules import shared, images, devices, scripts, scripts_postprocessing, infotext
+from modules import shared, images, devices, scripts_manager, scripts_postprocessing, infotext
 from modules.shared import opts
 
 
@@ -70,7 +70,7 @@ def run_postprocessing(extras_mode, image, image_folder: List[tempfile.NamedTemp
             continue
         shared.state.textinfo = name
         pp = scripts_postprocessing.PostprocessedImage(image.convert("RGB"))
-        scripts.scripts_postproc.run(pp, args)
+        scripts_manager.scripts_postproc.run(pp, args)
         geninfo, items = images.read_info_from_image(image)
         params = infotext.parse(geninfo)
         for k, v in items.items():
@@ -89,7 +89,7 @@ def run_postprocessing(extras_mode, image, image_folder: List[tempfile.NamedTemp
         if extras_mode != 2 or show_extras_results:
             outputs.append(pp.image)
         image.close()
-    scripts.scripts_postproc.postprocess(processed_images, args)
+    scripts_manager.scripts_postproc.postprocess(processed_images, args)
 
     devices.torch_gc()
     return outputs, info, params
@@ -98,7 +98,7 @@ def run_postprocessing(extras_mode, image, image_folder: List[tempfile.NamedTemp
 def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_first: bool, save_output: bool = True): #pylint: disable=unused-argument
     """old handler for API"""
 
-    args = scripts.scripts_postproc.create_args_for_run({
+    args = scripts_manager.scripts_postproc.create_args_for_run({
         "Upscale": {
             "upscale_mode": resize_mode,
             "upscale_by": upscaling_resize,

modules/processing.py

@@ -4,7 +4,7 @@ import time
 from contextlib import nullcontext
 import numpy as np
 from PIL import Image, ImageOps
-from modules import shared, devices, errors, images, scripts, memstats, lowvram, script_callbacks, extra_networks, detailer, sd_models, sd_checkpoint, sd_vae, processing_helpers, timer, face_restoration, token_merge
+from modules import shared, devices, errors, images, scripts_manager, memstats, lowvram, script_callbacks, extra_networks, detailer, sd_models, sd_checkpoint, sd_vae, processing_helpers, timer, face_restoration, token_merge
 from modules.sd_hijack_hypertile import context_hypertile_vae, context_hypertile_unet
 from modules.processing_class import StableDiffusionProcessing, StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, StableDiffusionProcessingControl, StableDiffusionProcessingVideo # pylint: disable=unused-import
 from modules.processing_info import create_infotext
@@ -128,7 +128,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
     debug(f'Process images: {vars(p)}')
     if not hasattr(p.sd_model, 'sd_checkpoint_info'):
         return None
-    if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner):
+    if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
         p.scripts.before_process(p)
     stored_opts = {}
     for k, v in p.override_settings.copy().items():
@@ -290,7 +290,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     process_init(p)
     if not shared.native and os.path.exists(shared.opts.embeddings_dir) and not p.do_not_reload_embeddings:
         modules.sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=False)
-    if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner):
+    if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
         p.scripts.process(p)
 
     ema_scope_context = p.sd_model.ema_scope if not shared.native else nullcontext
@@ -324,19 +324,19 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                 p.negative_prompts = p.all_negative_prompts[n * p.batch_size:(n+1) * p.batch_size]
             p.seeds = p.all_seeds[n * p.batch_size:(n+1) * p.batch_size]
             p.subseeds = p.all_subseeds[n * p.batch_size:(n+1) * p.batch_size]
-            if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner):
+            if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
                 p.scripts.before_process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
             if len(p.prompts) == 0:
                 break
             p.prompts, p.network_data = extra_networks.parse_prompts(p.prompts)
             if not shared.native:
                 extra_networks.activate(p, p.network_data)
-            if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner):
+            if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
                 p.scripts.process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
 
             samples = None
             timer.process.record('init')
-            if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner):
+            if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
                 processed = p.scripts.process_images(p)
                 if processed is not None:
                     samples = processed.images
@@ -358,12 +358,12 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if not shared.native and (shared.cmd_opts.lowvram or shared.cmd_opts.medvram):
                 lowvram.send_everything_to_cpu()
                 devices.torch_gc()
-            if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner):
+            if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
                 p.scripts.postprocess_batch(p, samples, batch_number=n)
-            if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner):
+            if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
                 p.prompts = p.all_prompts[n * p.batch_size:(n+1) * p.batch_size]
                 p.negative_prompts = p.all_negative_prompts[n * p.batch_size:(n+1) * p.batch_size]
-                batch_params = scripts.PostprocessBatchListArgs(list(samples))
+                batch_params = scripts_manager.PostprocessBatchListArgs(list(samples))
                 p.scripts.postprocess_batch_list(p, batch_params, batch_number=n)
                 samples = batch_params.images
 
@@ -402,8 +402,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                         info = create_infotext(p, p.prompts, p.seeds, p.subseeds, index=i)
                         images.save_image(image_without_cc, path=p.outpath_samples, basename="", seed=p.seeds[i], prompt=p.prompts[i], extension=shared.opts.samples_format, info=info, p=p, suffix="-before-color-correct")
                     image = apply_color_correction(p.color_corrections[i], image)
-                if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner):
+                if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
-                    pp = scripts.PostprocessImageArgs(image)
+                    pp = scripts_manager.PostprocessImageArgs(image)
                     p.scripts.postprocess_image(p, pp)
                     if pp.image is not None:
                         image = pp.image
@@ -496,7 +496,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         index_of_first_image=index_of_first_image,
         infotexts=infotexts,
     )
-    if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner) and not (shared.state.interrupted or shared.state.skipped):
+    if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner) and not (shared.state.interrupted or shared.state.skipped):
         p.scripts.postprocess(p, processed)
     timer.process.record('post')
     if not p.disable_extra_networks:

modules/processing_class.py

@@ -8,7 +8,7 @@ import torch
 import numpy as np
 import cv2
 from PIL import Image, ImageOps
-from modules import shared, devices, images, scripts, masking, sd_samplers, sd_models, processing_helpers
+from modules import shared, devices, images, scripts_manager, masking, sd_samplers, sd_models, processing_helpers
 from modules.sd_hijack_hypertile import hypertile_set
 
 
@@ -278,7 +278,7 @@ class StableDiffusionProcessing:
         self.prompt_for_display: str = None
 
         # scripts
-        self.scripts_value: scripts.ScriptRunner = field(default=None, init=False)
+        self.scripts_value: scripts_manager.ScriptRunner = field(default=None, init=False)
         self.script_args_value: list = field(default=None, init=False)
         self.scripts_setup_complete: bool = field(default=False, init=False)
         self.script_args = script_args

modules/prompt_parser_xhinker.py

@@ -731,7 +731,7 @@ def get_weighted_text_embeddings_sdxl_refiner(
 
         for z in range(len(neg_weight_tensor_2)):
             if neg_weight_tensor_2[z] != 1.0:
-                ow = neg_weight_tensor_2[z] - 1
+                # ow = neg_weight_tensor_2[z] - 1
                 # neg_weight = 1 + (math.exp(ow)/(math.exp(ow) + 1) - 0.5) * 2
 
                 # add weight method 1:
@@ -1330,7 +1330,6 @@ def get_weighted_text_embeddings_sd3(
     sd3_neg_prompt_embeds = torch.cat([clip_neg_prompt_embeds, t5_neg_prompt_embeds], dim=-2)
 
     # padding
-    import torch.nn.functional as F
     size_diff = sd3_neg_prompt_embeds.size(1) - sd3_prompt_embeds.size(1)
     # Calculate padding. Format for pad is (padding_left, padding_right, padding_top, padding_bottom, padding_front, padding_back)
     # Since we are padding along the second dimension (axis=1), we need (0, 0, padding_top, padding_bottom, 0, 0)

modules/scripts.py

@@ -1,730 +1,2 @@
-import os
+# compatibility with extensions that import scripts directly
-import re
+from modules.scripts_manager import * # noqa: F403
-import sys
-import time
-from collections import namedtuple
-from dataclasses import dataclass
-import gradio as gr
-from modules import paths, script_callbacks, extensions, script_loading, scripts_postprocessing, errors, timer
-from installer import control_extensions
-
-
-AlwaysVisible = object()
-time_component = {}
-time_setup = {}
-debug = errors.log.trace if os.environ.get('SD_SCRIPT_DEBUG', None) is not None else lambda *args, **kwargs: None
-
-
-class PostprocessImageArgs:
-    def __init__(self, image):
-        self.image = image
-
-
-class PostprocessBatchListArgs:
-    def __init__(self, images):
-        self.images = images
-
-
-@dataclass
-class OnComponent:
-    component: gr.blocks.Block
-
-
-class Script:
-    parent = None
-    name = None
-    filename = None
-    args_from = 0
-    args_to = 0
-    alwayson = False
-    is_txt2img = False
-    is_img2img = False
-    api_info = None
-    group = None
-    infotext_fields = None
-    paste_field_names = None
-    section = None
-    standalone = False
-    on_before_component_elem_id = [] # list of callbacks to be called before a component with an elem_id is created
-    on_after_component_elem_id = [] # list of callbacks to be called after a component with an elem_id is created
-
-    def title(self):
-        """this function should return the title of the script. This is what will be displayed in the dropdown menu."""
-        raise NotImplementedError
-
-    def ui(self, is_img2img):
-        """this function should create gradio UI elements. See https://gradio.app/docs/#components
-        The return value should be an array of all components that are used in processing.
-        Values of those returned components will be passed to run() and process() functions.
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def show(self, is_img2img): # pylint: disable=unused-argument
-        """
-        is_img2img is True if this function is called for the img2img interface, and False otherwise
-        This function should return:
-         - False if the script should not be shown in UI at all
-         - True if the script should be shown in UI if it's selected in the scripts dropdown
-         - script.AlwaysVisible if the script should be shown in UI at all times
-         """
-        return True
-
-    def run(self, p, *args):
-        """
-        This function is called if the script has been selected in the script dropdown.
-        It must do all processing and return the Processed object with results, same as
-        one returned by processing.process_images.
-        Usually the processing is done by calling the processing.process_images function.
-        args contains all values returned by components from ui()
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def setup(self, p, *args):
-        """For AlwaysVisible scripts, this function is called when the processing object is set up, before any processing starts.
-        args contains all values returned by components from ui().
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def before_process(self, p, *args):
-        """
-        This function is called very early during processing begins for AlwaysVisible scripts.
-        You can modify the processing object (p) here, inject hooks, etc.
-        args contains all values returned by components from ui()
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def process(self, p, *args):
-        """
-        This function is called before processing begins for AlwaysVisible scripts.
-        You can modify the processing object (p) here, inject hooks, etc.
-        args contains all values returned by components from ui()
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def process_images(self, p, *args):
-        """
-        This function is called instead of main processing for AlwaysVisible scripts.
-        You can modify the processing object (p) here, inject hooks, etc.
-        args contains all values returned by components from ui()
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def before_process_batch(self, p, *args, **kwargs):
-        """
-        Called before extra networks are parsed from the prompt, so you can add
-        new extra network keywords to the prompt with this callback.
-        **kwargs will have those items:
-          - batch_number - index of current batch, from 0 to number of batches-1
-          - prompts - list of prompts for current batch; you can change contents of this list but changing the number of entries will likely break things
-          - seeds - list of seeds for current batch
-          - subseeds - list of subseeds for current batch
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def process_batch(self, p, *args, **kwargs):
-        """
-        Same as process(), but called for every batch.
-        **kwargs will have those items:
-          - batch_number - index of current batch, from 0 to number of batches-1
-          - prompts - list of prompts for current batch; you can change contents of this list but changing the number of entries will likely break things
-          - seeds - list of seeds for current batch
-          - subseeds - list of subseeds for current batch
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def postprocess_batch(self, p, *args, **kwargs):
-        """
-        Same as process_batch(), but called for every batch after it has been generated.
-        **kwargs will have same items as process_batch, and also:
-          - batch_number - index of current batch, from 0 to number of batches-1
-          - images - torch tensor with all generated images, with values ranging from 0 to 1;
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def postprocess_image(self, p, pp: PostprocessImageArgs, *args):
-        """
-        Called for every image after it has been generated.
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, *args, **kwargs):
-        """
-        Same as postprocess_batch(), but receives batch images as a list of 3D tensors instead of a 4D tensor.
-        This is useful when you want to update the entire batch instead of individual images.
-        You can modify the postprocessing object (pp) to update the images in the batch, remove images, add images, etc.
-        If the number of images is different from the batch size when returning,
-        then the script has the responsibility to also update the following attributes in the processing object (p):
-          - p.prompts
-          - p.negative_prompts
-          - p.seeds
-          - p.subseeds
-        **kwargs will have same items as process_batch, and also:
-          - batch_number - index of current batch, from 0 to number of batches-1
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def postprocess(self, p, processed, *args):
-        """
-        This function is called after processing ends for AlwaysVisible scripts.
-        args contains all values returned by components from ui()
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def before_component(self, component, **kwargs):
-        """
-        Called before a component is created.
-        Use elem_id/label fields of kwargs to figure out which component it is.
-        This can be useful to inject your own components somewhere in the middle of vanilla UI.
-        You can return created components in the ui() function to add them to the list of arguments for your processing functions
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def after_component(self, component, **kwargs):
-        """
-        Called after a component is created. Same as above.
-        """
-        pass # pylint: disable=unnecessary-pass
-
-    def describe(self):
-        """unused"""
-        return ""
-
-    def elem_id(self, item_id):
-        """helper function to generate id for a HTML element, constructs final id out of script name, tab and user-supplied item_id"""
-        title = re.sub(r'[^a-z_0-9]', '', re.sub(r'\s', '_', self.title().lower()))
-        return f'script_{self.parent}_{title}_{item_id}'
-
-
-current_basedir = paths.script_path
-
-
-def basedir():
-    """returns the base directory for the current script. For scripts in the main scripts directory,
-    this is the main directory (where webui.py resides), and for scripts in extensions directory
-    (ie extensions/aesthetic/script/aesthetic.py), this is extension's directory (extensions/aesthetic)
-    """
-    return current_basedir
-
-
-ScriptFile = namedtuple("ScriptFile", ["basedir", "filename", "path", "priority"])
-scripts_data = []
-postprocessing_scripts_data = []
-ScriptClassData = namedtuple("ScriptClassData", ["script_class", "path", "basedir", "module"])
-
-
-def list_scripts(scriptdirname, extension):
-    tmp_list = []
-    base = os.path.join(paths.script_path, scriptdirname)
-    if os.path.exists(base):
-        for filename in sorted(os.listdir(base)):
-            tmp_list.append(ScriptFile(paths.script_path, filename, os.path.join(base, filename), '50'))
-    for ext in extensions.active():
-        tmp_list += ext.list_files(scriptdirname, extension)
-    priority_list = []
-    for script in tmp_list:
-        if os.path.splitext(script.path)[1].lower() == extension and os.path.isfile(script.path):
-            if script.basedir == paths.script_path:
-                priority = '0'
-            elif script.basedir.startswith(os.path.join(paths.script_path, 'scripts')):
-                priority = '1'
-            elif script.basedir.startswith(os.path.join(paths.script_path, 'extensions-builtin')):
-                priority = '2'
-            elif script.basedir.startswith(os.path.join(paths.script_path, 'extensions')):
-                priority = '3'
-            else:
-                priority = '9'
-            if os.path.isfile(os.path.join(base, "..", ".priority")):
-                with open(os.path.join(base, "..", ".priority"), "r", encoding="utf-8") as f:
-                    priority = priority + str(f.read().strip())
-                    errors.log.debug(f'Script priority override: ${script.name}:{priority}')
-            else:
-                priority = priority + script.priority
-            priority_list.append(ScriptFile(script.basedir, script.filename, script.path, priority))
-            debug(f'Adding script: folder="{script.basedir}" file="{script.filename}" full="{script.path}" priority={priority}')
-    priority_sort = sorted(priority_list, key=lambda item: item.priority + item.path.lower(), reverse=False)
-    return priority_sort
-
-
-def list_files_with_name(filename):
-    res = []
-    dirs = [paths.script_path] + [ext.path for ext in extensions.active()]
-    for dirpath in dirs:
-        if not os.path.isdir(dirpath):
-            continue
-        path = os.path.join(dirpath, filename)
-        if os.path.isfile(path):
-            res.append(path)
-    return res
-
-
-def load_scripts():
-    t = timer.Timer()
-    t0 = time.time()
-    global current_basedir # pylint: disable=global-statement
-    scripts_data.clear()
-    postprocessing_scripts_data.clear()
-    script_callbacks.clear_callbacks()
-    scripts_list = list_scripts('scripts', '.py') + list_scripts(os.path.join('modules', 'face'), '.py')
-    scripts_list = sorted(scripts_list, key=lambda item: item.priority + item.path.lower(), reverse=False)
-    syspath = sys.path
-
-    def register_scripts_from_module(module, scriptfile):
-        for script_class in module.__dict__.values():
-            if type(script_class) != type:
-                continue
-            debug(f'Registering script: path="{scriptfile.path}"')
-            if issubclass(script_class, Script):
-                scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir, module))
-            elif issubclass(script_class, scripts_postprocessing.ScriptPostprocessing):
-                postprocessing_scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir, module))
-
-    for scriptfile in scripts_list:
-        try:
-            if scriptfile.basedir != paths.script_path:
-                sys.path = [scriptfile.basedir] + sys.path
-            current_basedir = scriptfile.basedir
-            script_module = script_loading.load_module(scriptfile.path)
-            register_scripts_from_module(script_module, scriptfile)
-        except Exception as e:
-            errors.display(e, f'Load script: {scriptfile.filename}')
-        finally:
-            current_basedir = paths.script_path
-            t.record(os.path.basename(scriptfile.basedir) if scriptfile.basedir != paths.script_path else scriptfile.filename)
-            sys.path = syspath
-
-    global scripts_txt2img, scripts_img2img, scripts_control, scripts_postproc # pylint: disable=global-statement
-    scripts_txt2img = ScriptRunner('txt2img')
-    scripts_img2img = ScriptRunner('img2img')
-    scripts_control = ScriptRunner('control')
-    scripts_postproc = scripts_postprocessing.ScriptPostprocessingRunner()
-    return t, time.time()-t0
-
-
-def wrap_call(func, filename, funcname, *args, default=None, **kwargs):
-    try:
-        res = func(*args, **kwargs)
-        return res
-    except Exception as e:
-        errors.display(e, f'Calling script: {filename}/{funcname}')
-    return default
-
-
-class ScriptSummary:
-    def __init__(self, op):
-        self.start = time.time()
-        self.update = time.time()
-        self.op = op
-        self.time = {}
-
-    def record(self, script):
-        self.update = time.time()
-        self.time[script] = round(time.time() - self.update, 2)
-
-    def report(self):
-        total = sum(self.time.values())
-        if total == 0:
-            return
-        scripts = [f'{k}:{v}' for k, v in self.time.items() if v > 0]
-        errors.log.debug(f'Script: op={self.op} total={total} scripts={scripts}')
-
-
-class ScriptRunner:
-    def __init__(self, name=''):
-        self.name = name
-        self.scripts = []
-        self.selectable_scripts = []
-        self.alwayson_scripts = []
-        self.auto_processing_scripts = []
-        self.titles = []
-        self.infotext_fields = []
-        self.paste_field_names = []
-        self.script_load_ctr = 0
-        self.is_img2img = False
-        self.inputs = [None]
-        self.time = 0
-
-    def add_script(self, script_class, path, is_img2img, is_control):
-        try:
-            script = script_class()
-            script.filename = path
-            script.is_txt2img = not is_img2img
-            script.is_img2img = is_img2img
-            if is_control: # this is messy but show is a legacy function that is not aware of control tab
-                v1 = script.show(script.is_txt2img)
-                v2 = script.show(script.is_img2img)
-                if v1 == AlwaysVisible or v2 == AlwaysVisible:
-                    visibility = AlwaysVisible
-                else:
-                    visibility = v1 or v2
-            else:
-                visibility = script.show(script.is_img2img)
-            if visibility == AlwaysVisible:
-                self.scripts.append(script)
-                self.alwayson_scripts.append(script)
-                script.alwayson = True
-            elif visibility:
-                self.scripts.append(script)
-                self.selectable_scripts.append(script)
-        except Exception as e:
-            errors.log.error(f'Script initialize: {path} {e}')
-
-    def initialize_scripts(self, is_img2img=False, is_control=False):
-        from modules import scripts_auto_postprocessing
-
-        self.scripts.clear()
-        self.selectable_scripts.clear()
-        self.alwayson_scripts.clear()
-        self.titles.clear()
-        self.infotext_fields.clear()
-        self.paste_field_names.clear()
-        self.script_load_ctr = 0
-        self.is_img2img = is_img2img
-        self.scripts.clear()
-        self.alwayson_scripts.clear()
-        self.selectable_scripts.clear()
-        self.auto_processing_scripts = scripts_auto_postprocessing.create_auto_preprocessing_script_data()
-
-        sorted_scripts = sorted(scripts_data, key=lambda x: x.script_class().title().lower())
-        for script_class, path, _basedir, _script_module in sorted_scripts:
-            self.add_script(script_class, path, is_img2img, is_control)
-        sorted_scripts = sorted(self.auto_processing_scripts, key=lambda x: x.script_class().title().lower())
-        for script_class, path, _basedir, _script_module in sorted_scripts:
-            self.add_script(script_class, path, is_img2img, is_control)
-
-    def prepare_ui(self):
-        self.inputs = [None]
-
-    def setup_ui(self, parent='unknown', accordion=True):
-        import modules.api.models as api_models
-        self.titles = [wrap_call(script.title, script.filename, "title") or f"{script.filename} [error]" for script in self.selectable_scripts]
-
-        inputs = []
-        inputs_alwayson = [True]
-
-        def create_script_ui(script: Script, inputs, inputs_alwayson):
-            script.parent = parent
-            script.args_from = len(inputs)
-            script.args_to = len(inputs)
-            controls = wrap_call(script.ui, script.filename, "ui", script.is_img2img)
-            if controls is None:
-                return
-            script.name = wrap_call(script.title, script.filename, "title", default=script.filename).lower()
-            api_args = []
-            for control in controls:
-                debug(f'Script control: parent={script.parent} script="{script.name}" label="{control.label}" type={control} id={control.elem_id}')
-                if hasattr(gr.components, 'IOComponent'):
-                    if not isinstance(control, gr.components.IOComponent):
-                        errors.log.error(f'Invalid script control: "{script.filename}" control={control}')
-                        continue
-                else:
-                    if not isinstance(control, gr.components.Component):
-                        errors.log.error(f'Invalid script control: "{script.filename}" control={control}')
-                        continue
-                control.custom_script_source = os.path.basename(script.filename)
-                arg_info = api_models.ScriptArg(label=control.label or "")
-                for field in ("value", "minimum", "maximum", "step", "choices"):
-                    v = getattr(control, field, None)
-                    if v is not None:
-                        setattr(arg_info, field, v)
-                api_args.append(arg_info)
-
-            script.api_info = api_models.ItemScript(
-                name=script.name,
-                is_img2img=script.is_img2img,
-                is_alwayson=script.alwayson,
-                args=api_args,
-            )
-            if script.infotext_fields is not None:
-                self.infotext_fields += script.infotext_fields
-            if script.paste_field_names is not None:
-                self.paste_field_names += script.paste_field_names
-            inputs += controls
-            inputs_alwayson += [script.alwayson for _ in controls]
-            script.args_to = len(inputs)
-
-        with gr.Row():
-            dropdown = gr.Dropdown(label="Script", elem_id=f'{parent}_script_list', choices=["None"] + self.titles, value="None", type="index")
-            inputs.insert(0, dropdown)
-
-        with gr.Row():
-            for script in self.alwayson_scripts:
-                if not script.standalone:
-                    continue
-                if (self.name == 'control') and (script.name not in control_extensions) and (script.title() not in control_extensions):
-                    errors.log.debug(f'Script: fn="{script.filename}" type={self.name} skip')
-                    continue
-                t0 = time.time()
-                with gr.Group(elem_id=f'{parent}_script_{script.title().lower().replace(" ", "_")}', elem_classes=['group-extension']) as group:
-                    create_script_ui(script, inputs, inputs_alwayson)
-                script.group = group
-                time_setup[script.title()] = time_setup.get(script.title(), 0) + (time.time()-t0)
-
-        with gr.Row():
-            with gr.Accordion(label="Extensions", elem_id=f'{parent}_script_alwayson') if accordion else gr.Group():
-                for script in self.alwayson_scripts:
-                    if script.standalone:
-                        continue
-                    if (self.name == 'control') and (paths.extensions_dir in script.filename) and (script.title() not in control_extensions):
-                        errors.log.debug(f'Script: fn="{script.filename}" type={self.name} skip')
-                        continue
-                    t0 = time.time()
-                    with gr.Group(elem_id=f'{parent}_script_{script.title().lower().replace(" ", "_")}', elem_classes=['group-extension']) as group:
-                        create_script_ui(script, inputs, inputs_alwayson)
-                    script.group = group
-                    time_setup[script.title()] = time_setup.get(script.title(), 0) + (time.time()-t0)
-
-        for script in self.selectable_scripts:
-            if (self.name == 'control') and (paths.extensions_dir in script.filename) and (script.title() not in control_extensions):
-                errors.log.debug(f'Script: fn="{script.filename}" type={self.name} skip')
-                continue
-            with gr.Group(elem_id=f'{parent}_script_{script.title().lower().replace(" ", "_")}', elem_classes=['group-scripts'], visible=False) as group:
-                t0 = time.time()
-                create_script_ui(script, inputs, inputs_alwayson)
-                time_setup[script.title()] = time_setup.get(script.title(), 0) + (time.time()-t0)
-                script.group = group
-
-        def select_script(script_index):
-            if script_index is None:
-                return [gr.update(visible=False) for script in self.selectable_scripts]
-            selected_script = self.selectable_scripts[script_index - 1] if script_index > 0 else None
-            return [gr.update(visible=selected_script == s) for s in self.selectable_scripts]
-
-        def init_field(title):
-            if title == 'None': # called when an initial value is set from ui-config.json to show script's UI components
-                return
-            if title not in self.titles:
-                errors.log.error(f'Script not found: {title}')
-                return
-            script_index = self.titles.index(title)
-            self.selectable_scripts[script_index].group.visible = True
-
-        dropdown.init_field = init_field
-        dropdown.change(fn=select_script, inputs=[dropdown], outputs=[script.group for script in self.selectable_scripts if script.group is not None])
-
-        def onload_script_visibility(params):
-            title = params.get('Script', None)
-            if title:
-                title_index = self.titles.index(title)
-                visibility = title_index == self.script_load_ctr
-                self.script_load_ctr = (self.script_load_ctr + 1) % len(self.titles)
-                return gr.update(visible=visibility)
-            else:
-                return gr.update(visible=False)
-
-        self.infotext_fields.append((dropdown, lambda x: gr.update(value=x.get('Script', 'None'))))
-        self.infotext_fields.extend([(script.group, onload_script_visibility) for script in self.selectable_scripts if script.group is not None])
-        return inputs
-
-    def run(self, p, *args):
-        s = ScriptSummary('run')
-        script_index = args[0] if len(args) > 0 else 0
-        if script_index == 0:
-            return None
-        script = self.selectable_scripts[script_index-1]
-        if script is None:
-            return None
-        if 'upscale' in script.title():
-            if not hasattr(p, 'init_images') and p.task_args.get('image', None) is not None:
-                p.init_images = p.task_args['image']
-        parsed = []
-        if hasattr(script, 'args_to') and hasattr(script, 'args_from'):
-            parsed = p.per_script_args.get(script.title(), args[script.args_from:script.args_to])
-        if hasattr(script, 'run'):
-            processed = script.run(p, *parsed)
-        else:
-            processed = None
-            errors.log.error(f'Script: file="{script.filename}" no run function defined')
-        s.record(script.title())
-        s.report()
-        return processed
-
-    def after(self, p, processed, *args):
-        s = ScriptSummary('after')
-        script_index = args[0] if len(args) > 0 else 0
-        if script_index == 0:
-            return processed
-        script = self.selectable_scripts[script_index-1]
-        if script is None or not hasattr(script, 'after'):
-            return processed
-        parsed = []
-        if hasattr(script, 'args_to') and hasattr(script, 'args_from'):
-            parsed = p.per_script_args.get(script.title(), args[script.args_from:script.args_to])
-        after_processed = script.after(p, processed, *parsed)
-        if after_processed is not None:
-            processed = after_processed
-        s.record(script.title())
-        s.report()
-        return processed
-
-    def before_process(self, p, **kwargs):
-        s = ScriptSummary('before-process')
-        for script in self.alwayson_scripts:
-            try:
-                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
-                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
-                    script.before_process(p, *args, **kwargs)
-            except Exception as e:
-                errors.display(e, f"Error running before process: {script.filename}")
-            s.record(script.title())
-        s.report()
-
-    def process(self, p, **kwargs):
-        s = ScriptSummary('process')
-        for script in self.alwayson_scripts:
-            try:
-                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
-                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
-                    script.process(p, *args, **kwargs)
-            except Exception as e:
-                errors.display(e, f'Running script process: {script.filename}')
-            s.record(script.title())
-        s.report()
-
-    def process_images(self, p, **kwargs):
-        s = ScriptSummary('process_images')
-        processed = None
-        for script in self.alwayson_scripts:
-            try:
-                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
-                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
-                    _processed = script.process_images(p, *args, **kwargs)
-                    if _processed is not None:
-                        processed = _processed
-            except Exception as e:
-                errors.display(e, f'Running script process images: {script.filename}')
-            s.record(script.title())
-        s.report()
-        return processed
-
-    def before_process_batch(self, p, **kwargs):
-        s = ScriptSummary('before-process-batch')
-        for script in self.alwayson_scripts:
-            try:
-                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
-                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
-                    script.before_process_batch(p, *args, **kwargs)
-            except Exception as e:
-                errors.display(e, f'Running script before process batch: {script.filename}')
-            s.record(script.title())
-        s.report()
-
-    def process_batch(self, p, **kwargs):
-        s = ScriptSummary('process-batch')
-        for script in self.alwayson_scripts:
-            try:
-                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
-                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
-                    script.process_batch(p, *args, **kwargs)
-            except Exception as e:
-                errors.display(e, f'Running script process batch: {script.filename}')
-            s.record(script.title())
-        s.report()
-
-    def postprocess(self, p, processed):
-        s = ScriptSummary('postprocess')
-        for script in self.alwayson_scripts:
-            try:
-                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
-                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
-                    script.postprocess(p, processed, *args)
-            except Exception as e:
-                errors.display(e, f'Running script postprocess: {script.filename}')
-            s.record(script.title())
-        s.report()
-
-    def postprocess_batch(self, p, images, **kwargs):
-        s = ScriptSummary('postprocess-batch')
-        for script in self.alwayson_scripts:
-            try:
-                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
-                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
-                    script.postprocess_batch(p, *args, images=images, **kwargs)
-            except Exception as e:
-                errors.display(e, f'Running script before postprocess batch: {script.filename}')
-            s.record(script.title())
-        s.report()
-
-    def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, **kwargs):
-        s = ScriptSummary('postprocess-batch-list')
-        for script in self.alwayson_scripts:
-            try:
-                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
-                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
-                    script.postprocess_batch_list(p, pp, *args, **kwargs)
-            except Exception as e:
-                errors.display(e, f'Running script before postprocess batch list: {script.filename}')
-            s.record(script.title())
-        s.report()
-
-    def postprocess_image(self, p, pp: PostprocessImageArgs):
-        s = ScriptSummary('postprocess-image')
-        for script in self.alwayson_scripts:
-            try:
-                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
-                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
-                    script.postprocess_image(p, pp, *args)
-            except Exception as e:
-                errors.display(e, f'Running script postprocess image: {script.filename}')
-            s.record(script.title())
-        s.report()
-
-    def before_component(self, component, **kwargs):
-        s = ScriptSummary('before-component')
-        for script in self.scripts:
-            try:
-                script.before_component(component, **kwargs)
-            except Exception as e:
-                errors.display(e, f'Running script before component: {script.filename}')
-            s.record(script.title())
-        s.report()
-
-    def after_component(self, component, **kwargs):
-        s = ScriptSummary('after-component')
-        for script in self.scripts:
-            for elem_id, callback in script.on_after_component_elem_id:
-                if elem_id == kwargs.get("elem_id"):
-                    try:
-                        callback(OnComponent(component=component))
-                    except Exception as e:
-                        errors.display(e, f"Running script before_component_elem_id: {script.filename}")
-            try:
-                script.after_component(component, **kwargs)
-            except Exception as e:
-                errors.display(e, f'Running script after component: {script.filename}')
-            s.record(script.title())
-        s.report()
-
-    def reload_sources(self, cache):
-        s = ScriptSummary('reload-sources')
-        for si, script in list(enumerate(self.scripts)):
-            if hasattr(script, 'args_to') and hasattr(script, 'args_from'):
-                args_from = script.args_from
-                args_to = script.args_to
-                filename = script.filename
-                module = cache.get(filename, None)
-                if module is None:
-                    module = script_loading.load_module(script.filename)
-                    cache[filename] = module
-                for script_class in module.__dict__.values():
-                    if type(script_class) == type and issubclass(script_class, Script):
-                        self.scripts[si] = script_class()
-                        self.scripts[si].filename = filename
-                        self.scripts[si].args_from = args_from
-                        self.scripts[si].args_to = args_to
-                s.record(script.title())
-        s.report()
-
-
-scripts_txt2img: ScriptRunner = None
-scripts_img2img: ScriptRunner = None
-scripts_control: ScriptRunner = None
-scripts_current: ScriptRunner = None
-scripts_postproc: scripts_postprocessing.ScriptPostprocessingRunner = None
-reload_scripts = load_scripts  # compatibility alias
-
-
-def reload_script_body_only():
-    cache = {}
-    scripts_txt2img.reload_sources(cache)
-    scripts_img2img.reload_sources(cache)
-    scripts_control.reload_sources(cache)

modules/scripts_auto_postprocessing.py

@@ -1,7 +1,7 @@
-from modules import scripts, scripts_postprocessing, shared
+from modules import scripts_manager, scripts_postprocessing, shared
 
 
-class ScriptPostprocessingForMainUI(scripts.Script):
+class ScriptPostprocessingForMainUI(scripts_manager.Script):
     def __init__(self, script_postproc):
         self.script: scripts_postprocessing.ScriptPostprocessing = script_postproc
         self.postprocessing_controls = None
@@ -10,7 +10,7 @@ class ScriptPostprocessingForMainUI(scripts.Script):
         return self.script.name
 
     def show(self, is_img2img): # pylint: disable=unused-argument
-        return scripts.AlwaysVisible
+        return scripts_manager.AlwaysVisible
 
     def ui(self, is_img2img): # pylint: disable=unused-argument
         self.postprocessing_controls = self.script.ui()
@@ -28,9 +28,9 @@ class ScriptPostprocessingForMainUI(scripts.Script):
 def create_auto_preprocessing_script_data():
     res = []
     for name in shared.opts.postprocessing_enable_in_main_ui:
-        script = next(iter([x for x in scripts.postprocessing_scripts_data if x.script_class.name == name]), None)
+        script = next(iter([x for x in scripts_manager.postprocessing_scripts_data if x.script_class.name == name]), None)
         if script is None:
             continue
         constructor = lambda s=script: ScriptPostprocessingForMainUI(s.script_class()) # pylint: disable=unnecessary-lambda-assignment
-        res.append(scripts.ScriptClassData(script_class=constructor, path=script.path, basedir=script.basedir, module=script.module))
+        res.append(scripts_manager.ScriptClassData(script_class=constructor, path=script.path, basedir=script.basedir, module=script.module))
     return res

modules/scripts_manager.py

@@ -0,0 +1,730 @@
+import os
+import re
+import sys
+import time
+from collections import namedtuple
+from dataclasses import dataclass
+import gradio as gr
+from modules import paths, script_callbacks, extensions, script_loading, scripts_postprocessing, errors, timer
+from installer import control_extensions
+
+
+AlwaysVisible = object()
+time_component = {}
+time_setup = {}
+debug = errors.log.trace if os.environ.get('SD_SCRIPT_DEBUG', None) is not None else lambda *args, **kwargs: None
+
+
+class PostprocessImageArgs:
+    def __init__(self, image):
+        self.image = image
+
+
+class PostprocessBatchListArgs:
+    def __init__(self, images):
+        self.images = images
+
+
+@dataclass
+class OnComponent:
+    component: gr.blocks.Block
+
+
+class Script:
+    parent = None
+    name = None
+    filename = None
+    args_from = 0
+    args_to = 0
+    alwayson = False
+    is_txt2img = False
+    is_img2img = False
+    api_info = None
+    group = None
+    infotext_fields = None
+    paste_field_names = None
+    section = None
+    standalone = False
+    on_before_component_elem_id = [] # list of callbacks to be called before a component with an elem_id is created
+    on_after_component_elem_id = [] # list of callbacks to be called after a component with an elem_id is created
+
+    def title(self):
+        """this function should return the title of the script. This is what will be displayed in the dropdown menu."""
+        raise NotImplementedError
+
+    def ui(self, is_img2img):
+        """this function should create gradio UI elements. See https://gradio.app/docs/#components
+        The return value should be an array of all components that are used in processing.
+        Values of those returned components will be passed to run() and process() functions.
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def show(self, is_img2img): # pylint: disable=unused-argument
+        """
+        is_img2img is True if this function is called for the img2img interface, and False otherwise
+        This function should return:
+         - False if the script should not be shown in UI at all
+         - True if the script should be shown in UI if it's selected in the scripts dropdown
+         - script.AlwaysVisible if the script should be shown in UI at all times
+         """
+        return True
+
+    def run(self, p, *args):
+        """
+        This function is called if the script has been selected in the script dropdown.
+        It must do all processing and return the Processed object with results, same as
+        one returned by processing.process_images.
+        Usually the processing is done by calling the processing.process_images function.
+        args contains all values returned by components from ui()
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def setup(self, p, *args):
+        """For AlwaysVisible scripts, this function is called when the processing object is set up, before any processing starts.
+        args contains all values returned by components from ui().
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def before_process(self, p, *args):
+        """
+        This function is called very early during processing begins for AlwaysVisible scripts.
+        You can modify the processing object (p) here, inject hooks, etc.
+        args contains all values returned by components from ui()
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def process(self, p, *args):
+        """
+        This function is called before processing begins for AlwaysVisible scripts.
+        You can modify the processing object (p) here, inject hooks, etc.
+        args contains all values returned by components from ui()
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def process_images(self, p, *args):
+        """
+        This function is called instead of main processing for AlwaysVisible scripts.
+        You can modify the processing object (p) here, inject hooks, etc.
+        args contains all values returned by components from ui()
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def before_process_batch(self, p, *args, **kwargs):
+        """
+        Called before extra networks are parsed from the prompt, so you can add
+        new extra network keywords to the prompt with this callback.
+        **kwargs will have those items:
+          - batch_number - index of current batch, from 0 to number of batches-1
+          - prompts - list of prompts for current batch; you can change contents of this list but changing the number of entries will likely break things
+          - seeds - list of seeds for current batch
+          - subseeds - list of subseeds for current batch
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def process_batch(self, p, *args, **kwargs):
+        """
+        Same as process(), but called for every batch.
+        **kwargs will have those items:
+          - batch_number - index of current batch, from 0 to number of batches-1
+          - prompts - list of prompts for current batch; you can change contents of this list but changing the number of entries will likely break things
+          - seeds - list of seeds for current batch
+          - subseeds - list of subseeds for current batch
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def postprocess_batch(self, p, *args, **kwargs):
+        """
+        Same as process_batch(), but called for every batch after it has been generated.
+        **kwargs will have same items as process_batch, and also:
+          - batch_number - index of current batch, from 0 to number of batches-1
+          - images - torch tensor with all generated images, with values ranging from 0 to 1;
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def postprocess_image(self, p, pp: PostprocessImageArgs, *args):
+        """
+        Called for every image after it has been generated.
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, *args, **kwargs):
+        """
+        Same as postprocess_batch(), but receives batch images as a list of 3D tensors instead of a 4D tensor.
+        This is useful when you want to update the entire batch instead of individual images.
+        You can modify the postprocessing object (pp) to update the images in the batch, remove images, add images, etc.
+        If the number of images is different from the batch size when returning,
+        then the script has the responsibility to also update the following attributes in the processing object (p):
+          - p.prompts
+          - p.negative_prompts
+          - p.seeds
+          - p.subseeds
+        **kwargs will have same items as process_batch, and also:
+          - batch_number - index of current batch, from 0 to number of batches-1
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def postprocess(self, p, processed, *args):
+        """
+        This function is called after processing ends for AlwaysVisible scripts.
+        args contains all values returned by components from ui()
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def before_component(self, component, **kwargs):
+        """
+        Called before a component is created.
+        Use elem_id/label fields of kwargs to figure out which component it is.
+        This can be useful to inject your own components somewhere in the middle of vanilla UI.
+        You can return created components in the ui() function to add them to the list of arguments for your processing functions
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def after_component(self, component, **kwargs):
+        """
+        Called after a component is created. Same as above.
+        """
+        pass # pylint: disable=unnecessary-pass
+
+    def describe(self):
+        """unused"""
+        return ""
+
+    def elem_id(self, item_id):
+        """helper function to generate id for a HTML element, constructs final id out of script name, tab and user-supplied item_id"""
+        title = re.sub(r'[^a-z_0-9]', '', re.sub(r'\s', '_', self.title().lower()))
+        return f'script_{self.parent}_{title}_{item_id}'
+
+
+current_basedir = paths.script_path
+
+
+def basedir():
+    """returns the base directory for the current script. For scripts in the main scripts directory,
+    this is the main directory (where webui.py resides), and for scripts in extensions directory
+    (ie extensions/aesthetic/script/aesthetic.py), this is extension's directory (extensions/aesthetic)
+    """
+    return current_basedir
+
+
+ScriptFile = namedtuple("ScriptFile", ["basedir", "filename", "path", "priority"])
+scripts_data = []
+postprocessing_scripts_data = []
+ScriptClassData = namedtuple("ScriptClassData", ["script_class", "path", "basedir", "module"])
+
+
+def list_scripts(scriptdirname, extension):
+    tmp_list = []
+    base = os.path.join(paths.script_path, scriptdirname)
+    if os.path.exists(base):
+        for filename in sorted(os.listdir(base)):
+            tmp_list.append(ScriptFile(paths.script_path, filename, os.path.join(base, filename), '50'))
+    for ext in extensions.active():
+        tmp_list += ext.list_files(scriptdirname, extension)
+    priority_list = []
+    for script in tmp_list:
+        if os.path.splitext(script.path)[1].lower() == extension and os.path.isfile(script.path):
+            if script.basedir == paths.script_path:
+                priority = '0'
+            elif script.basedir.startswith(os.path.join(paths.script_path, 'scripts')):
+                priority = '1'
+            elif script.basedir.startswith(os.path.join(paths.script_path, 'extensions-builtin')):
+                priority = '2'
+            elif script.basedir.startswith(os.path.join(paths.script_path, 'extensions')):
+                priority = '3'
+            else:
+                priority = '9'
+            if os.path.isfile(os.path.join(base, "..", ".priority")):
+                with open(os.path.join(base, "..", ".priority"), "r", encoding="utf-8") as f:
+                    priority = priority + str(f.read().strip())
+                    errors.log.debug(f'Script priority override: ${script.name}:{priority}')
+            else:
+                priority = priority + script.priority
+            priority_list.append(ScriptFile(script.basedir, script.filename, script.path, priority))
+            debug(f'Adding script: folder="{script.basedir}" file="{script.filename}" full="{script.path}" priority={priority}')
+    priority_sort = sorted(priority_list, key=lambda item: item.priority + item.path.lower(), reverse=False)
+    return priority_sort
+
+
+def list_files_with_name(filename):
+    res = []
+    dirs = [paths.script_path] + [ext.path for ext in extensions.active()]
+    for dirpath in dirs:
+        if not os.path.isdir(dirpath):
+            continue
+        path = os.path.join(dirpath, filename)
+        if os.path.isfile(path):
+            res.append(path)
+    return res
+
+
+def load_scripts():
+    t = timer.Timer()
+    t0 = time.time()
+    global current_basedir # pylint: disable=global-statement
+    scripts_data.clear()
+    postprocessing_scripts_data.clear()
+    script_callbacks.clear_callbacks()
+    scripts_list = list_scripts('scripts', '.py') + list_scripts(os.path.join('modules', 'face'), '.py')
+    scripts_list = sorted(scripts_list, key=lambda item: item.priority + item.path.lower(), reverse=False)
+    syspath = sys.path
+
+    def register_scripts_from_module(module, scriptfile):
+        for script_class in module.__dict__.values():
+            if type(script_class) != type:
+                continue
+            debug(f'Registering script: path="{scriptfile.path}"')
+            if issubclass(script_class, Script):
+                scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir, module))
+            elif issubclass(script_class, scripts_postprocessing.ScriptPostprocessing):
+                postprocessing_scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir, module))
+
+    for scriptfile in scripts_list:
+        try:
+            if scriptfile.basedir != paths.script_path:
+                sys.path = [scriptfile.basedir] + sys.path
+            current_basedir = scriptfile.basedir
+            script_module = script_loading.load_module(scriptfile.path)
+            register_scripts_from_module(script_module, scriptfile)
+        except Exception as e:
+            errors.display(e, f'Load script: {scriptfile.filename}')
+        finally:
+            current_basedir = paths.script_path
+            t.record(os.path.basename(scriptfile.basedir) if scriptfile.basedir != paths.script_path else scriptfile.filename)
+            sys.path = syspath
+
+    global scripts_txt2img, scripts_img2img, scripts_control, scripts_postproc # pylint: disable=global-statement
+    scripts_txt2img = ScriptRunner('txt2img')
+    scripts_img2img = ScriptRunner('img2img')
+    scripts_control = ScriptRunner('control')
+    scripts_postproc = scripts_postprocessing.ScriptPostprocessingRunner()
+    return t, time.time()-t0
+
+
+def wrap_call(func, filename, funcname, *args, default=None, **kwargs):
+    try:
+        res = func(*args, **kwargs)
+        return res
+    except Exception as e:
+        errors.display(e, f'Calling script: {filename}/{funcname}')
+    return default
+
+
+class ScriptSummary:
+    def __init__(self, op):
+        self.start = time.time()
+        self.update = time.time()
+        self.op = op
+        self.time = {}
+
+    def record(self, script):
+        self.update = time.time()
+        self.time[script] = round(time.time() - self.update, 2)
+
+    def report(self):
+        total = sum(self.time.values())
+        if total == 0:
+            return
+        scripts = [f'{k}:{v}' for k, v in self.time.items() if v > 0]
+        errors.log.debug(f'Script: op={self.op} total={total} scripts={scripts}')
+
+
+class ScriptRunner:
+    def __init__(self, name=''):
+        self.name = name
+        self.scripts = []
+        self.selectable_scripts = []
+        self.alwayson_scripts = []
+        self.auto_processing_scripts = []
+        self.titles = []
+        self.infotext_fields = []
+        self.paste_field_names = []
+        self.script_load_ctr = 0
+        self.is_img2img = False
+        self.inputs = [None]
+        self.time = 0
+
+    def add_script(self, script_class, path, is_img2img, is_control):
+        try:
+            script = script_class()
+            script.filename = path
+            script.is_txt2img = not is_img2img
+            script.is_img2img = is_img2img
+            if is_control: # this is messy but show is a legacy function that is not aware of control tab
+                v1 = script.show(script.is_txt2img)
+                v2 = script.show(script.is_img2img)
+                if v1 == AlwaysVisible or v2 == AlwaysVisible:
+                    visibility = AlwaysVisible
+                else:
+                    visibility = v1 or v2
+            else:
+                visibility = script.show(script.is_img2img)
+            if visibility == AlwaysVisible:
+                self.scripts.append(script)
+                self.alwayson_scripts.append(script)
+                script.alwayson = True
+            elif visibility:
+                self.scripts.append(script)
+                self.selectable_scripts.append(script)
+        except Exception as e:
+            errors.log.error(f'Script initialize: {path} {e}')
+
+    def initialize_scripts(self, is_img2img=False, is_control=False):
+        from modules import scripts_auto_postprocessing
+
+        self.scripts.clear()
+        self.selectable_scripts.clear()
+        self.alwayson_scripts.clear()
+        self.titles.clear()
+        self.infotext_fields.clear()
+        self.paste_field_names.clear()
+        self.script_load_ctr = 0
+        self.is_img2img = is_img2img
+        self.scripts.clear()
+        self.alwayson_scripts.clear()
+        self.selectable_scripts.clear()
+        self.auto_processing_scripts = scripts_auto_postprocessing.create_auto_preprocessing_script_data()
+
+        sorted_scripts = sorted(scripts_data, key=lambda x: x.script_class().title().lower())
+        for script_class, path, _basedir, _script_module in sorted_scripts:
+            self.add_script(script_class, path, is_img2img, is_control)
+        sorted_scripts = sorted(self.auto_processing_scripts, key=lambda x: x.script_class().title().lower())
+        for script_class, path, _basedir, _script_module in sorted_scripts:
+            self.add_script(script_class, path, is_img2img, is_control)
+
+    def prepare_ui(self):
+        self.inputs = [None]
+
+    def setup_ui(self, parent='unknown', accordion=True):
+        import modules.api.models as api_models
+        self.titles = [wrap_call(script.title, script.filename, "title") or f"{script.filename} [error]" for script in self.selectable_scripts]
+
+        inputs = []
+        inputs_alwayson = [True]
+
+        def create_script_ui(script: Script, inputs, inputs_alwayson):
+            script.parent = parent
+            script.args_from = len(inputs)
+            script.args_to = len(inputs)
+            controls = wrap_call(script.ui, script.filename, "ui", script.is_img2img)
+            if controls is None:
+                return
+            script.name = wrap_call(script.title, script.filename, "title", default=script.filename).lower()
+            api_args = []
+            for control in controls:
+                debug(f'Script control: parent={script.parent} script="{script.name}" label="{control.label}" type={control} id={control.elem_id}')
+                if hasattr(gr.components, 'IOComponent'):
+                    if not isinstance(control, gr.components.IOComponent):
+                        errors.log.error(f'Invalid script control: "{script.filename}" control={control}')
+                        continue
+                else:
+                    if not isinstance(control, gr.components.Component):
+                        errors.log.error(f'Invalid script control: "{script.filename}" control={control}')
+                        continue
+                control.custom_script_source = os.path.basename(script.filename)
+                arg_info = api_models.ScriptArg(label=control.label or "")
+                for field in ("value", "minimum", "maximum", "step", "choices"):
+                    v = getattr(control, field, None)
+                    if v is not None:
+                        setattr(arg_info, field, v)
+                api_args.append(arg_info)
+
+            script.api_info = api_models.ItemScript(
+                name=script.name,
+                is_img2img=script.is_img2img,
+                is_alwayson=script.alwayson,
+                args=api_args,
+            )
+            if script.infotext_fields is not None:
+                self.infotext_fields += script.infotext_fields
+            if script.paste_field_names is not None:
+                self.paste_field_names += script.paste_field_names
+            inputs += controls
+            inputs_alwayson += [script.alwayson for _ in controls]
+            script.args_to = len(inputs)
+
+        with gr.Row():
+            dropdown = gr.Dropdown(label="Script", elem_id=f'{parent}_script_list', choices=["None"] + self.titles, value="None", type="index")
+            inputs.insert(0, dropdown)
+
+        with gr.Row():
+            for script in self.alwayson_scripts:
+                if not script.standalone:
+                    continue
+                if (self.name == 'control') and (script.name not in control_extensions) and (script.title() not in control_extensions):
+                    errors.log.debug(f'Script: fn="{script.filename}" type={self.name} skip')
+                    continue
+                t0 = time.time()
+                with gr.Group(elem_id=f'{parent}_script_{script.title().lower().replace(" ", "_")}', elem_classes=['group-extension']) as group:
+                    create_script_ui(script, inputs, inputs_alwayson)
+                script.group = group
+                time_setup[script.title()] = time_setup.get(script.title(), 0) + (time.time()-t0)
+
+        with gr.Row():
+            with gr.Accordion(label="Extensions", elem_id=f'{parent}_script_alwayson') if accordion else gr.Group():
+                for script in self.alwayson_scripts:
+                    if script.standalone:
+                        continue
+                    if (self.name == 'control') and (paths.extensions_dir in script.filename) and (script.title() not in control_extensions):
+                        errors.log.debug(f'Script: fn="{script.filename}" type={self.name} skip')
+                        continue
+                    t0 = time.time()
+                    with gr.Group(elem_id=f'{parent}_script_{script.title().lower().replace(" ", "_")}', elem_classes=['group-extension']) as group:
+                        create_script_ui(script, inputs, inputs_alwayson)
+                    script.group = group
+                    time_setup[script.title()] = time_setup.get(script.title(), 0) + (time.time()-t0)
+
+        for script in self.selectable_scripts:
+            if (self.name == 'control') and (paths.extensions_dir in script.filename) and (script.title() not in control_extensions):
+                errors.log.debug(f'Script: fn="{script.filename}" type={self.name} skip')
+                continue
+            with gr.Group(elem_id=f'{parent}_script_{script.title().lower().replace(" ", "_")}', elem_classes=['group-scripts'], visible=False) as group:
+                t0 = time.time()
+                create_script_ui(script, inputs, inputs_alwayson)
+                time_setup[script.title()] = time_setup.get(script.title(), 0) + (time.time()-t0)
+                script.group = group
+
+        def select_script(script_index):
+            if script_index is None:
+                return [gr.update(visible=False) for script in self.selectable_scripts]
+            selected_script = self.selectable_scripts[script_index - 1] if script_index > 0 else None
+            return [gr.update(visible=selected_script == s) for s in self.selectable_scripts]
+
+        def init_field(title):
+            if title == 'None': # called when an initial value is set from ui-config.json to show script's UI components
+                return
+            if title not in self.titles:
+                errors.log.error(f'Script not found: {title}')
+                return
+            script_index = self.titles.index(title)
+            self.selectable_scripts[script_index].group.visible = True
+
+        dropdown.init_field = init_field
+        dropdown.change(fn=select_script, inputs=[dropdown], outputs=[script.group for script in self.selectable_scripts if script.group is not None])
+
+        def onload_script_visibility(params):
+            title = params.get('Script', None)
+            if title:
+                title_index = self.titles.index(title)
+                visibility = title_index == self.script_load_ctr
+                self.script_load_ctr = (self.script_load_ctr + 1) % len(self.titles)
+                return gr.update(visible=visibility)
+            else:
+                return gr.update(visible=False)
+
+        self.infotext_fields.append((dropdown, lambda x: gr.update(value=x.get('Script', 'None'))))
+        self.infotext_fields.extend([(script.group, onload_script_visibility) for script in self.selectable_scripts if script.group is not None])
+        return inputs
+
+    def run(self, p, *args):
+        s = ScriptSummary('run')
+        script_index = args[0] if len(args) > 0 else 0
+        if script_index == 0:
+            return None
+        script = self.selectable_scripts[script_index-1]
+        if script is None:
+            return None
+        if 'upscale' in script.title():
+            if not hasattr(p, 'init_images') and p.task_args.get('image', None) is not None:
+                p.init_images = p.task_args['image']
+        parsed = []
+        if hasattr(script, 'args_to') and hasattr(script, 'args_from'):
+            parsed = p.per_script_args.get(script.title(), args[script.args_from:script.args_to])
+        if hasattr(script, 'run'):
+            processed = script.run(p, *parsed)
+        else:
+            processed = None
+            errors.log.error(f'Script: file="{script.filename}" no run function defined')
+        s.record(script.title())
+        s.report()
+        return processed
+
+    def after(self, p, processed, *args):
+        s = ScriptSummary('after')
+        script_index = args[0] if len(args) > 0 else 0
+        if script_index == 0:
+            return processed
+        script = self.selectable_scripts[script_index-1]
+        if script is None or not hasattr(script, 'after'):
+            return processed
+        parsed = []
+        if hasattr(script, 'args_to') and hasattr(script, 'args_from'):
+            parsed = p.per_script_args.get(script.title(), args[script.args_from:script.args_to])
+        after_processed = script.after(p, processed, *parsed)
+        if after_processed is not None:
+            processed = after_processed
+        s.record(script.title())
+        s.report()
+        return processed
+
+    def before_process(self, p, **kwargs):
+        s = ScriptSummary('before-process')
+        for script in self.alwayson_scripts:
+            try:
+                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
+                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
+                    script.before_process(p, *args, **kwargs)
+            except Exception as e:
+                errors.display(e, f"Error running before process: {script.filename}")
+            s.record(script.title())
+        s.report()
+
+    def process(self, p, **kwargs):
+        s = ScriptSummary('process')
+        for script in self.alwayson_scripts:
+            try:
+                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
+                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
+                    script.process(p, *args, **kwargs)
+            except Exception as e:
+                errors.display(e, f'Running script process: {script.filename}')
+            s.record(script.title())
+        s.report()
+
+    def process_images(self, p, **kwargs):
+        s = ScriptSummary('process_images')
+        processed = None
+        for script in self.alwayson_scripts:
+            try:
+                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
+                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
+                    _processed = script.process_images(p, *args, **kwargs)
+                    if _processed is not None:
+                        processed = _processed
+            except Exception as e:
+                errors.display(e, f'Running script process images: {script.filename}')
+            s.record(script.title())
+        s.report()
+        return processed
+
+    def before_process_batch(self, p, **kwargs):
+        s = ScriptSummary('before-process-batch')
+        for script in self.alwayson_scripts:
+            try:
+                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
+                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
+                    script.before_process_batch(p, *args, **kwargs)
+            except Exception as e:
+                errors.display(e, f'Running script before process batch: {script.filename}')
+            s.record(script.title())
+        s.report()
+
+    def process_batch(self, p, **kwargs):
+        s = ScriptSummary('process-batch')
+        for script in self.alwayson_scripts:
+            try:
+                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
+                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
+                    script.process_batch(p, *args, **kwargs)
+            except Exception as e:
+                errors.display(e, f'Running script process batch: {script.filename}')
+            s.record(script.title())
+        s.report()
+
+    def postprocess(self, p, processed):
+        s = ScriptSummary('postprocess')
+        for script in self.alwayson_scripts:
+            try:
+                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
+                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
+                    script.postprocess(p, processed, *args)
+            except Exception as e:
+                errors.display(e, f'Running script postprocess: {script.filename}')
+            s.record(script.title())
+        s.report()
+
+    def postprocess_batch(self, p, images, **kwargs):
+        s = ScriptSummary('postprocess-batch')
+        for script in self.alwayson_scripts:
+            try:
+                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
+                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
+                    script.postprocess_batch(p, *args, images=images, **kwargs)
+            except Exception as e:
+                errors.display(e, f'Running script before postprocess batch: {script.filename}')
+            s.record(script.title())
+        s.report()
+
+    def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, **kwargs):
+        s = ScriptSummary('postprocess-batch-list')
+        for script in self.alwayson_scripts:
+            try:
+                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
+                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
+                    script.postprocess_batch_list(p, pp, *args, **kwargs)
+            except Exception as e:
+                errors.display(e, f'Running script before postprocess batch list: {script.filename}')
+            s.record(script.title())
+        s.report()
+
+    def postprocess_image(self, p, pp: PostprocessImageArgs):
+        s = ScriptSummary('postprocess-image')
+        for script in self.alwayson_scripts:
+            try:
+                if hasattr(script, 'args_to') and hasattr(script, 'args_from') and (script.args_to > 0) and (script.args_to >= script.args_from):
+                    args = p.per_script_args.get(script.title(), p.script_args[script.args_from:script.args_to])
+                    script.postprocess_image(p, pp, *args)
+            except Exception as e:
+                errors.display(e, f'Running script postprocess image: {script.filename}')
+            s.record(script.title())
+        s.report()
+
+    def before_component(self, component, **kwargs):
+        s = ScriptSummary('before-component')
+        for script in self.scripts:
+            try:
+                script.before_component(component, **kwargs)
+            except Exception as e:
+                errors.display(e, f'Running script before component: {script.filename}')
+            s.record(script.title())
+        s.report()
+
+    def after_component(self, component, **kwargs):
+        s = ScriptSummary('after-component')
+        for script in self.scripts:
+            for elem_id, callback in script.on_after_component_elem_id:
+                if elem_id == kwargs.get("elem_id"):
+                    try:
+                        callback(OnComponent(component=component))
+                    except Exception as e:
+                        errors.display(e, f"Running script before_component_elem_id: {script.filename}")
+            try:
+                script.after_component(component, **kwargs)
+            except Exception as e:
+                errors.display(e, f'Running script after component: {script.filename}')
+            s.record(script.title())
+        s.report()
+
+    def reload_sources(self, cache):
+        s = ScriptSummary('reload-sources')
+        for si, script in list(enumerate(self.scripts)):
+            if hasattr(script, 'args_to') and hasattr(script, 'args_from'):
+                args_from = script.args_from
+                args_to = script.args_to
+                filename = script.filename
+                module = cache.get(filename, None)
+                if module is None:
+                    module = script_loading.load_module(script.filename)
+                    cache[filename] = module
+                for script_class in module.__dict__.values():
+                    if type(script_class) == type and issubclass(script_class, Script):
+                        self.scripts[si] = script_class()
+                        self.scripts[si].filename = filename
+                        self.scripts[si].args_from = args_from
+                        self.scripts[si].args_to = args_to
+                s.record(script.title())
+        s.report()
+
+
+scripts_txt2img: ScriptRunner = None
+scripts_img2img: ScriptRunner = None
+scripts_control: ScriptRunner = None
+scripts_current: ScriptRunner = None
+scripts_postproc: scripts_postprocessing.ScriptPostprocessingRunner = None
+reload_scripts = load_scripts  # compatibility alias
+
+
+def reload_script_body_only():
+    cache = {}
+    scripts_txt2img.reload_sources(cache)
+    scripts_img2img.reload_sources(cache)
+    scripts_control.reload_sources(cache)

modules/scripts_postprocessing.py

@@ -72,8 +72,8 @@ class ScriptPostprocessingRunner:
 
     def scripts_in_preferred_order(self):
         if self.scripts is None:
-            import modules.scripts
+            import modules.scripts_manager
-            self.initialize_scripts(modules.scripts.postprocessing_scripts_data)
+            self.initialize_scripts(modules.scripts_manager.postprocessing_scripts_data)
         scripts_order = shared.opts.postprocessing_operation_order
 
         def script_score(name):

modules/sd_models.py

@@ -306,7 +306,7 @@ def load_diffuser_force(model_type, checkpoint_info, diffusers_load_config, op='
     shared.sd_model = None
     try:
         if model_type in ['Stable Cascade']: # forced pipeline
-            from modules.model_stablecascade import load_cascade_combined
+            from pipelines.model_stablecascade import load_cascade_combined
             sd_model = load_cascade_combined(checkpoint_info, diffusers_load_config)
             allow_post_quant = True
         elif model_type in ['InstaFlow']: # forced pipeline
@@ -315,77 +315,77 @@ def load_diffuser_force(model_type, checkpoint_info, diffusers_load_config, op='
             sd_model = pipeline.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
             allow_post_quant = True
         elif model_type in ['SegMoE']: # forced pipeline
-            from modules.segmoe.segmoe_model import SegMoEPipeline
+            from pipelines.segmoe.segmoe_model import SegMoEPipeline
             sd_model = SegMoEPipeline(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
             sd_model = sd_model.pipe # segmoe pipe does its stuff in __init__ and __call__ is the original pipeline
             allow_post_quant = True
             shared_items.pipelines['SegMoE'] = SegMoEPipeline
         elif model_type in ['PixArt Sigma']: # forced pipeline
-            from modules.model_pixart import load_pixart
+            from pipelines.model_pixart import load_pixart
             sd_model = load_pixart(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['Sana']: # forced pipeline
-            from modules.model_sana import load_sana
+            from pipelines.model_sana import load_sana
             sd_model = load_sana(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['Lumina-Next']: # forced pipeline
-            from modules.model_lumina import load_lumina
+            from pipelines.model_lumina import load_lumina
             sd_model = load_lumina(checkpoint_info, diffusers_load_config)
             allow_post_quant = True
         elif model_type in ['Kolors']: # forced pipeline
-            from modules.model_kolors import load_kolors
+            from pipelines.model_kolors import load_kolors
             sd_model = load_kolors(checkpoint_info, diffusers_load_config)
             allow_post_quant = True
         elif model_type in ['AuraFlow']: # forced pipeline
-            from modules.model_auraflow import load_auraflow
+            from pipelines.model_auraflow import load_auraflow
             sd_model = load_auraflow(checkpoint_info, diffusers_load_config)
             allow_post_quant = True
         elif model_type in ['FLUX']:
-            from modules.model_flux import load_flux
+            from pipelines.model_flux import load_flux
             sd_model = load_flux(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['FLEX']:
-            from modules.model_flex import load_flex
+            from pipelines.model_flex import load_flex
             sd_model = load_flex(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['Chroma']:
-            from modules.model_chroma import load_chroma
+            from pipelines.model_chroma import load_chroma
             sd_model = load_chroma(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['Lumina 2']:
-            from modules.model_lumina import load_lumina2
+            from pipelines.model_lumina import load_lumina2
             sd_model = load_lumina2(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['Stable Diffusion 3']:
-            from modules.model_sd3 import load_sd3
+            from pipelines.model_sd3 import load_sd3
             sd_model = load_sd3(checkpoint_info, cache_dir=shared.opts.diffusers_dir, config=diffusers_load_config.get('config', None))
             allow_post_quant = False
         elif model_type in ['CogView 3']: # forced pipeline
-            from modules.model_cogview import load_cogview3
+            from pipelines.model_cogview import load_cogview3
             sd_model = load_cogview3(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['CogView 4']: # forced pipeline
-            from modules.model_cogview import load_cogview4
+            from pipelines.model_cogview import load_cogview4
             sd_model = load_cogview4(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['Meissonic']: # forced pipeline
-            from modules.model_meissonic import load_meissonic
+            from pipelines.model_meissonic import load_meissonic
             sd_model = load_meissonic(checkpoint_info, diffusers_load_config)
             allow_post_quant = True
         elif model_type in ['OmniGen2']: # forced pipeline
-            from modules.model_omnigen2 import load_omnigen2
+            from pipelines.model_omnigen2 import load_omnigen2
             sd_model = load_omnigen2(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['OmniGen']: # forced pipeline
-            from modules.model_omnigen import load_omnigen
+            from pipelines.model_omnigen import load_omnigen
             sd_model = load_omnigen(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['HiDream']:
-            from modules.model_hidream import load_hidream
+            from pipelines.model_hidream import load_hidream
             sd_model = load_hidream(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
         elif model_type in ['Cosmos']:
-            from modules.model_cosmos import load_cosmos_t2i
+            from pipelines.model_cosmos import load_cosmos_t2i
             sd_model = load_cosmos_t2i(checkpoint_info, diffusers_load_config)
             allow_post_quant = False
     except Exception as e:
@@ -480,7 +480,7 @@ def load_diffuser_file(model_type, pipeline, checkpoint_info, diffusers_load_con
                         shared.log.debug(f'Load {op}: config="{model_config}"')
                     diffusers_load_config['config'] = model_config
         if model_type.startswith('Stable Diffusion 3'):
-            from modules.model_sd3 import load_sd3
+            from pipelines.model_sd3 import load_sd3
             sd_model = load_sd3(checkpoint_info=checkpoint_info, cache_dir=shared.opts.diffusers_dir, config=diffusers_load_config.get('config', None))
         elif hasattr(pipeline, 'from_single_file'):
             diffusers.loaders.single_file_utils.CHECKPOINT_KEY_NAMES["clip"] = "cond_stage_model.transformer.text_model.embeddings.position_embedding.weight" # patch for diffusers==0.28.0
@@ -1069,7 +1069,7 @@ def reload_model_weights(sd_model=None, info=None, reuse_dict=False, op='model',
             unload_model_weights(op=op)
             sd_model = None
     timer = Timer()
-    # TODO model loader: implement model in-memory caching
+    # TODO model load: implement model in-memory caching
     state_dict = get_checkpoint_state_dict(checkpoint_info, timer) if not shared.native else None
     checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info)
     timer.record("config")

modules/sd_unet.py

@@ -25,7 +25,7 @@ def load_unet(model):
         if shared.opts.sd_unet == loaded_unet or shared.opts.sd_unet in failed_unet:
             pass
         elif "StableCascade" in model.__class__.__name__:
-            from modules.model_stablecascade import load_prior
+            from pipelines.model_stablecascade import load_prior
             prior_unet, prior_text_encoder = load_prior(unet_dict[shared.opts.sd_unet], config_file=config_file)
             loaded_unet = shared.opts.sd_unet
             if prior_unet is not None:
@@ -38,7 +38,7 @@ def load_unet(model):
             loaded_unet = shared.opts.sd_unet
             sd_models.load_diffuser() # TODO model load: force-reloading entire model as loading transformers only leads to massive memory usage
             """
-            from modules.model_flux import load_transformer
+            from pipelines.model_flux import load_transformer
             transformer = load_transformer(unet_dict[shared.opts.sd_unet])
             if transformer is not None:
                 model.transformer = None

modules/sdnq/__init__.py

@@ -14,7 +14,7 @@ from .dequantizer import dequantizer_dict
 from .forward import get_forward_func
 
 
-def sdnq_quantize_layer(layer, weights_dtype="int8", torch_dtype=None, group_size=0, quant_conv=False, use_quantized_matmul=False, use_quantized_matmul_conv=False, dequantize_fp32=False, quantization_device=None, return_device=None, param_name=None):
+def sdnq_quantize_layer(layer, weights_dtype="int8", torch_dtype=None, group_size=0, quant_conv=False, use_quantized_matmul=False, use_quantized_matmul_conv=False, dequantize_fp32=False, quantization_device=None, return_device=None, param_name=None): # pylint: disable=unused-argument
     layer_class_name = layer.__class__.__name__
     if layer_class_name in allowed_types:
         is_conv_type = False

modules/shared_items.py

@@ -61,8 +61,8 @@ onnx_pipelines = {
 
 
 def postprocessing_scripts():
-    import modules.scripts
+    import modules.scripts_manager
-    return modules.scripts.scripts_postproc.scripts
+    return modules.scripts_manager.scripts_postproc.scripts
 
 
 def sd_vae_items():

modules/txt2img.py

@@ -1,5 +1,5 @@
 import os
-from modules import shared, processing, scripts
+from modules import shared, processing, scripts_manager
 from modules.generation_parameters_copypaste import create_override_settings_dict
 from modules.ui_common import plaintext_to_html
 
@@ -90,13 +90,13 @@ def txt2img(id_task, state,
         hdr_boundary=hdr_boundary, hdr_threshold=hdr_threshold, hdr_maximize=hdr_maximize, hdr_max_center=hdr_max_center, hdr_max_boundry=hdr_max_boundry, hdr_color_picker=hdr_color_picker, hdr_tint_ratio=hdr_tint_ratio,
         override_settings=override_settings,
     )
-    p.scripts = scripts.scripts_txt2img
+    p.scripts = scripts_manager.scripts_txt2img
     p.script_args = args
     p.state = state
-    processed: processing.Processed = scripts.scripts_txt2img.run(p, *args)
+    processed: processing.Processed = scripts_manager.scripts_txt2img.run(p, *args)
     if processed is None:
         processed = processing.process_images(p)
-    processed = scripts.scripts_txt2img.after(p, processed, *args)
+    processed = scripts_manager.scripts_txt2img.after(p, processed, *args)
     p.close()
     if processed is None:
         return [], '', '', 'Error: processing failed'

modules/ui.py

@@ -2,7 +2,7 @@ import mimetypes
 import gradio as gr
 import gradio.routes
 import gradio.utils
-from modules import errors, timer, gr_hijack, shared, script_callbacks, ui_common, ui_symbols, ui_javascript, ui_sections, generation_parameters_copypaste, call_queue, scripts
+from modules import errors, timer, gr_hijack, shared, script_callbacks, ui_common, ui_symbols, ui_javascript, ui_sections, generation_parameters_copypaste, call_queue, scripts_manager
 from modules.paths import script_path, data_path # pylint: disable=unused-import
 
 
@@ -76,7 +76,7 @@ def create_ui(startup_timer = None):
         timer.startup = timer.Timer()
     ui_javascript.reload_javascript()
     generation_parameters_copypaste.reset()
-    scripts.scripts_current = None
+    scripts_manager.scripts_current = None
 
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
         from modules import ui_txt2img

modules/ui_common.py

@@ -6,7 +6,7 @@ import platform
 import subprocess
 from functools import reduce
 import gradio as gr
-from modules import call_queue, shared, prompt_parser, ui_sections, ui_symbols, ui_components, generation_parameters_copypaste, images, scripts, script_callbacks, infotext
+from modules import call_queue, shared, prompt_parser, ui_sections, ui_symbols, ui_components, generation_parameters_copypaste, images, scripts_manager, script_callbacks, infotext
 
 
 folder_symbol = ui_symbols.folder
@@ -304,11 +304,11 @@ def create_output_panel(tabname, preview=True, prompt=None, height=None, transfe
                 )
 
             if tabname == "txt2img":
-                paste_field_names = scripts.scripts_txt2img.paste_field_names
+                paste_field_names = scripts_manager.scripts_txt2img.paste_field_names
             elif tabname == "img2img":
-                paste_field_names = scripts.scripts_img2img.paste_field_names
+                paste_field_names = scripts_manager.scripts_img2img.paste_field_names
             elif tabname == "control":
-                paste_field_names = scripts.scripts_control.paste_field_names
+                paste_field_names = scripts_manager.scripts_control.paste_field_names
             else:
                 paste_field_names = []
             debug(f'Paste field: tab={tabname} fields={paste_field_names}')

modules/ui_control.py

@@ -9,7 +9,7 @@ from modules.control.units import xs # vislearn ControlNet-XS
 from modules.control.units import lite # vislearn ControlNet-XS
 from modules.control.units import t2iadapter # TencentARC T2I-Adapter
 from modules.control.units import reference # reference pipeline
-from modules import errors, shared, progress, ui_components, ui_symbols, ui_common, ui_sections, generation_parameters_copypaste, call_queue, scripts, masking, images, processing_vae, timer # pylint: disable=ungrouped-imports
+from modules import errors, shared, progress, ui_components, ui_symbols, ui_common, ui_sections, generation_parameters_copypaste, call_queue, scripts_manager, masking, images, processing_vae, timer # pylint: disable=ungrouped-imports
 from modules import ui_control_helpers as helpers
 
 
@@ -539,7 +539,7 @@ def create_ui(_blocks: gr.Blocks=None):
                             setting.change(fn=processors.update_settings, inputs=settings, outputs=[])
 
             with gr.Row(elem_id="control_script_container"):
-                input_script_args = scripts.scripts_current.setup_ui(parent='control', accordion=True)
+                input_script_args = scripts_manager.scripts_current.setup_ui(parent='control', accordion=True)
 
             # handlers
             for btn in input_buttons:
@@ -709,7 +709,7 @@ def create_ui(_blocks: gr.Blocks=None):
                 # hidden
                 (seed_resize_from_w, "Seed resize from-1"),
                 (seed_resize_from_h, "Seed resize from-2"),
-                *scripts.scripts_control.infotext_fields
+                *scripts_manager.scripts_control.infotext_fields
             ]
             generation_parameters_copypaste.add_paste_fields("control", input_image, paste_fields, override_settings)
             bindings = generation_parameters_copypaste.ParamBinding(paste_button=btn_paste, tabname="control", source_text_component=prompt, source_image_component=output_gallery)

modules/ui_control_helpers.py

@@ -1,7 +1,7 @@
 import os
 import gradio as gr
 from PIL import Image
-from modules import shared, scripts, masking, video # pylint: disable=ungrouped-imports
+from modules import shared, scripts_manager, masking, video # pylint: disable=ungrouped-imports
 
 
 gr_height = None
@@ -43,8 +43,8 @@ def initialize():
         os.makedirs(masking.cache_dir, exist_ok=True)
     except Exception:
         pass
-    scripts.scripts_current = scripts.scripts_control
+    scripts_manager.scripts_current = scripts_manager.scripts_control
-    scripts.scripts_control.initialize_scripts(is_img2img=False, is_control=True)
+    scripts_manager.scripts_control.initialize_scripts(is_img2img=False, is_control=True)
 
 
 def interrogate():

modules/ui_img2img.py

@@ -35,8 +35,8 @@ def process_interrogate(mode, ii_input_files, ii_input_dir, ii_output_dir, *ii_s
 def create_ui():
     shared.log.debug('UI initialize: img2img')
     import modules.img2img # pylint: disable=redefined-outer-name
-    modules.scripts.scripts_current = modules.scripts.scripts_img2img
+    modules.scripts_manager.scripts_current = modules.scripts_manager.scripts_img2img
-    modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True, is_control=False)
+    modules.scripts_manager.scripts_img2img.initialize_scripts(is_img2img=True, is_control=False)
     with gr.Blocks(analytics_enabled=False) as _img2img_interface:
         img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, img2img_submit, img2img_reprocess, img2img_paste, img2img_extra_networks_button, img2img_token_counter, img2img_token_button, img2img_negative_token_counter, img2img_negative_token_button = ui_sections.create_toprow(is_img2img=True, id_part="img2img")
         img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="binary", visible=False)
@@ -156,7 +156,7 @@ def create_ui():
                     override_settings = ui_common.create_override_inputs('img2img')
 
                 with gr.Group(elem_id="img2img_script_container"):
-                    img2img_script_inputs = modules.scripts.scripts_img2img.setup_ui(parent='img2img', accordion=True)
+                    img2img_script_inputs = modules.scripts_manager.scripts_img2img.setup_ui(parent='img2img', accordion=True)
 
             img2img_gallery, img2img_generation_info, img2img_html_info, _img2img_html_info_formatted, img2img_html_log = ui_common.create_output_panel("img2img", prompt=img2img_prompt)
 
@@ -304,7 +304,7 @@ def create_ui():
                 # hidden
                 (seed_resize_from_w, "Seed resize from-1"),
                 (seed_resize_from_h, "Seed resize from-2"),
-                *modules.scripts.scripts_img2img.infotext_fields
+                *modules.scripts_manager.scripts_img2img.infotext_fields
             ]
             generation_parameters_copypaste.add_paste_fields("img2img", img_init, img2img_paste_fields, override_settings)
             generation_parameters_copypaste.add_paste_fields("sketch", img_sketch, img2img_paste_fields, override_settings)

modules/ui_javascript.py

@@ -3,7 +3,7 @@ import gradio.routes
 import gradio.utils
 from modules import shared, theme
 from modules.paths import script_path, data_path
-import modules.scripts
+import modules.scripts_manager
 
 
 def webpath(fn):
@@ -22,12 +22,12 @@ def html_head():
         script_js = os.path.join(script_path, "javascript", js)
         head += f'<script type="text/javascript" src="{webpath(script_js)}"></script>\n'
     added = []
-    for script in modules.scripts.list_scripts("javascript", ".js"):
+    for script in modules.scripts_manager.list_scripts("javascript", ".js"):
         if script.filename in main or script.filename in skip:
             continue
         head += f'<script type="text/javascript" src="{webpath(script.path)}"></script>\n'
         added.append(script.path)
-    for script in modules.scripts.list_scripts("javascript", ".mjs"):
+    for script in modules.scripts_manager.list_scripts("javascript", ".mjs"):
         head += f'<script type="module" src="{webpath(script.path)}"></script>\n'
         added.append(script.path)
     added = [a.replace(script_path, '').replace('\\', '/') for a in added]
@@ -59,7 +59,7 @@ def html_css(css: str):
     head = ''
     if css is not None:
         head += stylesheet(os.path.join(script_path, 'javascript', css))
-    for cssfile in modules.scripts.list_files_with_name("style.css"):
+    for cssfile in modules.scripts_manager.list_files_with_name("style.css"):
         if not os.path.isfile(cssfile):
             continue
         head += stylesheet(cssfile)

modules/ui_postprocessing.py

@@ -1,6 +1,6 @@
 import json
 import gradio as gr
-from modules import scripts, shared, ui_common, postprocessing, call_queue, generation_parameters_copypaste
+from modules import scripts_manager, shared, ui_common, postprocessing, call_queue, generation_parameters_copypaste
 
 
 def submit_info(image):
@@ -32,7 +32,7 @@ def create_ui():
             with gr.Row():
                 save_output = gr.Checkbox(label='Save output', value=True, elem_id="extras_save_output")
 
-            script_inputs = scripts.scripts_postproc.setup_ui()
+            script_inputs = scripts_manager.scripts_postproc.setup_ui()
         with gr.Column():
             id_part = 'extras'
             with gr.Row(elem_id=f"{id_part}_generate_box", elem_classes="generate-box"):
@@ -56,7 +56,7 @@ def create_ui():
     tab_batch.select(fn=lambda: 1, inputs=[], outputs=[tab_index])
     tab_batch_dir.select(fn=lambda: 2, inputs=[], outputs=[tab_index])
     extras_image.change(fn=submit_info, inputs=[extras_image], outputs=[html_info_formatted, exif_info, gen_info])
-    extras_image.change(fn=scripts.scripts_postproc.image_changed, inputs=[], outputs=[])
+    extras_image.change(fn=scripts_manager.scripts_postproc.image_changed, inputs=[], outputs=[])
     submit.click(
         _js="submit_postprocessing",
         fn=call_queue.wrap_gradio_gpu_call(submit_process, extra_outputs=[None, ''], name='Postprocess'),

modules/ui_txt2img.py

@@ -17,8 +17,8 @@ def calc_resolution_hires(width, height, hr_scale, hr_resize_x, hr_resize_y, hr_
 def create_ui():
     shared.log.debug('UI initialize: txt2img')
     import modules.txt2img # pylint: disable=redefined-outer-name
-    modules.scripts.scripts_current = modules.scripts.scripts_txt2img
+    modules.scripts_manager.scripts_current = modules.scripts_manager.scripts_txt2img
-    modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False, is_control=False)
+    modules.scripts_manager.scripts_txt2img.initialize_scripts(is_img2img=False, is_control=False)
     with gr.Blocks(analytics_enabled=False) as _txt2img_interface:
         txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, txt2img_submit, txt2img_reprocess, txt2img_paste, txt2img_extra_networks_button, txt2img_token_counter, txt2img_token_button, txt2img_negative_token_counter, txt2img_negative_token_button = ui_sections.create_toprow(is_img2img=False, id_part="txt2img")
 
@@ -52,7 +52,7 @@ def create_ui():
                     state = gr.Textbox(value='', visible=False)
 
                 with gr.Group(elem_id="txt2img_script_container"):
-                    txt2img_script_inputs = modules.scripts.scripts_txt2img.setup_ui(parent='txt2img', accordion=True)
+                    txt2img_script_inputs = modules.scripts_manager.scripts_txt2img.setup_ui(parent='txt2img', accordion=True)
 
             txt2img_gallery, txt2img_generation_info, txt2img_html_info, _txt2img_html_info_formatted, txt2img_html_log = ui_common.create_output_panel("txt2img", preview=True, prompt=txt2img_prompt)
             ui_common.connect_reuse_seed(seed, reuse_seed, txt2img_generation_info, is_subseed=False)
@@ -158,7 +158,7 @@ def create_ui():
                 # hidden
                 (seed_resize_from_w, "Seed resize from-1"),
                 (seed_resize_from_h, "Seed resize from-2"),
-                *modules.scripts.scripts_txt2img.infotext_fields
+                *modules.scripts_manager.scripts_txt2img.infotext_fields
             ]
             generation_parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields, override_settings)
             txt2img_bindings = generation_parameters_copypaste.ParamBinding(paste_button=txt2img_paste, tabname="txt2img", source_text_component=txt2img_prompt, source_image_component=None)

package.json

@@ -21,7 +21,7 @@
     "localize": "node cli/localize.js",
     "ruff": ". venv/bin/activate && ruff check",
     "eslint": "eslint javascript/ extensions-builtin/sdnext-modernui/javascript/",
-    "pylint": ". venv/bin/activate && pylint *.py modules/ extensions-builtin/ | grep -v '^*'",
+    "pylint": ". venv/bin/activate && pylint *.py modules/ pipelines/ scripts/ extensions-builtin/ | grep -v '^*'",
     "lint": "npm run eslint && npm run ruff && npm run pylint",
     "test": "cli/test.sh"
   },

pipelines/model_chroma.py

@@ -173,7 +173,7 @@ def load_transformer(file_path): # triggered by opts.sd_unet change
             if transformer is not None:
                 return transformer
         shared.log.info(f'Load module: type=UNet/Transformer file="{file_path}" offload={shared.opts.diffusers_offload_mode} quant=none dtype={devices.dtype}')
-        # TODO chroma transformer from-single-file with quant
+        # TODO model load: chroma transformer from-single-file with quant
         # shared.log.warning('Load module: type=UNet/Transformer does not support load-time quantization')
         # transformer = diffusers.ChromaTransformer2DModel.from_single_file(file_path, **diffusers_load_config)
     if transformer is None:
@@ -261,8 +261,8 @@ def load_chroma(checkpoint_info, diffusers_load_config): # triggered by opts.sd_
     if vae is not None:
         kwargs['vae'] = vae
 
-    # TODO add ChromaFillPipeline, ChromaControlPipeline, ChromaImg2ImgPipeline etc when available
+    # TODO model load: add ChromaFillPipeline, ChromaControlPipeline, ChromaImg2ImgPipeline etc when available
-    # TODO Chroma will support inpainting *after* its training has finished: https://huggingface.co/lodestones/Chroma/discussions/28#6826dd2ed86f53ff983add5c
+    # Chroma will support inpainting *after* its training has finished: https://huggingface.co/lodestones/Chroma/discussions/28#6826dd2ed86f53ff983add5c
     cls = diffusers.ChromaPipeline
     shared.log.debug(f'Load model: type=Chroma cls={cls.__name__} preloaded={list(kwargs)} revision={diffusers_load_config.get("revision", None)}')
     for c in kwargs:

pipelines/model_cogview.py

@@ -76,6 +76,6 @@ def load_cogview4(checkpoint_info, diffusers_load_config={}):
     if shared.opts.diffusers_eval:
         pipe.text_encoder.eval()
         pipe.transformer.eval()
-    pipe.enable_model_cpu_offload() # TODO cogview4: balanced offload does not work for GlmModel
+    pipe.enable_model_cpu_offload() # TODO model fix: cogview4: balanced offload does not work for GlmModel
     devices.torch_gc()
     return pipe

pipelines/model_flex.py

@@ -24,9 +24,6 @@ def load_transformer(repo_id, diffusers_load_config={}):
     elif fn is not None and 'safetensors' in fn.lower():
         shared.log.debug(f'Load model: type=FLEX transformer="{repo_id}" quant="{model_quant.get_quant(repo_id)}" args={load_args}')
         transformer = diffusers.FluxTransformer2DModel.from_single_file(fn, cache_dir=shared.opts.hfcache_dir, **load_args)
-    # elif model_quant.check_nunchaku('Model'):
-    #     shared.log.error(f'Load model: type=HiDream transformer="{repo_id}" quant="Nunchaku" unsupported')
-    #     transformer = None
     else:
         shared.log.debug(f'Load model: type=FLEX transformer="{repo_id}" quant="{model_quant.get_quant_type(quant_args)}" args={load_args}')
         transformer = diffusers.FluxTransformer2DModel.from_pretrained(
@@ -71,7 +68,7 @@ def load_flex(checkpoint_info, diffusers_load_config={}):
     load_args, _quant_args = model_quant.get_dit_args(diffusers_load_config, module='Model')
     shared.log.debug(f'Load model: type=FLEX model="{checkpoint_info.name}" repo="{repo_id}" offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args}')
 
-    from modules.flex2 import Flex2Pipeline
+    from pipelines.flex2 import Flex2Pipeline
     pipe = Flex2Pipeline.from_pretrained(
         repo_id,
         # custom_pipeline=repo_id,

pipelines/model_flux.py

@@ -175,7 +175,7 @@ def load_transformer(file_path): # triggered by opts.sd_unet change
         if _transformer is not None:
             transformer = _transformer
     elif 'nf4' in quant: # TODO flux: loader for civitai nf4 models
-        from modules.model_flux_nf4 import load_flux_nf4
+        from pipelines.model_flux_nf4 import load_flux_nf4
         _transformer, _text_encoder_2 = load_flux_nf4(file_path, prequantized=True)
         if _transformer is not None:
             transformer = _transformer
@@ -183,7 +183,7 @@ def load_transformer(file_path): # triggered by opts.sd_unet change
         quant_args = model_quant.create_bnb_config({})
         if quant_args:
             shared.log.info(f'Load module: type=UNet/Transformer file="{file_path}" offload={shared.opts.diffusers_offload_mode} quant=bnb dtype={devices.dtype}')
-            from modules.model_flux_nf4 import load_flux_nf4
+            from pipelines.model_flux_nf4 import load_flux_nf4
             transformer, _text_encoder_2 = load_flux_nf4(file_path, prequantized=False)
             if transformer is not None:
                 return transformer
@@ -275,7 +275,7 @@ def load_flux(checkpoint_info, diffusers_load_config): # triggered by opts.sd_ch
     # load quantized components if any
     if prequantized == 'nf4':
         try:
-            from modules.model_flux_nf4 import load_flux_nf4
+            from pipelines.model_flux_nf4 import load_flux_nf4
             _transformer, _text_encoder = load_flux_nf4(checkpoint_info)
             if _transformer is not None:
                 transformer = _transformer

pipelines/model_hidream.py

@@ -102,7 +102,7 @@ def load_hidream(checkpoint_info, diffusers_load_config={}):
     if 'I1' in repo_id:
         cls = diffusers.HiDreamImagePipeline
     elif 'E1' in repo_id:
-        from modules.hidream.pipeline_hidream_image_editing import HiDreamImageEditingPipeline
+        from pipelines.hidream.pipeline_hidream_image_editing import HiDreamImageEditingPipeline
         cls = HiDreamImageEditingPipeline
         diffusers.pipelines.auto_pipeline.AUTO_TEXT2IMAGE_PIPELINES_MAPPING["hidream-e1"] = diffusers.HiDreamImagePipeline
         diffusers.pipelines.auto_pipeline.AUTO_IMAGE2IMAGE_PIPELINES_MAPPING["hidream-e1"] = HiDreamImageEditingPipeline

pipelines/model_meissonic.py

@@ -4,11 +4,11 @@ import diffusers
 
 def load_meissonic(checkpoint_info, diffusers_load_config={}):
     from modules import shared, devices, modelloader, sd_models, shared_items
-    from modules.meissonic.transformer import Transformer2DModel as TransformerMeissonic
+    from pipelines.meissonic.transformer import Transformer2DModel as TransformerMeissonic
-    from modules.meissonic.scheduler import Scheduler as MeissonicScheduler
+    from pipelines.meissonic.scheduler import Scheduler as MeissonicScheduler
-    from modules.meissonic.pipeline import Pipeline as PipelineMeissonic
+    from pipelines.meissonic.pipeline import Pipeline as PipelineMeissonic
-    from modules.meissonic.pipeline_img2img import Img2ImgPipeline as PipelineMeissonicImg2Img
+    from pipelines.meissonic.pipeline_img2img import Img2ImgPipeline as PipelineMeissonicImg2Img
-    from modules.meissonic.pipeline_inpaint import InpaintPipeline as PipelineMeissonicInpaint
+    from pipelines.meissonic.pipeline_inpaint import InpaintPipeline as PipelineMeissonicInpaint
     shared_items.pipelines['Meissonic'] = PipelineMeissonic
 
     modelloader.hf_login()

pipelines/model_omnigen.py

@@ -1,6 +1,6 @@
 import os
 import diffusers
-from modules import errors, shared, devices, sd_models, model_quant
+from modules import shared, devices, sd_models, model_quant
 
 debug = shared.log.trace if os.environ.get('SD_LOAD_DEBUG', None) is not None else lambda *args, **kwargs: None
 

pipelines/model_omnigen2.py

@@ -7,7 +7,7 @@ debug = shared.log.trace if os.environ.get('SD_LOAD_DEBUG', None) is not None el
 def load_omnigen2(checkpoint_info, diffusers_load_config={}): # pylint: disable=unused-argument
     repo_id = sd_models.path_to_repo(checkpoint_info.name)
 
-    from modules.omnigen2 import OmniGen2Pipeline, OmniGen2Transformer2DModel, Qwen2_5_VLForConditionalGeneration
+    from pipelines.omnigen2 import OmniGen2Pipeline, OmniGen2Transformer2DModel, Qwen2_5_VLForConditionalGeneration
     import diffusers
     from diffusers import pipelines
     diffusers.OmniGen2Pipeline = OmniGen2Pipeline # monkey-pathch

scripts/allegrovideo.py

@@ -2,7 +2,7 @@ import time
 import gradio as gr
 import transformers
 import diffusers
-from modules import scripts, processing, shared, images, devices, sd_models, sd_checkpoint, model_quant, timer, sd_hijack_te
+from modules import scripts_manager, processing, shared, images, devices, sd_models, sd_checkpoint, model_quant, timer, sd_hijack_te
 
 
 repo_id = 'rhymes-ai/Allegro'
@@ -19,7 +19,7 @@ def hijack_decode(*args, **kwargs):
     return res
 
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
     def title(self):
         return 'Video: Allegro (Legacy)'
 

scripts/animatediff.py

@@ -2,7 +2,7 @@ import os
 import gradio as gr
 import diffusers
 from safetensors.torch import load_file
-from modules import scripts, processing, shared, devices, sd_models
+from modules import scripts_manager, processing, shared, devices, sd_models
 
 
 # config
@@ -189,12 +189,12 @@ def set_free_noise(frames):
         shared.sd_model.enable_free_noise(context_length=context_length, context_stride=context_stride)
 
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
     def title(self):
         return 'Video: AnimateDiff'
 
     def show(self, is_img2img):
-        # return scripts.AlwaysVisible if shared.native else False
+        # return scripts_manager.AlwaysVisible if shared.native else False
         return not is_img2img
 
 
@@ -231,7 +231,7 @@ class Script(scripts.Script):
         lora = LORAS[lora_index]
         set_adapter(adapter)
         if motion_adapter is None:
-            return
+            return None
         set_scheduler(p, adapter, override_scheduler)
         set_lora(p, lora, strength)
         set_free_init(fi_method, fi_iters, fi_order, fi_spatial, fi_temporal)

scripts/apg.py

@@ -1,11 +1,11 @@
 import gradio as gr
-from modules import scripts, processing, shared, sd_models
+from modules import scripts_manager, processing, shared, sd_models
 
 
 registered = False
 
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
     def __init__(self):
         super().__init__()
         self.orig_pipe = None
@@ -71,6 +71,7 @@ class Script(scripts.Script):
         shared.log.info(f'APG apply: guidance={p.cfg_scale} momentum={apg.momentum} eta={apg.eta} threshold={apg.threshold} class={shared.sd_model.__class__.__name__}')
         p.extra_generation_params["APG"] = f'ETA={apg.eta} Momentum={apg.momentum} Threshold={apg.threshold}'
         # processed = processing.process_images(p)
+        return None
 
     def after(self, p: processing.StableDiffusionProcessing, processed: processing.Processed, eta, momentum, threshold): # pylint: disable=arguments-differ, unused-argument
         from modules import apg

scripts/automatic_color_inpaint.py

@@ -1,7 +1,7 @@
 import gradio as gr
 from PIL import Image
 import numpy as np
-from modules import shared, scripts, processing, masking
+from modules import shared, scripts_manager, processing, masking
 
 """
 Automatic Color Inpaint Script for SD.NEXT - SD & SDXL Support
@@ -28,7 +28,7 @@ img2img = True
 
 ### Script definition
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
     def title(self):
         return title
 

scripts/blipdiffusion.py

@@ -1,8 +1,8 @@
 import gradio as gr
-from modules import scripts, processing, shared, sd_models
+from modules import scripts_manager, processing, shared, sd_models
 
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
     def title(self):
         return 'BLIP Diffusion: Controllable Generation and Editing'
 

scripts/cogvideo.py

@@ -13,14 +13,14 @@ import torch
 from torchvision import transforms
 import diffusers
 import numpy as np
-from modules import scripts, shared, devices, errors, sd_models, processing
+from modules import scripts_manager, shared, devices, errors, sd_models, processing
 from modules.processing_callbacks import diffusers_callback, set_callbacks_p
 
 
 debug = (os.environ.get('SD_LOAD_DEBUG', None) is not None) or (os.environ.get('SD_PROCESS_DEBUG', None) is not None)
 
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
     def title(self):
         return 'Video: CogVideoX (Legacy)'
 

scripts/consistory_ext.py

@@ -12,10 +12,10 @@ ported to modules/consistory
 import time
 import gradio as gr
 import diffusers
-from modules import scripts, devices, errors, processing, shared, sd_models, sd_samplers
+from modules import scripts_manager, devices, errors, processing, shared, sd_models, sd_samplers
 
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
     def __init__(self):
         super().__init__()
         self.anchor_cache_first_stage = None
@@ -66,7 +66,7 @@ class Script(scripts.Script):
 
     def create_model(self):
         diffusers.models.embeddings.PositionNet = diffusers.models.embeddings.GLIGENTextBoundingboxProjection # patch as renamed in https://github.com/huggingface/diffusers/pull/6244/files
-        import modules.consistory as cs
+        import scripts.consistory as cs
         if shared.sd_model.__class__.__name__ != 'ConsistoryExtendAttnSDXLPipeline':
             shared.log.debug('ConsiStory init')
             t0 = time.time()
@@ -128,7 +128,7 @@ class Script(scripts.Script):
         return concepts, anchors, prompts, alpha, steps, seed
 
     def create_anchors(self, anchors, concepts, seed, steps, dropout, same, queries, sdsa, injection, alpha):
-        import modules.consistory as cs
+        import scripts.consistory as cs
         t0 = time.time()
         if len(anchors) == 0:
             shared.log.warning('ConsiStory: no anchors')
@@ -159,7 +159,7 @@ class Script(scripts.Script):
         return images
 
     def create_extra(self, prompt, concepts, seed, steps, dropout, same, queries, sdsa, injection, alpha):
-        import modules.consistory as cs
+        import scripts.consistory as cs
         t0 = time.time()
         images = []
         shared.log.debug(f'ConsiStory extra: concepts={concepts} prompt="{prompt}"')

scripts/ctrlx_ext.py

@@ -2,10 +2,10 @@
 
 import gradio as gr
 from diffusers import StableDiffusionXLPipeline
-from modules import shared, scripts, processing, processing_helpers, sd_models, devices
+from modules import shared, scripts_manager, processing, processing_helpers, sd_models, devices
 
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
     def title(self):
         return 'Ctrl-X: Controlling Structure and Appearance'
 
@@ -44,9 +44,9 @@ class Script(scripts.Script):
             return None
 
         import yaml
-        from modules.ctrlx import CtrlXStableDiffusionXLPipeline
+        from scripts.ctrlx import CtrlXStableDiffusionXLPipeline
-        from modules.ctrlx.sdxl import get_control_config, register_control
+        from scripts.ctrlx.sdxl import get_control_config, register_control
-        from modules.ctrlx.utils import get_self_recurrence_schedule
+        from scripts.ctrlx.utils import get_self_recurrence_schedule
 
         orig_prompt_attention = shared.opts.prompt_attention
         shared.opts.data['prompt_attention'] = 'fixed'

scripts/custom_code.py

@@ -1,8 +1,7 @@
 import copy
 import ast
 import gradio as gr
-import modules.scripts as scripts
+from modules import scripts_manager
-
 from modules.processing import Processed
 from modules.shared import opts, cmd_opts, state # pylint: disable=unused-import
 
@@ -28,14 +27,15 @@ def exec_with_return(code, module):
     last_ast = copy.deepcopy(code_ast)
     last_ast.body = code_ast.body[-1:]
 
-    exec(compile(init_ast, "<ast>", "exec"), module.__dict__)
+    exec(compile(init_ast, "<ast>", "exec"), module.__dict__) # pylint: disable=exec-used
     if type(last_ast.body[0]) == ast.Expr:
-        return eval(compile(convertExpr2Expression(last_ast.body[0]), "<ast>", "eval"), module.__dict__)
+        return eval(compile(convertExpr2Expression(last_ast.body[0]), "<ast>", "eval"), module.__dict__) # pylint: disable=eval-used
     else:
-        exec(compile(last_ast, "<ast>", "exec"), module.__dict__)
+        exec(compile(last_ast, "<ast>", "exec"), module.__dict__) # pylint: disable=exec-used
+    return None
 
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
 
     def title(self):
         return "Custom code"
@@ -60,7 +60,7 @@ return process_images(p)
 
         return [code, indent_level]
 
-    def run(self, p, code, indent_level):
+    def run(self, p, code, indent_level): # pylint: disable=arguments-differ
         assert cmd_opts.allow_code, '--allow-code option must be enabled'
 
         display_result_data = [[], -1, ""]

scripts/demofusion.py

@@ -14,7 +14,7 @@ from diffusers.schedulers import KarrasDiffusionSchedulers
 from diffusers.utils import is_accelerate_available, is_accelerate_version
 from diffusers.utils.torch_utils import randn_tensor
 from diffusers.pipelines.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
-from modules import scripts, processing, shared, sd_models, devices
+from modules import scripts_manager, processing, shared, sd_models, devices
 
 
 ### Class definition
@@ -1219,7 +1219,7 @@ class DemoFusionSDXLPipeline(DiffusionPipeline, FromSingleFileMixin, LoraLoaderM
 
 ### Script definition
 
-class Script(scripts.Script):
+class Script(scripts_manager.Script):
     def title(self):
         return 'DemoFusion: High-Resolution Image Generation'