Introduce a two-stage Docker build that compiles SageAttention 2.2/2++ from the upstream repository using Debian’s CUDA toolkit (nvcc) and the same Torch stack (cu129) as the runtime, then installs the produced wheel in the final slim image. This ensures the sageattention module is present at launch and makes the existing --use-sage-attention flag functional. The runtime image remains minimal while the builder stage carries heavy toolchains; matching Torch across stages prevents CUDA/ABI mismatch. Also retains the previous launch command so ComfyUI auto-enables SageAttention on startup.
Update README to reflect that SageAttention 2.2/2++ is compiled into the
image at build time and enabled automatically on launch using
--use-sage-attention. Clarifies NVIDIA GPU setup expectations and that no
extra steps are required to activate SageAttention in container runs.
Changes:
- Features: add “SageAttention 2.2 baked in” and “Auto-enabled at launch”.
- Getting Started: note that SageAttention is compiled during docker build
and requires no manual install.
- Docker Compose: confirm the image launches with SageAttention enabled by default.
- Usage: add a SageAttention subsection with startup log verification notes.
- General cleanup and wording to align with current image behavior.
No functional code changes; documentation only.
Adds a multi-stage Docker build that compiles SageAttention 2.2/2++ from the upstream repository head into a wheel using nvcc, then installs it into the slim runtime to keep images small. Ensures the builder installs the same Torch CUDA 12.9 stack as the runtime so the compiled extension ABI matches at load time. Shallow clones the SageAttention repo during build to always pull the latest version on each new image build. Updates the container launch to pass --use-sage-attention so ComfyUI enables SageAttention at startup when the package is present. This change keeps the runtime minimal while delivering up-to-date, high-performance attention kernels for modern NVIDIA GPUs in ComfyUI.
Introduce a run() helper that shell-quotes and prints each command before execution, and use it for mkdir/chown/chmod in the /usr/local-only Python target loop. This makes permission and path fixes visible in logs for easier debugging, preserves existing error-tolerance with || true, and remains compatible with set -euo pipefail and the runuser re-exec (runs only in the root branch). No functional changes beyond added verbosity; non-/usr/local paths remain no-op.
This updates ComfyUI-Manager on container launch using a shallow fetch/reset pattern and cleans untracked files to ensure a fresh working tree, which is the recommended way to refresh depth‑1 clones without full history. It also installs all detected requirements.txt files with pip --upgrade and only-if-needed strategy so direct requirements are upgraded within constraints on each run, while still excluding Manager from wheel-builds to avoid setuptools flat‑layout errors.
This adds av>=14.2 to satisfy Comfy’s API-node canary, ensuring video/audio nodes import without error, and uses the standard PyTorch CUDA 12.9 index URL syntax for reliability. It also installs nvidia-ml-py to align with the ecosystem shift away from deprecated pynvml, reducing future NVML warnings while preserving current functionality. The rest of the base remains unchanged, and existing ComfyUI requirements continue to install as before.
Update the Dockerfile to use python:3.12.11-slim-trixie to align with available cp312 wheels (notably MediaPipe) and avoid 3.13 ABI gaps, add cmake alongside build-essential to support native builds like dlib, keep the CUDA-enabled PyTorch install via the vendor index, and leave user/workdir/entrypoint/port settings unchanged to preserve runtime behavior.
* 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
