lint pass

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

TODO.md

@@ -155,15 +155,20 @@ TODO: Investigate which models are diffusers-compatible and prioritize!
 > npm run todo
 
 ```code
-installer.py:642:15: W0511: TODO rocm: switch to pytorch source when it becomes available (fixme)
-modules/transformer_cache.py:29:61: W0511: TODO fc: autodetect tensor format based on model (fixme)
-modules/transformer_cache.py:30:50: W0511: TODO fc: autodetect distilled based on model (fixme)
-modules/processing_class.py:404:32: W0511: TODO processing: remove duplicate mask params (fixme)
-modules/sd_samplers_diffusers.py:355:31: W0511: TODO enso-required (fixme)
-modules/sd_models.py:1356:5: W0511: TODO model load: implement model in-memory caching (fixme)
-modules/ui_models_load.py:257:5: W0511: TODO loader: load receipe (fixme)
-modules/ui_models_load.py:264:5: W0511: TODO loader: save receipe (fixme)
-modules/sd_hijack_hypertile.py:123:17: W0511: TODO hypertile: vae breaks when using non-standard sizes (fixme)
-modules/sd_unet.py:77:39: W0511: TODO model load: force-reloading entire model as loading transformers only leads to massive memory usage (fixme)
-modules/modular_guiders.py:66:51: W0511: TODO: guiders (fixme)
+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_load.py:TODO lora: add t5 key support for sd35/f1
+modules/masking.py:TODO: additional masking algorithms
+modules/modular_guiders.py:TODO: guiders
+modules/processing_class.py:TODO processing: remove duplicate mask params
+modules/sd_hijack_hypertile.py:TODO hypertile: vae breaks when using non-standard sizes
+modules/sd_models.py:TODO model load: implement model in-memory caching
+modules/sd_samplers_diffusers.py:TODO enso-required
+modules/sd_unet.py:TODO model load: force-reloading entire model as loading transformers only leads to massive memory usage
+modules/transformer_cache.py:TODO fc: autodetect distilled based on model
+modules/transformer_cache.py:TODO fc: autodetect tensor format based on model
+modules/ui_models_load.py:TODO loader: load receipe
+modules/ui_models_load.py:TODO loader: save receipe
 ```

pipelines/hidream/qwen3_vl_transformers.py

@@ -1838,9 +1838,6 @@ class HiDreamO1Qwen3VLTransformer(Qwen3VLPreTrainedModel, GenerationMixin):
             The temporal, height and width of feature shape of each image in LLM.
         video_grid_thw (`torch.LongTensor` of shape `(num_videos, 3)`, *optional*):
             The temporal, height and width of feature shape of each video in LLM.
-
-        Example:
-            TODO: Add example
         """
         outputs = self.model(
             input_ids=input_ids,

pipelines/hidream/scheduler_flashfloweuler.py

@@ -366,7 +366,7 @@ class FlashFlowMatchEulerDiscreteScheduler(SchedulerMixin, ConfigMixin):
         """Constructs the noise schedule of Karras et al. (2022)."""
 
         # Hack to make sure that other schedulers which copy this function don't break
-        # TODO: Add this logic to the other schedulers
+        # Add this logic to the other schedulers
         if hasattr(self.config, "sigma_min"):
             sigma_min = self.config.sigma_min
         else:
@@ -392,7 +392,7 @@ class FlashFlowMatchEulerDiscreteScheduler(SchedulerMixin, ConfigMixin):
         """Constructs an exponential noise schedule."""
 
         # Hack to make sure that other schedulers which copy this function don't break
-        # TODO: Add this logic to the other schedulers
+        # Add this logic to the other schedulers
         if hasattr(self.config, "sigma_min"):
             sigma_min = self.config.sigma_min
         else:
@@ -416,7 +416,7 @@ class FlashFlowMatchEulerDiscreteScheduler(SchedulerMixin, ConfigMixin):
         """From "Beta Sampling is All You Need" [arXiv:2407.12173] (Lee et. al, 2024)"""
 
         # Hack to make sure that other schedulers which copy this function don't break
-        # TODO: Add this logic to the other schedulers
+        # Add this logic to the other schedulers
         if hasattr(self.config, "sigma_min"):
             sigma_min = self.config.sigma_min
         else:

pipelines/lumina_dimmo/lumina_dimoo.py

@@ -169,7 +169,7 @@ class ActivationCheckpointingStrategy(StrEnum):
 
 class LLaDAConfig(PretrainedConfig):
     model_type = "llada"
-    keys_to_ignore_at_inference = ["past_key_values"]  # TODO: confirm
+    keys_to_ignore_at_inference = ["past_key_values"]
 
     def __init__(self, use_cache: bool = False, **kwargs):
         model_config = ModelConfig()

pyproject.toml

@@ -413,7 +413,7 @@ exclude = [
     "pipelines/f_lite",
     "pipelines/bria",
     "pipelines/ernie",
-    "pipelines/flex2",   
+    "pipelines/flex2",
     "pipelines/anima",
     "pipelines/meissonic",
     "extensions-builtin/sd-extension-chainner/nodes",