- ROCMSamplerCustomAdvanced: V3 ComfyNode drop-in for stock SamplerCustomAdvanced
with architecture detection, ROCm backend tuning, memory defrag for high-memory
models (LTX 128ch), enhanced per-step callback with ETA
- ROCMSamplerCustomAdvancedBenchmark: A/B comparison node for stock vs ROCm
- docs/SAMPLER_CUSTOM_ADVANCED.md: full documentation for agents and users
- Category: ROCm Ninodes/Sampling
- Bump version to 2.2.0 across all files
- LTX Video VAE detection (128 channels, 32x spatial compression, 8x temporal)
- z-image / z-image-turbo pixel-space VAE passthrough (no decode needed)
- fp16 default on all AMD GPUs (Strix Halo, RDNA 2/3, CDNA)
- Per-architecture tuning with automatic detection (gfx1151/gfx1100/gfx1030/CDNA)
- Temporal tiling for long videos: overlapping chunks with linear blend,
zero frame loss, progress bar in UI (disabled by default)
- Chunked IO bypass for LTX — fixes OOM with max_split_size_mb caps
- Fixed memory estimation: correct for all dims (including 5D temporal) and dtypes
- APU-aware memory management (psutil for unified memory on Strix Halo)
- Tile size floor for high-compression VAEs (min 64 latent pixels)
- 25 unit tests covering all new features
- Added full on-the-fly dequantization for GGUF models (Q8_0, Q4_0, Q4_1, Q5_0, Q5_1, BF16)
- Implemented get_weight() and cast_bias_weight() methods for proper tensor handling
- Fixed 'Multiple dispatch failed for torch.nn.linear' error by converting all ROCmGGMLTensor objects to regular tensors
- Added forward_comfy_cast_weights() routing for all ROCmGGMLTensor objects (quantized and non-quantized)
- Based on City96's ComfyUI-GGUF implementation, optimized for ROCm/gfx1151
- Added LoRA patch support and VRAM estimation
- All GGUF models now work correctly for loading and sampling
- Fixed file listing issue: now checks multiple folder names (diffusion_models, unet, unet_gguf)
- Fixed PyTorch 2.0+ GGUF loading: patches torch.load to set weights_only=False for GGUF files
- Removed all Unicode emojis: replaced with ASCII prefixes [INFO], [WARNING], [ERROR], etc.
- Improved cross-platform compatibility for Windows console
Issues reported by u/x5nder on Reddit - thank you for the bug reports!
Version bump: 2.0.5 -> 2.0.6
- Fixed UnicodeEncodeError when printing emoji characters on Windows
- Windows console (cp1252) cannot display emoji characters like ✅, ❌, ⚠️
- Added safe_print() function with automatic ASCII fallbacks for Windows
- Emojis are replaced with [OK], [ERROR], [WARNING] on incompatible encodings
- All print statements in install.py now use safe_print() for cross-platform compatibility
Issue reported by u/x5nder on Reddit - thank you for finding this bug!
Version bump: 2.0.4 -> 2.0.5
- Fixed ROCm Diffusion Model loader to accept .gguf, .ckpt, .pt, .pth, .bin, and .onnx files
- Previously only accepted .safetensors files due to ComfyUI's default filter
- Added custom file scanner that supports all common model formats
- Falls back to ComfyUI's default if custom scanning fails
Issue reported by u/x5nder on Reddit - thank you for finding this bug!
Version bump: 2.0.3 -> 2.0.4
- Added reliable WAN VAE detection using isinstance() with imported classes
- Added fallback detection using latent_channels (16 for WAN 2.1, 48 for WAN 2.2)
- Disabled chunking for WAN VAEs to preserve causal decoding chain with feature caching
- Matched native ComfyUI behavior exactly for WAN VAE video processing
- Fixed detection logic to use correct file (rocm_nodes/core/vae.py)
- Applied ROCm backend optimizations to video processing
- Added async memory cleanup for WAN VAE videos
- Added gfx1151 architecture detection and logging
- Updated version to 2.0.1 across all files
- Optimized for mature ROCm drivers and libraries
- Added TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL=1 for better performance
- Replaced aggressive memory management with gentle cleanup
- Updated memory allocation settings (256MB chunks, 0.8 threshold)
- Removed performance-penalizing functions and complex memory management
- Cleaned up development files and test workflows
- Enhanced README with clear explanation of what we do and how we do it
- Maintained 9 optimized nodes with gentle memory management
- Fixed free memory calculation to use reserved_memory instead of allocated_memory
- Added accurate memory monitoring with both allocated and reserved memory display
- Implemented dynamic memory fraction calculation based on actual available memory
- Added helper functions for consistent memory management across all samplers
- Improved OOM prevention with more accurate memory thresholds
- Enhanced memory cleanup with aggressive cache clearing and garbage collection
- Fixed memory calculation consistency between regular and advanced KSamplers
- Added detailed progress indicators to reduce perceived idle time
- Optimized memory management for video processing workflows
- Added video-specific progress feedback and status messages
- Improved fallback handling with better error reporting
- Enhanced completion feedback for better user experience
- Fixed idle time issues in video_wan2_2_14B_s2v workflow
- Iterate version to 1.0.19 for node publication
- Document repository cleanup and merge conflict resolution
- Repository now in clean, publishable state
- Fixed version consistency between package.json and comfyui version
- Incremented from v1.0.17 base to v1.0.18 with VAE decode fix
- Both main version and comfyui version now properly set to 1.0.18
- Fixed out_channels parameter from vae.latent_channels (16) to 3 (RGB) in tiled decoding
- Resolves 'The size of tensor a (16) must match the size of tensor b (3)' error
- Fixes VAE decode failures when processing images with tiled decoding
- Applied fix to current codebase structure
- Add progress indicators for Windows users experiencing 6-minute hang
- Add conservative memory allocation for Windows stability
- Add completion messages for better user feedback
- Maintain all ROCm optimizations for AMD GPU performance
- Fix WAN VAE frame duplication issue
- Ready for publication
- Fixed 'Input type (float) and bias type (c10::BFloat16) should be the same' error
- Added smart precision detection to match VAE model dtype
- Added explicit BFloat16 to Float32 conversion when needed
- Enhanced model conversion logic with proper logging
- Updated version to 1.0.16
This fix ensures VAE model and input tensors always have matching dtypes,
preventing PyTorch type mismatch errors while maintaining ROCm optimizations.
- Restored v1.0.13 with all 9 working nodes (ROCMOptimizedCheckpointLoader, ROCMOptimizedKSampler, etc.)
- Implemented comprehensive debug flag system (ROCM_NINODES_DEBUG=1)
- Created complete test suite with performance and correctness tests
- Added data capture infrastructure for real workflow testing
- Built standalone test runner with mock data support
- Created ComfyUI integration tests for Flux and WAN workflows
- Added comprehensive documentation (ARCHITECTURE.md, RULES.md, TESTING_GUIDE.md)
- Updated README with testing section and performance targets
- All tests passing with proper error handling and data validation
Performance Targets:
- Flux: 78% improvement (≤110s total)
- WAN: 5.6% improvement (≤93s sampling)
- VAE Decode: <10s for any resolution
- Checkpoint Load: <30s for Flux models
Ready for production use with comprehensive testing infrastructure!
- Increment version in pyproject.toml from 1.0.6 to 1.0.7
- Increment version in package.json from 1.0.6 to 1.0.7
- Update comfyui_manager.json version to 1.0.7
- Prepare for release with version bump
- Add comprehensive benchmark results for 320x320px, 17 frames WAN 2.2 i2v
- Show 8.1% overall performance improvement (93.05s vs 101.17s average)
- Include detailed breakdown of KSampler and VAE Decode timings
- Update version to 1.2.1 for ComfyUI registry submission
- Add consistency metrics showing stable performance across runs
- Add comfyui_manager.json with node definitions
- Update package.json with node list and requirements
- Update pyproject.toml with ComfyUI Manager metadata
- This should fix ComfyUI Manager's 'Check Missing' functionality
- Add WindowsPaginationDiagnostic node for automatic detection and fixes
- Add Windows-specific memory management and optimizations
- Add 6 different methods to fix pagination errors
- Add PowerShell and Batch scripts for automatic fixes
- Add psutil dependency for memory diagnostics
- Update documentation with comprehensive troubleshooting guide
- Version bump to 1.2.0
- Renamed directory from ComfyUI-ROCM-Optimized-VAE to rocm-ninodes
- Updated package.json to reflect correct plugin name
- Plugin now properly named to match the actual project identity
- Added package.json for ComfyUI Manager support
- Includes proper metadata, keywords, and requirements
- Enables automatic installation through ComfyUI Manager
- Users can now install via Manager or manual git clone
iGavroche