- Remove optimize_for_video (auto-detects 5D video latents)
- Remove precision_mode (was a no-op)
- compatibility_mode moved to advanced=True toggle
- Node now matches stock interface exactly (5 inputs) with only
an advanced debug toggle added
- Video workflow auto-detected from latent shape (5D, T > 1)
- Architecture logging explicitly shows GPU family on ROCm
- Benchmark node also cleaned up (no extra params)
- 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
- Updated version to 2.0.11 in pyproject.toml and comfyui_manager.json for consistency.
- Removed video chunking from ROCMOptimizedVAEDecode to ensure full video decoding for temporal/causal VAEs, preventing artifacts.
- Added new ROCm Text Generate LTX2 Prompt node, enhancing generative AI capabilities.
- Updated README to reflect new features and improvements in v2.0.11.
- Enhanced changelog with details on changes and fixes in this release.
- Added optional in-memory cache to ROCmOptimizedCheckpointLoader to avoid redundant disk loads during repeated API runs.
- Implemented cache eviction strategy to manage memory efficiently on gfx1151 architecture.
- Updated INPUT_TYPES to include parameters for cache usage and forced reload.
- Added integration and unit tests to verify cache behavior and functionality.
- Documented caching mechanism in CHECKPOINT_CACHE_API.md and updated LOADER_NODES_GUIDE.md for clarity.
- 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
iGavroche