Commit Graph

29 Commits

Author SHA1 Message Date
f3a36e7484 Temporarily disable auto enabling triton by default on AMD. (#14878)
I get freezing issues on my test machine.
2026-07-10 18:37:59 -07:00
1377a2f729 Only auto-enable the ROCm comfy-kitchen Triton backend on matrix-core GPUs (#14869)
#14862 auto-enables the comfy-kitchen Triton backend whenever torch.version.hip
is set and Triton >= 3.7. The INT8 matmul kernels compile tl.dot to matrix-core
instructions (WMMA on RDNA3+/gfx11xx-gfx12xx, MFMA on CDNA/gfx9xx); RDNA1/RDNA2
(gfx10xx) have neither, so the auto-enabled INT8 path hangs the GPU there
(reported on RDNA2 + triton-windows 3.7.1: native and custom-node INT8 freeze
until reset).

Gate the automatic ROCm default on GPU architecture as well as Triton version so
RDNA1/RDNA2 stay on the working eager fallback. Add --disable-triton-backend as
an explicit override; --enable-triton-backend still force-enables on any arch.
2026-07-10 03:31:20 -07:00
099522f85b Enable comfy-kitchen Triton backend by default on ROCm/AMD (#14862)
On AMD/ROCm the CUDA backend is unavailable, so Triton is the only accelerated
comfy-kitchen backend. It was disabled by default (opt-in --enable-triton-backend),
leaving AMD on the slow eager path. Enable it by default when torch.version.hip is
set AND Triton is >= 3.7 -- older Triton lacks libdevice.rint on the HIP backend and
hard-crashes the INT8 path, so on Triton < 3.7 it stays disabled with a log line.
NVIDIA behavior is unchanged; the explicit --enable-triton-backend flag still works
as an override.

Fixes #14861
2026-07-09 23:11:52 -04:00
73e84d5ec8 Support convrot int4 models. (#14859)
linear_dtype in comfy_quant metadata can be used to set if the int4 op does
the matrix multiplication in int8 or int4, the default is int4 on GPUs that
support it with fallback to int8 for GPUs that don't.
2026-07-09 18:57:09 -04:00
1a510f0423 Support int8 models. (#14636) 2026-06-25 11:23:58 -07:00
b138133ffa Enable triton comfy kitchen via cli-arg (#12730) 2026-05-03 14:07:21 -04:00
1c5db7397d feat: Support mxfp8 (#12907) 2026-03-14 18:36:29 -04:00
6165c38cb5 Optimize nvfp4 lora applying. (#11866)
This changes results a bit but it also speeds up things a lot.
2026-01-14 00:49:38 -05:00
b3c0e4de57 Make loras work on nvfp4 models. (#11837)
The initial applying is a bit slow but will probably be sped up in the
future.
2026-01-12 22:33:54 -05:00
21e8425087 Add warning for old pytorch. (#11718) 2026-01-07 21:07:26 -05:00
edee33f55e Disable comfy kitchen cuda if pytorch cuda less than 13 (#11681) 2026-01-06 22:13:43 -05:00
6da00dd899 Initial ops changes to use comfy_kitchen: Initial nvfp4 checkpoint support. (#11635)
---------

Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>
2026-01-05 21:48:58 -05:00
791e30ff50 Fix nan issue when quantizing fp16 tensor. (#11213) 2025-12-09 17:03:21 -05:00
43071e3de3 Make old scaled fp8 format use the new mixed quant ops system. (#11000) 2025-12-05 14:35:42 -05:00
6484ac89dc fix QuantizedTensor.is_contiguous (#10956) (#10959) 2025-11-28 16:33:07 -05:00
3f382a4f98 quant ops: Dequantize weight in-place (#10935)
In flux2 these weights are huge (200MB). As plain_tensor is a throw-away
deep copy, do this multiplication in-place to save VRAM.
2025-11-27 08:06:30 -08:00
bdb10a583f Fix loras not working on mixed fp8. (#10899) 2025-11-26 00:07:58 -05:00
015a0599d0 I found a case where this is needed (#10875) 2025-11-25 03:23:19 -05:00
b6805429b9 Allow pinning quantized tensors. (#10873) 2025-11-25 02:48:20 -05:00
25022e0b09 Cleanup and fix issues with text encoder quants. (#10872) 2025-11-25 01:48:53 -05:00
3b3ef9a77a Quantized Ops fixes (#10715)
* offload support, bug fixes, remove mixins

* add readme
2025-11-12 18:26:52 -05:00
af4b7b5edb More fp8 torch.compile regressions fixed. (#10625) 2025-11-03 22:14:20 -05:00
6b88478f9f Bring back fp8 torch compile performance to what it should be. (#10622) 2025-11-03 19:22:10 -05:00
e199c8cc67 Fixes (#10621) 2025-11-03 17:58:24 -05:00
958a17199a People should update their pytorch versions. (#10618) 2025-11-03 17:08:30 -05:00
c58c13b2ba Fix torch compile regression on fp8 ops. (#10580) 2025-11-01 00:25:17 -04:00
906c089957 Fix small performance regression with fp8 fast and scaled fp8. (#10537) 2025-10-29 19:29:01 -04:00
1a58087ac2 Reduce memory usage for fp8 scaled op. (#10531) 2025-10-29 15:43:51 -04:00
8817f8fc14 Mixed Precision Quantization System (#10498)
* Implement mixed precision operations with a registry design and metadate for quant spec in checkpoint.

* Updated design using Tensor Subclasses

* Fix FP8 MM

* An actually functional POC

* Remove CK reference and ensure correct compute dtype

* Update unit tests

* ruff lint

* Implement mixed precision operations with a registry design and metadate for quant spec in checkpoint.

* Updated design using Tensor Subclasses

* Fix FP8 MM

* An actually functional POC

* Remove CK reference and ensure correct compute dtype

* Update unit tests

* ruff lint

* Fix missing keys

* Rename quant dtype parameter

* Rename quant dtype parameter

* Fix unittests for CPU build
2025-10-28 16:20:53 -04:00