This rule enforces no arrow functions in component props. In practice, it means all functions passed as component props must be wrapped in `useCallback()`.
This is a performance optimization to prevent unnecessary rerenders.
The rule is added and all violations have been fixed, whew!
* adding VAE recall when using all parameters
* adding VAE to the RecallParameters tab in ImageMetadataActions
* checking for nil vae and casting to null if undefined
* adding default VAE to recall actions list if VAE is nullish
* fix(ui): use `lodash-es` for tree-shakeable imports
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
* drop-down for the color picker
* fixed the bug in alpha value
* designing done
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
* working
* added selector for method
* refactoring graph
* added ersgan method
* fixing yarn build
* add tooltips
* a conjuction
* rephrase
* removed manual sliders, set HRF to calculate dimensions automatically to match 512^2 pixels
* working
* working
* working
* fixed tooltip
* add hrf to use all parameters
* adding hrf method to parameters
* working on parameter recall
* working on parameter recall
* cleaning
* fix(ui): fix unnecessary casts in addHrfToGraph
* chore(ui): use camelCase in addHrfToGraph
* fix(ui): do not add HRF metadata unless HRF is added to graph
* fix(ui): remove unused imports in addHrfToGraph
* feat(ui): do not hide HRF params when disabled, only disable them
* fix(ui): remove unused vars in addHrfToGraph
* feat(ui): default HRF str to 0.35, method ESRGAN
* fix(ui): use isValidBoolean to check hrfEnabled param
* fix(nodes): update CoreMetadataInvocation fields for HRF
* feat(ui): set hrf strength default to 0.45
* fix(ui): set default hrf strength in configSlice
* feat(ui): use translations for HRF features
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
## What type of PR is this? (check all applicable)
- [ ] Refactor
- [ ] Feature
- [X] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission
## Have you discussed this change with the InvokeAI team?
- [ ] Yes
- [ ] No, because:
## Have you updated all relevant documentation?
- [ ] Yes
- [ ] No
## Description
## Related Tickets & Documents
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- Related Issue #
- Closes #
## QA Instructions, Screenshots, Recordings
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## Added/updated tests?
- [ ] Yes
- [ ] No : _please replace this line with details on why tests
have not been included_
## [optional] Are there any post deployment tasks we need to perform?
## What type of PR is this? (check all applicable)
- [ ] Refactor
- [ ] Feature
- [X] Bug Fix
- [X] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission
## Have you discussed this change with the InvokeAI team?
- [X] Yes, with @blessedcoolant
- [ ] No, because:
## Have you updated all relevant documentation?
- [ ] Yes
- [ ] No
## Description
This PR updates Transformers to the most recent version and fixes the
value `pad_to_multiple_of` for `text_encoder.resize_token_embeddings`
which was introduced with
https://github.com/huggingface/transformers/pull/25088 in Transformers
4.32.0.
According to the [Nvidia
Documentation](https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc),
`Performance is better when equivalent matrix dimensions M, N, and K are
aligned to multiples of 8 bytes (or 64 bytes on A100) for FP16`
This fixes the following error that was popping up before every
invocation starting with Transformers 4.32.0
`You are resizing the embedding layer without providing a
pad_to_multiple_of parameter. This means that the new embedding
dimension will be None. This might induce some performance reduction as
Tensor Cores will not be available. For more details about this, or help
on choosing the correct value for resizing, refer to this guide:
https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc`
This is my first "real" fix PR, so I hope this is fine. Please inform me
if there is anything wrong with this. I am glad to help.
Have a nice day and thank you!
## Related Tickets & Documents
<!--
For pull requests that relate or close an issue, please include them
below.
For example having the text: "closes #1234" would connect the current
pull
request to issue 1234. And when we merge the pull request, Github will
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- Related Issue:
https://github.com/huggingface/transformers/issues/26303
- Related Discord discussion:
https://discord.com/channels/1020123559063990373/1154152783579197571
- Closes #
## QA Instructions, Screenshots, Recordings
<!--
Please provide steps on how to test changes, any hardware or
software specifications as well as any other pertinent information.
-->
## Added/updated tests?
- [ ] Yes
- [ ] No : _please replace this line with details on why tests
have not been included_
## [optional] Are there any post deployment tasks we need to perform?
## What type of PR is this? (check all applicable)
- [ ] Refactor
- [X] Feature
- [ ] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission
## Have you discussed this change with the InvokeAI team?
- [X] Yes
- [ ] No, because:
## Have you updated all relevant documentation?
- [X] Yes
- [ ] No
## Description
## Related Tickets & Documents
<!--
For pull requests that relate or close an issue, please include them
below.
For example having the text: "closes #1234" would connect the current
pull
request to issue 1234. And when we merge the pull request, Github will
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- Related Issue #
- Closes #
## QA Instructions, Screenshots, Recordings
<!--
Please provide steps on how to test changes, any hardware or
software specifications as well as any other pertinent information.
-->
## Added/updated tests?
- [ ] Yes
- [ ] No : _please replace this line with details on why tests
have not been included_
## [optional] Are there any post deployment tasks we need to perform?
