fix lint

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

.github/skills/analyze-model/SKILL.md

@@ -130,4 +130,4 @@ If critical information is missing, explicitly list unknowns and what to inspect
 
 - Prefer concrete evidence from repository files and model card over assumptions.
 - If source suggests multiple possible paths, compare at least two and state why one is preferred.
-- Keep recommendations aligned with the conventions defined in the port-model skill.
+- Keep recommendations aligned with the conventions defined in the port-model skill.

.github/skills/check-models/SKILL.md

@@ -148,4 +148,4 @@ A full pass requires all of the following in audited scope:
 - reference entries are valid, categorized correctly, and have preview files
 - custom pipeline contracts are consistent with actual model behavior
 
-If any area is intentionally out of scope, mark as partial pass with explicit exclusions.
+If any area is intentionally out of scope, mark as partial pass with explicit exclusions.

.github/skills/check-schedulers/SKILL.md

@@ -146,4 +146,4 @@ The check passes only if all are true:
 - each `SamplerData` entry is correctly mapped and usable
 - no blocking runtime or compile-path failures in validated scope
 
-If scope is partial due to environment limitations, report pass with explicit limitations, not a full pass.
+If scope is partial due to environment limitations, report pass with explicit limitations, not a full pass.

.github/skills/debug-model/SKILL.md

@@ -214,4 +214,4 @@ When closing the task, report which of these were completed:
 - "The new model port fails in from_pretrained"
 - "SD.Next detects my custom pipeline as the wrong model type"
 - "The loader works but generation returns black images"
-- "This standalone-script port loads weights but crashes in attention"
+- "This standalone-script port loads weights but crashes in attention"

.github/skills/fix-lint/SKILL.md

@@ -29,8 +29,8 @@ If activation fails, report the blocker and stop before running Python-based too
 Run tools in this exact sequence:
 
 1. `pre-commit run --all-files`
-2. `eslint . javascript/`
-3. `cd extensions-builtin/sdnext-modernui && eslint . javascript/`
+2. `{PROJECT_ROOT}/node_modules/.bin/eslint . javascript/`
+3. `cd extensions-builtin/sdnext-modernui && {PROJECT_ROOT}/node_modules/.bin/eslint . javascript/`
 4. `ruff check`
 5. `pylint *.py`
 6. `pylint modules/`
@@ -38,6 +38,8 @@ Run tools in this exact sequence:
 8. `pylint scripts/`
 9. `pylint extensions-builtin/`
 
+Note that `pylint` can run for considerable time, so run with no timeouts.
+
 ## Fix Policy
 
 - Fix issues reported by each tool before moving on.

.github/skills/github-issues/SKILL.md

@@ -6,12 +6,12 @@ argument-hint: "Optionally specify state (open/closed/all), max issues, and whet
 
 # Summarize SD.Next [Issues] GitHub Issues
 
-Fetch issues from the SD.Next GitHub repository that contain `[Issues]` in the title, then produce a concise markdown report with one entry per issue.
+Fetch issues from the SD.Next GitHub repository that contain `[Issue]` in the title, then produce a concise markdown report with one entry per issue.
 
 ## When To Use
 
 - The user asks for periodic issue triage summaries
-- You need an actionable status report for `[Issues]` tracker items
+- You need an actionable status report for `[Issue]` tracker items
 - You want suggested next actions for each matching issue
 
 ## Repository

.github/skills/port-model/SKILL.md

@@ -244,4 +244,4 @@ When using this skill, the final implementation should usually include:
 - "Port this standalone inference script into an SD.Next Diffusers pipeline"
 - "Add support for this Hugging Face model repo to SD.Next"
 - "Wire this upstream Diffusers pipeline into SD.Next autodetect and loading"
-- "Convert this single-file checkpoint model into a custom Diffusers pipeline for SD.Next"
+- "Convert this single-file checkpoint model into a custom Diffusers pipeline for SD.Next"

TODO.md

@@ -135,7 +135,6 @@ installer.py:TODO rocm: switch to pytorch source when it becomes available
 modules/control/run.py:TODO modernui: monkey-patch for missing tabs.select event
 modules/history.py:TODO: apply metadata, preview, load/save
 modules/image/resize.py:TODO resize image: enable full VAE mode for resize-latent
-modules/lora/lora_apply.py:TODO lora: add other quantization types
 modules/lora/lora_apply.py:TODO lora: maybe force imediate quantization
 modules/lora/lora_extract.py:TODO: lora: support pre-quantized flux
 modules/lora/lora_load.py:TODO lora: add t5 key support for sd35/f1

modules/lora/lora_apply.py

@@ -161,7 +161,6 @@ def network_add_weights(self: torch.nn.Conv2d | torch.nn.Linear | torch.nn.Group
     if model_weights is None: # weights are used if provided-from-backup else use self.weight
         model_weights = self.weight
     weight, new_weight = None, None
-    # TODO lora: add other quantization types
     if self.__class__.__name__ == 'Linear4bit' and bnb is not None:
         try:
             dequant_weight = bnb.functional.dequantize_4bit(model_weights.to(devices.device), quant_state=self.quant_state, quant_type=self.quant_type, blocksize=self.blocksize)

modules/lora/lora_extract.py

@@ -186,19 +186,6 @@ def make_lora(fn, maxrank, auto_rank, rank_ratio, modules, overwrite):
             progress.remove_task(task)
         t3 = time.time()
 
-        # TODO: lora: support pre-quantized flux
-        # if 'te' in modules and getattr(shared.sd_model, 'transformer', None) is not None:
-        #     for name, module in shared.sd_model.transformer.named_modules():
-        #         if "norm" in name and "linear" not in name:
-        #             continue
-        #         weights_backup = getattr(module, "network_weights_backup", None)
-        #         if weights_backup is None:
-        #             continue
-        #         module.svdhandler = SVDHandler()
-        #         module.svdhandler.network_name = "lora_transformer_" + name.replace(".", "_")
-        #         module.svdhandler.decompose(module.weight, weights_backup)
-        #         module.svdhandler.findrank(rank, rank_ratio)
-
         lora_state_dict = {}
         for sub in ['text_encoder', 'text_encoder_2', 'unet', 'transformer']:
             submodel = getattr(shared.sd_model, sub, None)

scripts/custom_code.py

@@ -40,10 +40,10 @@ class CustomCodeScript(scripts_manager.Script):
     def title(self):
         return "Custom code"
 
-    def show(self, is_img2img):
+    def show(self, _is_img2img):
         return cmd_opts.allow_code
 
-    def ui(self, is_img2img):
+    def ui(self, _is_img2img):
         example = """from modules.processing import process_images
 
 p.width = 768

scripts/hdr.py

@@ -13,10 +13,10 @@ class HDRScript(scripts_manager.Script):
     def title(self):
         return "HDR: High Dynamic Range"
 
-    def show(self, is_img2img):
+    def show(self, _is_img2img):
         return True
 
-    def ui(self, is_img2img):
+    def ui(self, _is_img2img):
         with gr.Row():
             gr.HTML("<span>&nbsp HDR: High Dynamic Range</span><br>")
         with gr.Row():

scripts/init_latents.py

@@ -8,7 +8,7 @@ class InitLatentsScript(scripts_manager.Script):
     def title(self):
         return 'Init Latents'
 
-    def show(self, is_img2img):
+    def show(self, _is_img2img):
         return scripts_manager.AlwaysVisible
 
     @staticmethod
@@ -29,7 +29,7 @@ class InitLatentsScript(scripts_manager.Script):
         p.init_latent = slerp(p.subseed_strength, latents, var_latents) if p.subseed_strength < 1 else var_latents
         p.generator = generator if p.subseed_strength <= 0.5 else var_generator
 
-    def process_batch(self, p: processing.StableDiffusionProcessing, *args, **kwargs): # pylint: disable=arguments-differ
+    def process_batch(self, p: processing.StableDiffusionProcessing, *args, **_kwargs): # pylint: disable=arguments-differ
         if not shared.sd_loaded or not hasattr(shared.sd_model, 'unet'):
             return
         from modules.processing_helpers import create_random_tensors

scripts/ipadapter.py

@@ -14,7 +14,7 @@ class IPAdapterScript(scripts_manager.Script):
     def title(self):
         return 'IP Adapters'
 
-    def show(self, is_img2img):
+    def show(self, _is_img2img):
         return scripts_manager.AlwaysVisible
 
     def load_images(self, files):

scripts/loopback.py

@@ -11,10 +11,10 @@ class LoopbackScript(scripts_manager.Script):
     def title(self):
         return "Loopback"
 
-    def show(self, is_img2img):
+    def show(self, _is_img2img):
         return True
 
-    def ui(self, is_img2img):
+    def ui(self, _is_img2img):
         with gr.Row():
             gr.HTML("<span>&nbsp Loopback</span><br>")
         with gr.Row():

scripts/mulan.py

@@ -49,7 +49,7 @@ class MuLanScript(scripts_manager.Script):
     def title(self):
         return 'MuLan: Multi Language Prompts'
 
-    def show(self, is_img2img):
+    def show(self, _is_img2img):
         return True
 
     def ui(self, _is_img2img):

scripts/prompt_enhance.py

@@ -936,7 +936,7 @@ class PromptEnhanceScript(scripts_manager.Script):
             apply_btn.click(fn=self.apply, inputs=[self.prompt, self.image, apply_prompt, llm_model, prompt_system, prompt_prefix, prompt_suffix, max_tokens, do_sample, temperature, repetition_penalty, top_k, top_p, thinking_mode, nsfw_mode, use_vision, prefill_text, keep_prefill, keep_thinking], outputs=[prompt_output, self.prompt])
         return [self.prompt, self.image, apply_auto, llm_model, prompt_system, prompt_prefix, prompt_suffix, max_tokens, do_sample, temperature, repetition_penalty, top_k, top_p, thinking_mode, nsfw_mode, use_vision, prefill_text, keep_prefill, keep_thinking]
 
-    def after_component(self, component, **kwargs): # searching for actual ui prompt components
+    def after_component(self, component, **_kwargs): # searching for actual ui prompt components
         if getattr(component, 'elem_id', '') in ['txt2img_prompt', 'img2img_prompt', 'control_prompt', 'video_prompt']:
             self.prompt = component
             self.prompt.use_original = True

scripts/prompt_matrix.py

@@ -10,7 +10,7 @@ class PromptMatrixScript(scripts_manager.Script):
     def title(self):
         return "Prompt matrix"
 
-    def ui(self, is_img2img):
+    def ui(self, _is_img2img):
         with gr.Row():
             gr.HTML('<span">&nbsp Prompt matrix</span><br>')
         with gr.Row():

scripts/prompts_from_file.py

@@ -97,7 +97,7 @@ class PromptsFromFileScript(scripts_manager.Script):
     def title(self):
         return "Prompts from file"
 
-    def ui(self, is_img2img):
+    def ui(self, _is_img2img):
         with gr.Row():
             gr.HTML('<span">&nbsp Prompt from file</span><br>')
         with gr.Row():

scripts/sd_upscale.py

@@ -15,7 +15,7 @@ class SDUpscaleScript(scripts_manager.Script):
     def show(self, is_img2img):
         return is_img2img
 
-    def ui(self, is_img2img):
+    def ui(self, _is_img2img):
         with gr.Row():
             info = gr.HTML("<span>&nbsp SD Upscale</span><br>")
         with gr.Row():

scripts/skip_layer_guidance.py

@@ -15,7 +15,7 @@ class SLGScript(scripts_manager.Script):
     def title(self):
         return 'SLG: Skip Layer Guidance'
 
-    def show(self, is_img2img):
+    def show(self, _is_img2img):
         return True
 
     # return signature is array of gradio components

scripts/style_aligned_ext.py

@@ -16,7 +16,7 @@ class StyleAlignedScript(scripts_manager.Script):
     def title(self):
         return 'Style Aligned Image Generation'
 
-    def show(self, is_img2img):
+    def show(self, _is_img2img):
         return True
 
     def reset(self):

scripts/text2video.py

@@ -1,9 +1,6 @@
 """
 Additional params for Text-to-Video
 <https://huggingface.co/docs/diffusers/api/pipelines/text_to_video>
-
-TODO text2video items:
-- Video-to-Video upscaling: <https://huggingface.co/cerspense/zeroscope_v2_XL>, <https://huggingface.co/damo-vilab/MS-Vid2Vid-XL>
 """
 
 import gradio as gr

scripts/tiling.py

@@ -32,7 +32,7 @@ class TilingScript(scripts_manager.Script):
     def title(self):
         return 'Asymmetric Tiling'
 
-    def show(self, is_img2img):
+    def show(self, _is_img2img):
         return True
 
     def ui(self, _is_img2img): # ui elements

scripts/xyz_grid.py

@@ -25,6 +25,10 @@ debug = log.trace if os.environ.get('SD_XYZ_DEBUG', None) is not None else lambd
 class XYZGridScript(scripts_manager.Script):
     current_axis_options = []
 
+    def __init__(self):
+        super().__init__()
+        self.infotext_fields = ()
+
     def title(self):
         return "XYZ Grid Script"
 

scripts/xyz_grid_on.py

@@ -26,7 +26,11 @@ debug = log.trace if os.environ.get('SD_XYZ_DEBUG', None) is not None else lambd
 class XYZGridScript(scripts_manager.Script):
     current_axis_options = []
 
-    def show(self, is_img2img):
+    def __init__(self):
+        super().__init__()
+        self.infotext_fields = ()
+
+    def show(self, _is_img2img):
         return scripts_manager.AlwaysVisible
 
     def title(self):