cleanup todo

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

CHANGELOG.md

@@ -37,6 +37,8 @@
   - unnecessary secondary prompt if same
   - js fetch exception handling
   - detailer handling of stop/skip/pause
+  - cleanup dead rife code, thanks @Anai-Guo
+  - lumina-dimoo attention-kwargs, thanks @Anai-Guo
 
 ## Update for 2026-08-26
 

TODO.md

@@ -8,6 +8,7 @@
 - Benchmark tool productize: @CalamitousFelicitousness
 - Control tab verify overrides handling, @vladmandic
 - LTX: Create pre-quant for LTX-2.5
+- LTX: Implement LTX2DFRPipeline
 - ROCm: v10
 - Modular: cache hooks, @vladmandic
 - Modular: disable legacy PAG, etc., @vladmandic

installer.py

@@ -719,7 +719,7 @@ def install_rocm_zluda():
                 zluda_installer.load()
             except Exception as e:
                 log.error(f'Load ZLUDA: {e}')
-        else: # TODO rocm: switch to pytorch source when it becomes available
+        else:
             if device is None:
                 log.error('ROCm: no agent found - make sure that graphics driver is installed and up to date')
             if device is not None and device.therock is not None:

modules/lora/lora_load.py

@@ -107,7 +107,6 @@ def load_safetensors(name, network_on_disk: network.NetworkOnDisk) -> network.Ne
             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 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])

modules/masking.py

@@ -117,16 +117,6 @@ def fill(image, mask):
     return image_mod.convert("RGB")
 
 
-"""
-[docs](https://huggingface.co/docs/transformers/v4.36.1/en/model_doc/sam#overview)
-TODO: additional masking algorithms
-- PerSAM
-- REMBG
-- https://huggingface.co/docs/transformers/tasks/semantic_segmentation
-- transformers.pipeline.MaskGenerationPipeline: https://huggingface.co/models?pipeline_tag=mask-generation
-- transformers.pipeline.ImageSegmentationPipeline: https://huggingface.co/models?pipeline_tag=image-segmentation
-"""
-
 MODELS = {
     'None': None,
     'Facebook SAM ViT Base': 'facebook/sam-vit-base',

modules/postprocess/seedvr_model.py

@@ -340,9 +340,9 @@ class UpscalerSeedVR(Upscaler):
                 images=tensor,
                 cfg_scale=cfg_scale,
                 cfg_rescale=cfg_rescale,
-                steps=steps, # TODO SeedVR steps
-                batch_size=batch_size, # TODO SeedVR batch size
-                temporal_overlap=batch_overlap, # TODO SeedVR temporal overlap
+                steps=steps,
+                batch_size=batch_size,
+                temporal_overlap=batch_overlap,
                 seed=seed,
                 res_w=width,
                 device=devices.device,

modules/sd_models.py

@@ -1558,7 +1558,6 @@ def reload_model_weights(sd_model=None, info: CheckpointInfo | None = None, op='
         unload_model_weights(op=op)
         sd_model = None
     timer.load = timer.Timer()
-    # TODO model load: implement model in-memory caching
     timer.load.record("config")
     if sd_model is None or force:
         sd_model = None

modules/shared_defaults.py

@@ -55,7 +55,7 @@ def get_default_modes(cmd_opts, mem_stat):
         default_cross_attention = ['Dynamic attention']
 
     if devices.get_optimal_device_name() != "cpu":
-        os.environ.setdefault('SDNQ_USE_OPENVINO_MM', '0') # TODO sdnq openvino: this is too late as sdnq already initialized it
+        os.environ.setdefault('SDNQ_USE_OPENVINO_MM', '0')
 
     return (
         default_offload_mode,

modules/ui_definitions.py

@@ -90,6 +90,7 @@ def create_settings(cmd_opts):
 
         "advanced_sep": OptionInfo("<h2>Advanced Options</h2>", "", gr.HTML),
         "sd_checkpoint_autoload": OptionInfo(True, "Model auto-load on start"),
+        "model_modular_enable": OptionInfo(False, "Model convert to modular pipelines"),
         "sd_parallel_load": OptionInfo(True, "Model load using multiple threads"),
         "sd_checkpoint_autodownload": OptionInfo(True, "Model auto-download on demand"),
         "stream_load": OptionInfo(False, "Model load using streams", gr.Checkbox),
@@ -107,7 +108,6 @@ def create_settings(cmd_opts):
     # --- Model Options ---
     options_templates.update(options_section(('model_options', "Model Options"), {
         "model_modular_sep": OptionInfo("<h2>Modular Pipelines</h2>", "", gr.HTML),
-        "model_modular_enable": OptionInfo(False, "Enable modular pipelines (experimental)"),
         "model_google_sep": OptionInfo("<h2>Google GenAI</h2>", "", gr.HTML),
         "google_use_vertexai": OptionInfo(False, "Google cloud use VertexAI endpoints"),
         "google_api_key": OptionInfo("", "Google cloud API key", gr.Textbox, secret=True, env_var='GOOGLE_API_KEY'),