bugfix: fix typo in apply_directory for custom_nodes_directory
allow for PATH style ';' delimited custom_node directories.
change delimiter type for seperate folders per platform.
feat(API-nodes): move Rodin3D nodes to new client; removed old api client.py (#10645)
Fix qwen controlnet regression. (#10657)
Enable pinned memory by default on Nvidia. (#10656)
Removed the --fast pinned_memory flag.
You can use --disable-pinned-memory to disable it. Please report if it
causes any issues.
Pinned mem also seems to work on AMD. (#10658)
Remove environment variable.
Removed environment variable fallback for custom nodes directory.
Update documentation for custom nodes directory
Clarified documentation on custom nodes directory argument, removed documentation on environment variable
Clarify release cycle. (#10667)
Tell users they need to upload their logs in bug reports. (#10671)
mm: guard against double pin and unpin explicitly (#10672)
As commented, if you let cuda be the one to detect double pin/unpinning
it actually creates an asyc GPU error.
Only unpin tensor if it was pinned by ComfyUI (#10677)
Make ScaleROPE node work on Flux. (#10686)
Add logging for model unloading. (#10692)
Unload weights if vram usage goes up between runs. (#10690)
ops: Put weight cast on the offload stream (#10697)
This needs to be on the offload stream. This reproduced a black screen
with low resolution images on a slow bus when using FP8.
Update CI workflow to remove dead macOS runner. (#10704)
* Update CI workflow to remove dead macOS runner.
* revert
* revert
Don't pin tensor if not a torch.nn.parameter.Parameter (#10718)
Update README.md for Intel Arc GPU installation, remove IPEX (#10729)
IPEX is no longer needed for Intel Arc GPUs. Removing instruction to setup ipex.
mm/mp: always unload re-used but modified models (#10724)
The partial unloader path in model re-use flow skips straight to the
actual unload without any check of the patching UUID. This means that
if you do an upscale flow with a model patch on an existing model, it
will not apply your patchings.
Fix by delaying the partial_unload until after the uuid checks. This
is done by making partial_unload a model of partial_load where extra_mem
is -ve.
qwen: reduce VRAM usage (#10725)
Clean up a bunch of stacked and no-longer-needed tensors on the QWEN
VRAM peak (currently FFN).
With this I go from OOMing at B=37x1328x1328 to being able to
succesfully run B=47 (RTX5090).
Update Python 3.14 compatibility notes in README (#10730)
Quantized Ops fixes (#10715)
* offload support, bug fixes, remove mixins
* add readme
add PR template for API-Nodes (#10736)
feat: add create_time dict to prompt field in /history and /queue (#10741)
flux: reduce VRAM usage (#10737)
Cleanup a bunch of stack tensors on Flux. This take me from B=19 to B=22
for 1600x1600 on RTX5090.
Better instructions for the portable. (#10743)
Use same code for chroma and flux blocks so that optimizations are shared. (#10746)
Fix custom nodes import error. (#10747)
This should fix the import errors but will break if the custom nodes actually try to use the class.
revert import reordering
revert imports pt 2
Add left padding support to tokenizers. (#10753)
chore(api-nodes): mark OpenAIDalle2 and OpenAIDalle3 nodes as deprecated (#10757)
Revert "chore(api-nodes): mark OpenAIDalle2 and OpenAIDalle3 nodes as deprecated (#10757)" (#10759)
This reverts commit 9a02382568.
Change ROCm nightly install command to 7.1 (#10764)
* Initial Chroma Radiance support
* Minor Chroma Radiance cleanups
* Update Radiance nodes to ensure latents/images are on the intermediate device
* Fix Chroma Radiance memory estimation.
* Increase Chroma Radiance memory usage factor
* Increase Chroma Radiance memory usage factor once again
* Ensure images are multiples of 16 for Chroma Radiance
Add batch dimension and fix channels when necessary in ChromaRadianceImageToLatent node
* Tile Chroma Radiance NeRF to reduce memory consumption, update memory usage factor
* Update Radiance to support conv nerf final head type.
* Allow setting NeRF embedder dtype for Radiance
Bump Radiance nerf tile size to 32
Support EasyCache/LazyCache on Radiance (maybe)
* Add ChromaRadianceStubVAE node
* Crop Radiance image inputs to multiples of 16 instead of erroring to be in line with existing VAE behavior
* Convert Chroma Radiance nodes to V3 schema.
* Add ChromaRadianceOptions node and backend support.
Cleanups/refactoring to reduce code duplication with Chroma.
* Fix overriding the NeRF embedder dtype for Chroma Radiance
* Minor Chroma Radiance cleanups
* Move Chroma Radiance to its own directory in ldm
Minor code cleanups and tooltip improvements
* Fix Chroma Radiance embedder dtype overriding
* Remove Radiance dynamic nerf_embedder dtype override feature
* Unbork Radiance NeRF embedder init
* Remove Chroma Radiance image conversion and stub VAE nodes
Add a chroma_radiance option to the VAELoader builtin node which uses comfy.sd.PixelspaceConversionVAE
Add a PixelspaceConversionVAE to comfy.sd for converting BHWC 0..1 <-> BCHW -1..1
* Looking into a @wrap_attn decorator to look for 'optimized_attention_override' entry in transformer_options
* Created logging code for this branch so that it can be used to track down all the code paths where transformer_options would need to be added
* Fix memory usage issue with inspect
* Made WAN attention receive transformer_options, test node added to wan to test out attention override later
* Added **kwargs to all attention functions so transformer_options could potentially be passed through
* Make sure wrap_attn doesn't make itself recurse infinitely, attempt to load SageAttention and FlashAttention if not enabled so that they can be marked as available or not, create registry for available attention
* Turn off attention logging for now, make AttentionOverrideTestNode have a dropdown with available attention (this is a test node only)
* Make flux work with optimized_attention_override
* Add logs to verify optimized_attention_override is passed all the way into attention function
* Make Qwen work with optimized_attention_override
* Made hidream work with optimized_attention_override
* Made wan patches_replace work with optimized_attention_override
* Made SD3 work with optimized_attention_override
* Made HunyuanVideo work with optimized_attention_override
* Made Mochi work with optimized_attention_override
* Made LTX work with optimized_attention_override
* Made StableAudio work with optimized_attention_override
* Made optimized_attention_override work with ACE Step
* Made Hunyuan3D work with optimized_attention_override
* Make CosmosPredict2 work with optimized_attention_override
* Made CosmosVideo work with optimized_attention_override
* Made Omnigen 2 work with optimized_attention_override
* Made StableCascade work with optimized_attention_override
* Made AuraFlow work with optimized_attention_override
* Made Lumina work with optimized_attention_override
* Made Chroma work with optimized_attention_override
* Made SVD work with optimized_attention_override
* Fix WanI2VCrossAttention so that it expects to receive transformer_options
* Fixed Wan2.1 Fun Camera transformer_options passthrough
* Fixed WAN 2.1 VACE transformer_options passthrough
* Add optimized to get_attention_function
* Disable attention logs for now
* Remove attention logging code
* Remove _register_core_attention_functions, as we wouldn't want someone to call that, just in case
* Satisfy ruff
* Remove AttentionOverrideTest node, that's something to cook up for later
* Attempting a universal implementation of EasyCache, starting with flux as test; I screwed up the math a bit, but when I set it just right it works.
* Fixed math to make threshold work as expected, refactored code to use EasyCacheHolder instead of a dict wrapped by object
* Use sigmas from transformer_options instead of timesteps to be compatible with a greater amount of models, make end_percent work
* Make log statement when not skipping useful, preparing for per-cond caching
* Added DIFFUSION_MODEL wrapper around forward function for wan model
* Add subsampling for heuristic inputs
* Add subsampling to output_prev (output_prev_subsampled now)
* Properly consider conds in EasyCache logic
* Created SuperEasyCache to test what happens if caching and reuse is moved outside the scope of conds, added PREDICT_NOISE wrapper to facilitate this test
* Change max reuse_threshold to 3.0
* Mark EasyCache/SuperEasyCache as experimental (beta)
* Make Lumina2 compatible with EasyCache
* Add EasyCache support for Qwen Image
* Fix missing comma, curse you Cursor
* Add EasyCache support to AceStep
* Add EasyCache support to Chroma
* Added EasyCache support to Cosmos Predict t2i
* Make EasyCache not crash with Cosmos Predict ImagToVideo latents, but does not work well at all
* Add EasyCache support to hidream
* Added EasyCache support to hunyuan video
* Added EasyCache support to hunyuan3d
* Added EasyCache support to LTXV (not very good, but does not crash)
* Implemented EasyCache for aura_flow
* Renamed SuperEasyCache to LazyCache, hardcoded subsample_factor to 8 on nodes
* Eatra logging when verbose is true for EasyCache
* Upload files for Chroma Implementation
* Remove trailing whitespace
* trim more trailing whitespace..oops
* remove unused imports
* Add supported_inference_dtypes
* Set min_length to 0 and remove attention_mask=True
* Set min_length to 1
* get_mdulations added from blepping and minor changes
* Add lora conversion if statement in lora.py
* Update supported_models.py
* update model_base.py
* add uptream commits
* set modelType.FLOW, will cause beta scheduler to work properly
* Adjust memory usage factor and remove unnecessary code
* fix mistake
* reduce code duplication
* remove unused imports
* refactor for upstream sync
* sync chroma-support with upstream via syncbranch patch
* Update sd.py
* Add Chroma as option for the OptimalStepsScheduler node
