The V2 additions the KJNodes completion needed on the core side:
- _model_transforms: the closed, core-owned transform vocabulary
behind ModelRef.patch — 29 named transforms, declaratively
parameterized, validated host-side, immutable and stacking. No
function ever crosses the boundary; a pack cannot register one.
- structured-vs-live split: value()/from_value() only on structured
data refs (LATENT, AUDIO, TRACKS...). MODEL/CLIP/VAE/asset refs are
handles in every execution mode — in-process identity resolution no
longer hands a live model to node code.
- preview overrides (tiny-VAE, LTX factors), triton VAE seam, memory
attention, and profiling surfaces backing the corresponding closed
brokers in the overlay.
- torch_compile/model_patcher/model_management: compiled-view
aliasing recognized by the model manager (no double-counted
weights); shared state-dict loading path so the native loader and
the V2 broker cannot drift.
VAEDecode unwraps a NestedTensor latent (video/audio pair) to its
video component before calling vae.decode(). VAEDecodeTiled skipped
this unwrap and passed the NestedTensor straight into
vae.decode_tiled(), which fails deep in the MiniMax H3 video VAE when
a real tensor's .to() is called with the NestedTensor as an argument.
Fixes#15468.
* Move dataset/text nodes to text category
* Rename category utils into utilities
* Rename category api node into partner
* Move categories conditioning, latent, sampling, model_patches, training, etc. under model category
* Dispatch partner nodes in to 3d, audio, image, text, video categories
* Move PreviewAny node to utilities category
* Move detection category under image category
* Add missing categories
* Move detection nodes to detection category
* Move save nodes to image root catefory
* Rename postprocessors
* Move mask category under image
* Move guiders category to parent level at root of sampling category
* Move custom_sampling category to parent level at the root of sampling category
* Modify description of LoRA loaders
* Fix node id SolidMask
* Move VOID Quadmask under image/mask
* Group compositing nodes under image/compositing
* Move load image as mask to image category for consistency with other load image nodes
* Align display name with Load Checkpoint
* Move dataset category under training category
* Rename Number Convert to Conver Number (verb first)
* Rename Canny node
* Revert wanBlockSwap + description
* Add description to RemoveBackground node
* Revert category update of dataset
Split GLB save logic out of nodes_hunyuan3d.py into a new nodes_save_3d.py, and extend the writer to support UVs, per-vertex colors, and embedded baseColor textures.
Extend the MESH type with optional uvs, vertex_colors, and texture fields so meshes can carry texture data through the graph.
Add pack_variable_mesh_batch / get_mesh_batch_item helpers and switch VoxelToMesh / VoxelToMeshBasic to use them so batches with differing vertex/face counts no longer fail at torch.stack.
* Initial HiDream01-image support
* Cleanup nodes
* Cleaner handling of empty placeholder models
* Remove snap_to_predefined, prefer tooltip for the trained resolutions
* Add model and block wrappers
* Fix shift tooltip
* Add node to work around the patch tile issue
Experimental, runs multiple passes with the patch grid offset and blends with various different methods.
* Qwen35 vision rotary_pos_emb cast fix
* Fix embedding layout type
* Some small optimizations
* Cleanup, don't need this fallback
* Prefix KV cache, cleanup
Bit of speed, reduce redundant code
* Get rid of redundant custom sampler, refactor noise scaling
Our existing lcm sampler is mathematically same, just added the missing options to it instead and a node to control them. Refactored the noise scaling and fix it for the stochastic samplers, add a generic node to control the initial noise scale.
* Update nodes_hidream_o1.py
* Fix some cache validation cases
* Keep existing sampling params
* Remove redundant video vision path
* Replace some numpy ops with torch
* Fx RoPE index for batch size > 1
* Prefer torch preprocessing
* Rename block_type to be compatible with existing patch nodes
* Fixes and tweaks
benjcooley