From 84d1d3ad8038acf7a05d1f2c02f3ca5e62490cf2 Mon Sep 17 00:00:00 2001 From: Vladimir Mandic Date: Wed, 13 May 2026 10:19:51 +0200 Subject: [PATCH] lint pass Signed-off-by: Vladimir Mandic --- TODO.md | 27 +++++++++++-------- pipelines/hidream/qwen3_vl_transformers.py | 3 --- pipelines/hidream/scheduler_flashfloweuler.py | 6 ++--- pipelines/lumina_dimmo/lumina_dimoo.py | 2 +- pyproject.toml | 2 +- 5 files changed, 21 insertions(+), 19 deletions(-) diff --git a/TODO.md b/TODO.md index e71721286..dbc4230e5 100644 --- a/TODO.md +++ b/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 ``` diff --git a/pipelines/hidream/qwen3_vl_transformers.py b/pipelines/hidream/qwen3_vl_transformers.py index f0d1d1074..1abd7557f 100644 --- a/pipelines/hidream/qwen3_vl_transformers.py +++ b/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, diff --git a/pipelines/hidream/scheduler_flashfloweuler.py b/pipelines/hidream/scheduler_flashfloweuler.py index 97b7fa16a..c3fbe15b9 100644 --- a/pipelines/hidream/scheduler_flashfloweuler.py +++ b/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: diff --git a/pipelines/lumina_dimmo/lumina_dimoo.py b/pipelines/lumina_dimmo/lumina_dimoo.py index 25e728998..649e34d0a 100644 --- a/pipelines/lumina_dimmo/lumina_dimoo.py +++ b/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() diff --git a/pyproject.toml b/pyproject.toml index 3f27c7909..6266072d1 100644 --- a/pyproject.toml +++ b/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",