2207 Commits

Include renames

Author	SHA1	Message	Date
OctopusandGitHub	cc6f9500a1	fix: use Parameter assignment for Stable_Zero123 cc_projection weights (fixes #13492) (#13518) ... On Windows with aimdo enabled, disable_weight_init.Linear uses lazy initialization that sets weight and bias to None to avoid unnecessary memory allocation. This caused a crash when copy_() was called on the None weight attribute in Stable_Zero123.__init__. Replace copy_() with direct torch.nn.Parameter assignment, which works correctly on both Windows (aimdo enabled) and other platforms.	2026-04-22 15:05:43 -07:00
Jukka SeppänenandGitHub	eb22225387	Support standalone LTXV audio VAEs (#13499)	2026-04-21 10:46:37 -07:00
comfyanonymousandGitHub	ad94d47221	Make the ltx audio vae more native. (#13486)	2026-04-21 11:02:42 -04:00
comfyanonymousandGitHub	3d816db07f	Some optimizations to make Ernie inference a bit faster. (#13472)	2026-04-18 23:02:29 -04:00
Jukka SeppänenandGitHub	b9dedea57d	feat: SUPIR model support (CORE-17) (#13250)	2026-04-18 23:02:01 -04:00
BedovyyandGitHub	b41ab53b6f	Use ErnieTEModel_ not ErnieTEModel. (#13431)	2026-04-16 10:11:58 -04:00
Jun YamogandGitHub	1de83f91c3	Fix OOM regression in _apply() for quantized models during inference (#13372) ... Skip unnecessary clone of inference-mode tensors when already inside torch.inference_mode(), matching the existing guard in set_attr_param. The unconditional clone introduced in 20561aa9 caused transient VRAM doubling during model movement for FP8/quantized models.	2026-04-15 02:10:36 -07:00
comfyanonymousandGitHub	cb0bbde402	Fix ernie on devices that don't support fp64. (#13414)	2026-04-14 22:54:47 -04:00
comfyanonymousandGitHub	722bc73319	Make text generation work with ministral model. (#13395) ... Needs template before it works properly.	2026-04-13 20:43:57 -04:00
comfyanonymousandGitHub	402ff1cdb7	Fix issue with ernie image. (#13393)	2026-04-13 16:38:42 -04:00
comfyanonymousandGitHub	c2657d5fb9	Fix typo. (#13382)	2026-04-12 23:37:13 -04:00
comfyanonymousandGitHub	31283d2892	Implement Ernie Image model. (#13369)	2026-04-11 22:29:31 -04:00
comfyanonymousandGitHub	55ebd287ee	Add a supports_fp64 function. (#13368)	2026-04-11 21:06:36 -04:00
Jukka SeppänenandGitHub	a134423890	SDPose: resize input always (#13349)	2026-04-10 11:26:55 -10:00
hueminandGitHub	b615af1c65	Add support for small flux.2 decoder (#13314)	2026-04-07 03:44:18 -04:00
comfyanonymousandGitHub	40862c0776	Support Ace Step 1.5 XL model. (#13317)	2026-04-07 03:13:47 -04:00
comfyanonymousandGitHub	0c63b4f6e3	Remove dead code. (#13251)	2026-04-01 20:22:06 -04:00
comfyanonymousandGitHub	e2ddf28d78	Fix some fp8 scaled checkpoints no longer working. (#13239)	2026-03-31 14:27:17 -07:00
rattusandGitHub	8d723d2caa	Fix/tweak pinned memory accounting (#13221) ... * mm: Lower windows pin threshold Some workflows have more extranous use of shared GPU memory than is accounted for in the 5% pin headroom. Lower this for safety. * mm: Remove pin count clearing threshold. TOTAL_PINNED_MEMORY is shared between the legacy and aimdo pinning systems, however this catch-all assumes only the legacy system exists. Remove the catch-all as the PINNED_MEMORY buffer is coherent already.	2026-03-29 16:43:24 -07:00
Jukka SeppänenandGitHub	a500f1edac	CORE-13 feat: Support RT-DETRv4 detection model (#12748)	2026-03-28 23:34:10 -04:00
comfyanonymousandGitHub	3f77450ef1	Fix #13214 (#13216)	2026-03-28 22:35:59 -04:00
rattusandGitHub	b353a7c863	Integrate RAM cache with model RAM management (#13173)	2026-03-27 21:34:16 -04:00
comfyanonymousandGitHub	3a56201da5	Allow flux conditioning without a pooled output. (#13198)	2026-03-27 20:36:26 -04:00
Jukka SeppänenandGitHub	b0fd65e884	fix: regression in text generate with LTXAV model (#13170)	2026-03-26 09:55:05 -07:00
comfyanonymousandGitHub	2a1f402601	Make Qwen 8B work with TextGenerate node. (#13160)	2026-03-25 23:21:44 -04:00
Jukka SeppänenandGitHub	404d7b9978	feat: Support Qwen3.5 text generation models (#12771)	2026-03-25 22:48:28 -04:00
Kohaku-BlueleafandGitHub	5ebb0c2e0b	FP8 bwd training (#13121)	2026-03-24 20:39:04 -04:00
Jukka SeppänenandGitHub	e87858e974	feat: LTX2: Support reference audio (ID-LoRA) (#13111)	2026-03-23 18:22:24 -04:00
TalmajandGitHub	d49420b3c7	LongCat-Image edit (#13003)	2026-03-21 23:51:05 -04:00
rattusandGitHub	25b6d1d629	wan: vae: Fix light/color change (#13101) ... There was an issue where the resample split was too early and dropped one of the rolling convolutions a frame early. This is most noticable as a lighting/color change between pixel frames 5->6 (latent 2->3), or as a lighting change between the first and last frame in an FLF wan flow.	2026-03-21 18:44:35 -04:00
comfyanonymousandGitHub	11c15d8832	Fix fp16 intermediates giving different results. (#13100)	2026-03-21 17:53:25 -04:00
comfyanonymousandGitHub	b5d32e6ad2	Fix sampling issue with fp16 intermediates. (#13099)	2026-03-21 17:47:42 -04:00
Jedrzej KosinskiandGitHub	87cda1fc25	Move inline comfy.context_windows imports to top-level in model_base.py (#13083) ... The recent PR that added resize_cond_for_context_window methods to model classes used inline 'import comfy.context_windows' in each method body. This moves that import to the top-level import section, replacing 4 duplicate inline imports with a single top-level one.	2026-03-20 20:03:42 -04:00
drozbayandGitHub	589228e671	Add slice_cond and per-model context window cond resizing (#12645) ... * Add slice_cond and per-model context window cond resizing * Fix cond_value.size() call in context window cond resizing * Expose additional advanced inputs for ContextWindowsManualNode Necessary for WanAnimate context windows workflow, which needs cond_retain_index_list = 0 to work properly with its reference input. ---------	2026-03-19 20:42:42 -07:00
rattusandGitHub	f49856af57	ltx: vae: Fix missing init variable (#13074) ... Forgot to push this ammendment. Previous test results apply to this.	2026-03-19 22:34:58 -04:00
rattusandGitHub	82b868a45a	Fix VRAM leak in tiler fallback in video VAEs (#13073) ... * sd: soft_empty_cache on tiler fallback This doesnt cost a lot and creates the expected VRAM reduction in resource monitors when you fallback to tiler. * wan: vae: Don't recursion in local fns (move run_up) Moved Decoder3d’s recursive run_up out of forward into a class method to avoid nested closure self-reference cycles. This avoids cyclic garbage that delays garbage of tensors which in turn delays VRAM release before tiled fallback. * ltx: vae: Don't recursion in local fns (move run_up) Mov the recursive run_up out of forward into a class method to avoid nested closure self-reference cycles. This avoids cyclic garbage that delays garbage of tensors which in turn delays VRAM release before tiled fallback.	2026-03-19 22:30:27 -04:00
comfyanonymousandGitHub	8458ae2686	Revert "fix: run text encoders on MPS GPU instead of CPU for Apple Silicon (#…" (#13070) ... This reverts commit b941913f1d.	2026-03-19 15:27:55 -04:00
Jukka SeppänenandGitHub	fd0261d2bc	Reduce tiled decode peak memory (#13050)	2026-03-19 13:29:34 -04:00
rattusandGitHub	ab14541ef7	memory: Add more exclusion criteria to pinned read (#13067)	2026-03-19 10:03:20 -07:00
rattusandGitHub	fabed694a2	ltx: vae: implement chunked encoder + CPU IO chunking (Big VRAM reductions) (#13062) ... * ltx: vae: add cache state to downsample block * ltx: vae: Add time stride awareness to causal_conv_3d * ltx: vae: Automate truncation for encoder Other VAEs just truncate without error. Do the same. * sd/ltx: Make chunked_io a flag in its own right Taking this bi-direcitonal, so make it a for-purpose named flag. * ltx: vae: implement chunked encoder + CPU IO chunking People are doing things with big frame counts in LTX including V2V flows. Implement the time-chunked encoder to keep the VRAM down, with the converse of the new CPU pre-allocation technique, where the chunks are brought from the CPU JIT. * ltx: vae-encode: round chunk sizes more strictly Only powers of 2 and multiple of 8 are valid due to cache slicing.	2026-03-19 09:58:47 -07:00
comfyanonymousandGitHub	f6b869d7d3	fp16 intermediates doen't work for some text enc models. (#13056)	2026-03-18 19:42:28 -04:00
comfyanonymousandGitHub	56ff88f951	Fix regression. (#13053)	2026-03-18 18:35:25 -04:00
Jukka SeppänenandGitHub	9fff091f35	Further Reduce LTX VAE decode peak RAM usage (#13052)	2026-03-18 18:32:26 -04:00
comfyanonymousandGitHub	dcd659590f	Make more intermediate values follow the intermediate dtype. (#13051)	2026-03-18 18:14:18 -04:00
Anton BukovandGitHub	b941913f1d	fix: run text encoders on MPS GPU instead of CPU for Apple Silicon (#12809) ... On Apple Silicon, `vram_state` is set to `VRAMState.SHARED` because CPU and GPU share unified memory. However, `text_encoder_device()` only checked for `HIGH_VRAM` and `NORMAL_VRAM`, causing all text encoders to fall back to CPU on MPS devices. Adding `VRAMState.SHARED` to the condition allows non-quantized text encoders (e.g. bf16 Gemma 3 12B) to run on the MPS GPU, providing significant speedup for text encoding and prompt generation. Note: quantized models (fp4/fp8) that use float8_e4m3fn internally will still fall back to CPU via the `supports_cast()` check in `CLIP.__init__()`, since MPS does not support fp8 dtypes.	2026-03-17 21:21:32 -04:00
rattusandGitHub	cad24ce262	cascade: remove dead weight init code (#13026) ... This weight init process is fully shadowed be the weight load and doesnt work in dynamic_vram were the weight allocation is deferred.	2026-03-17 20:59:10 -04:00
comfyanonymousandGitHub	68d542cc06	Fix case where pixel space VAE could cause issues. (#13030)	2026-03-17 20:46:22 -04:00
Jukka SeppänenandGitHub	735a0465e5	Inplace VAE output processing to reduce peak RAM consumption. (#13028)	2026-03-17 20:20:49 -04:00
rattusandGitHub	035414ede4	Reduce WAN VAE VRAM, Save use cases for OOM/Tiler (#13014) ... * wan: vae: encoder: Add feature cache layer that corks singles If a downsample only gives you a single frame, save it to the feature cache and return nothing to the top level. This increases the efficiency of cacheability, but also prepares support for going two by two rather than four by four on the frames. * wan: remove all concatentation with the feature cache The loopers are now responsible for ensuring that non-final frames are processes at least two-by-two, elimiating the need for this cat case. * wan: vae: recurse and chunk for 2+2 frames on decode Avoid having to clone off slices of 4 frame chunks and reduce the size of the big 6 frame convolutions down to 4. Save the VRAMs. * wan: encode frames 2x2. Reduce VRAM usage greatly by encoding frames 2 at a time rather than 4. * wan: vae: remove cloning The loopers now control the chunking such there is noever more than 2 frames, so just cache these slices directly and avoid the clone allocations completely. * wan: vae: free consumer caller tensors on recursion * wan: vae: restyle a little to match LTX	2026-03-17 17:34:39 -04:00
rattusandGitHub	1a157e1f97	Reduce LTX VAE VRAM usage and save use cases from OOMs/Tiler (#13013) ... * ltx: vae: scale the chunk size with the users VRAM Scale this linearly down for users with low VRAM. * ltx: vae: free non-chunking recursive intermediates * ltx: vae: cleanup some intermediates The conv layer can be the VRAM peak and it does a torch.cat. So cleanup the pieces of the cat. Also clear our the cache ASAP as each layer detect its end as this VAE surges in VRAM at the end due to the ended padding increasing the size of the final frame convolutions off-the-books to the chunker. So if all the earlier layers free up their cache it can offset that surge. Its a fragmentation nightmare, and the chance of it having to recache the pyt allocator is very high, but you wont OOM.	2026-03-17 17:32:43 -04:00