lint fixes

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

CHANGELOG.md

@@ -1,6 +1,18 @@
 # Change Log for SD.Next
 
-## Update for 2025-04-27
+## Highlights for 2025-04-28
+
+Another major release with *over 120 commits*!  
+Highlights include **Nunchaku** inference engine that allows running FLUX.1 3-5x higher performance!  
+And a new **FramePack** extension for high-quality *I2V* and *FLF2V* video generation with unlimited duration and limited VRAM!  
+
+What else?
+- New UI **History** tab  
+- New models: **Flex.2, LTXVideo-0.9.6, WAN-2.1-14B-FLF2V**, schedulers: **UniPC and LCM FlowMatch**, features: **CFGZero**  
+- Major updates to: **NNCF, OpenVINO, ROCm, ZLUDA**  
+- Cumulative fixes since last release  
+
+## Details for 2025-04-28
 
 - **Features**
   - [Nunchaku](https://github.com/mit-han-lab/nunchaku) inference engine with custom **SVDQuant** 4-bit execution  

TODO.md

@@ -24,22 +24,24 @@ N/A
 
 > pnpm lint | grep W0511 | awk -F'TODO ' '{print "- "$NF}' | sed 's/ (fixme)//g'
  
-- install: enable ROCm for windows when available
-- resize image: enable full VAE mode for resize-latent
-- infotext: handle using regex instead
-- fc: autodetect tensor format based on model
+- control: support scripts via api
 - fc: autodetect distilled based on model
-- processing: remove duplicate mask params
-- model loader: implement model in-memory caching
-- custom: load receipe
-- custom: save receipe
+- fc: autodetect tensor format based on model
+- hidream: pack latents for remote vae
 - hypertile: vae breaks when using non-standard sizes
-- model load: force-reloading entire model as loading transformers only leads to massive memory usage
+- infotext: handle using regex instead
+- install: enable ROCm for windows when available
+- loader: load receipe
+- loader: save receipe
 - lora: add other quantization types
 - lora: maybe force imediate quantization
-- modules/lora/lora_extract.py:185:9: W0511: TODO: lora support pre-quantized flux
-- control: support scripts via api
+- lora: add t5 key support for sd35/f16
+- lora: support pre-quantized flux
+- model load: force-reloading entire model as loading transformers only leads to massive memory usage
+- model loader: implement model in-memory caching
 - modernui: monkey-patch for missing tabs.select event
-- nunchaku: cache-dir for transformer and t5 loader
 - nunchaku: batch support
-- nunchaku: LoRA support
+- nunchaku: cache-dir for transformer and t5 loader
+- processing: remove duplicate mask params
+- resize image: enable full VAE mode for resize-latent
+  

modules/lora/lora_extract.py

@@ -182,7 +182,7 @@ def make_lora(fn, maxrank, auto_rank, rank_ratio, modules, overwrite):
             progress.remove_task(task)
         t3 = time.time()
 
-        # TODO: lora support pre-quantized flux
+        # 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:

modules/lora/lora_load.py

@@ -119,7 +119,7 @@ def load_safetensors(name, network_on_disk) -> Union[network.Network, None]:
             if key_network_without_network_parts.startswith("unet") or key_network_without_network_parts.startswith("transformer"):
                 key_network_without_network_parts = "lora_" + key_network_without_network_parts
             key_network_without_network_parts = key_network_without_network_parts.replace("clip_g","lora_te2").replace("clip_l","lora_te")
-            #TODO Add t5 key support for SD3.5/f1 here?
+            # TODO lora: add t5 key support for sd35/f1
 
         elif len(parts) > 5: # messy handler for diffusers peft lora
             key_network_without_network_parts = '_'.join(parts[:-2])
@@ -148,8 +148,7 @@ def load_safetensors(name, network_on_disk) -> Union[network.Network, None]:
             if net_module is not None:
                 network_types.append(nettype.__class__.__name__)
                 break
-            else:
-                module_errors += 1
+            module_errors += 1
         if net_module is None:
             if l.debug:
                 shared.log.error(f'LoRA unhandled: name={name} key={key} weights={weights.w.keys()}')

modules/sd_models_utils.py

@@ -7,7 +7,7 @@ from rich import progress # pylint: disable=redefined-builtin
 import torch
 import safetensors.torch
 
-from modules import paths, shared, devices, errors
+from modules import paths, shared, errors
 from modules.sd_checkpoint import CheckpointInfo, select_checkpoint, list_models, checkpoints_list, checkpoint_titles, get_closet_checkpoint_match, model_hash, update_model_hashes, setup_model, write_metadata, read_metadata_from_safetensors # pylint: disable=unused-import
 from modules.sd_offload import disable_offload, set_diffuser_offload, apply_balanced_offload, set_accelerate # pylint: disable=unused-import
 from modules.sd_models_legacy import get_checkpoint_state_dict, load_model_weights, load_model, repair_config # pylint: disable=unused-import

modules/shared.py

@@ -20,7 +20,7 @@ from modules.onnx_impl import execution_providers
 from modules.memstats import memory_stats, ram_stats # pylint: disable=unused-import
 from modules.interrogate.openclip import caption_models, caption_types, get_clip_models, refresh_clip_models, category_types
 from modules.interrogate.vqa import vlm_models, vlm_prompts, vlm_system
-from modules.ui_components import DropdownEditable, DropdownMulti
+from modules.ui_components import DropdownEditable
 from modules.options import OptionInfo
 import modules.memmon
 import modules.styles