* Support Combo outputs in a more sane way
* Remove test validate_inputs function on test node
* Make curr_prefix be a list of strings instead of string for easier parsing as keys get added to dynamic types
* Start to account for id prefixes from frontend, need to fix bug with nested dynamics
* Ensure inputs/outputs/hidden are lists in schema finalize function, remove no longer needed 'is not None' checks
* Add raw_link and extra_dict to all relevant Inputs
* Make nested DynamicCombos work properly with prefixed keys on latest frontend; breaks old Autogrow, but is pretty much ready for upcoming Autogrow keys
* Replace ... usage with a MISSING sentinel for clarity in nodes_logic.py
* Added CustomCombo node in backend to reflect frontend node
* Prepare Autogrow's expand_schema_for_dynamic to work with upcoming frontend changes
* Prepare for look up table for dynamic input stuff
* More progress towards dynamic input lookup function stuff
* Finished converting _expand_schema_for_dynamic to be done via lookup instead of OOP to guarantee working with process isolation, did refactoring to remove old implementation + cleaning INPUT_TYPES definition including v3 hidden definition
* Change order of functions
* Removed some unneeded functions after dynamic refactor
* Make MatchType's output default displayname "MATCHTYPE"
* Fix DynamicSlot get_all
* Removed redundant code - dynamic stuff no longer happens in OOP way
* Natively support AnyType (*) without __ne__ hacks
* Remove stray code that made it in
* Remove expand_schema_for_dynamic left over on DynamicInput class
* get_dynamic() on DynamicInput/Output was not doing anything anymore, so removed it
* Make validate_inputs validate combo input correctly
* Temporarily comment out conversion to 'new' (9 month old) COMBO format in get_input_info
* Remove refrences to resources feature scrapped from V3
* Expose DynamicCombo in public API
* satisfy ruff after some code got commented out
* Make missing input error prettier for dynamic types
* Created a Switch2 node as a side-by-side test, will likely go with Switch2 as the initial switch node
* Figured out Switch situation
* Pass in v3_data in IsChangedCache.get function's fingerprint_inputs, add a from_v3_data helper method to HiddenHolder
* Switch order of Switch and Soft Switch nodes in file
* Temp test node for MatchType
* Fix missing v3_data for v1 nodes in validation
* For now, remove chacking duplicate id's for dynamic types
* Add Resize Image/Mask node that thanks to MatchType+DynamicCombo is 16-nodes-in-1
* Made DynamicCombo references in DCTestNode use public interface
* Add an AnyTypeTestNode
* Make lazy status for specific inputs on DynamicInputs work by having the values of the dictionary for check_lazy_status be a tuple, where the second element is the key of the input that can be returned
* Comment out test logic nodes
* Make primitive float's step make more sense
* Add (and leave commented out) some potential logic nodes
* Change default crop option to "center" on Resize Image/Mask node
* Changed copy.copy(d) to d.copy()
* Autogrow is available in stable frontend, so exposing it in public API
* Use outputs id as display_name if no display_name present, remove v3 outputs id restriction that made them have to have unique IDs from the inputs
* Enable Custom Combo node as stable frontend now supports it
* Make id properly act like display_name on outputs
* Add Batch Images/Masks/Latents node
* Comment out Batch Images/Masks/Latents node for now, as Autogrow has a bug with MatchType where top connection is disconnected upon refresh
* Removed code for a couple test nodes in nodes_logic.py
* Add Batch Images, Batch Masks, and Batch Latents nodes with Autogrow, deprecate old Batch Images + LatentBatch nodes
* Add support for sage attention 3 in comfyui, enable via new cli arg
--use-sage-attiention3
* Fix some bugs found in PR review. The N dimension at which Sage
Attention 3 takes effect is reduced to 1024 (although the improvement is
not significant at this scale).
* Remove the Sage Attention3 switch, but retain the attention function
registration.
* Fix a ruff check issue in attention.py
Pretty much every error cudaHostRegister can throw also queues the same
error on the async GPU queue. This was fixed for repinning error case,
but there is the bad mmap and just enomem cases that are harder to
detect.
Do some dummy GPU work to clean the error state.
Can be used to manually set the sigmas for a model.
This node accepts a list of integer and floating point numbers separated
with any non numeric character.
This operation trades in latents which in --gpu-only may be out of the GPU
The two VAE results will follow the --gpu-only defined behaviour so follow
the inpaint image device when calculating the mask in this path.
