* Use `torch.special.expm1`
This function provides greater precision than `exp(x) - 1` for small values of `x`.
Found with TorchFix https://github.com/pytorch-labs/torchfix/
* Use non-alias
* Add 'sigmas' to transformer_options so that downstream code can know about the full scope of current sampling run, fix Hook Keyframes' guarantee_steps=1 inconsistent behavior with sampling split across different Sampling nodes/sampling runs by referencing 'sigmas'
* Cleaned up hooks.py, refactored Hook.should_register and add_hook_patches to use target_dict instead of target so that more information can be provided about the current execution environment if needed
* Refactor WrapperHook into TransformerOptionsHook, as there is no need to separate out Wrappers/Callbacks/Patches into different hook types (all affect transformer_options)
* Refactored HookGroup to also store a dictionary of hooks separated by hook_type, modified necessary code to no longer need to manually separate out hooks by hook_type
* In inner_sample, change "sigmas" to "sampler_sigmas" in transformer_options to not conflict with the "sigmas" that will overwrite "sigmas" in _calc_cond_batch
* Refactored 'registered' to be HookGroup instead of a list of Hooks, made AddModelsHook operational and compliant with should_register result, moved TransformerOptionsHook handling out of ModelPatcher.register_all_hook_patches, support patches in TransformerOptionsHook properly by casting any patches/wrappers/hooks to proper device at sample time
* Made hook clone code sane, made clear ObjectPatchHook and SetInjectionsHook are not yet operational
* Fix performance of hooks when hooks are appended via Cond Pair Set Props nodes by properly caching between positive and negative conds, make hook_patches_backup behave as intended (in the case that something pre-registers WeightHooks on the ModelPatcher instead of registering it at sample time)
* Filter only registered hooks on self.conds in CFGGuider.sample
* Make hook_scope functional for TransformerOptionsHook
* removed 4 whitespace lines to satisfy Ruff,
* Add a get_injections function to ModelPatcher
* Made TransformerOptionsHook contribute to registered hooks properly, added some doc strings and removed a so-far unused variable
* Rename AddModelsHooks to AdditionalModelsHook, rename SetInjectionsHook to InjectionsHook (not yet implemented, but at least getting the naming figured out)
* Clean up a typehint
I think the issue this was working around has been solved.
If you notice that this change slows things down or causes stutters on
your AMD GPU with ROCm on Linux please report it.
This commit fixes the temporal tile size calculation, and removes
a redundant tile at the end of the range when its elements are
completely covered by the previous tile.
Co-authored-by: Andrew Kvochko <a.kvochko@lightricks.com>
* nit
* Add option to log non-error output to stdout
- No change to default behaviour
- Adds CLI argument: --log-stdout
- With this arg present, any logging of a level below logging.ERROR will be sent to stdout instead of stderr
* Add oneAPI device selector and some other minor changes.
* Fix device selector variable name.
* Flip minor version check sign.
* Undo changes to README.md.
This should make it possible to do higher res images/longer videos by
further offloading weights to CPU memory.
Please report an issue if this slows down things on your system.
* fix attention OOM in xformers
* allow passing attention mask in flux attention
* allow an attn_mask in flux
* attn masks can be done using replace patches instead of a separate dict
* fix return types
* fix return order
* enumerate
* patch the right keys
* arg names
* fix a silly bug
* fix xformers masks
* replace match with if, elif, else
* mask with image_ref_size
* remove unused import
* remove unused import 2
* fix pytorch/xformers attention
This corrects a weird inconsistency with skip_reshape.
It also allows masks of various shapes to be passed, which will be
automtically expanded (in a memory-efficient way) to a size that is
compatible with xformers or pytorch sdpa respectively.
* fix mask shapes
comfyanonymous
Chenlei Hu
chaObserv
Sergii Dymchenko
catboxanon
Pam
Jedrzej Kosinski
Andrew Kvochko
blepping
filtered
Huazhong Ji
Simon Lui
zhangp365
City
Raphael Walker