diff --git a/.github/ISSUE_TEMPLATE/FEATURE_REQUEST.yml b/.github/ISSUE_TEMPLATE/FEATURE_REQUEST.yml index 6fb80be593..c7e7f4bc87 100644 --- a/.github/ISSUE_TEMPLATE/FEATURE_REQUEST.yml +++ b/.github/ISSUE_TEMPLATE/FEATURE_REQUEST.yml @@ -1,5 +1,5 @@ name: Feature Request -description: Commit a idea or Request a new feature +description: Contribute a idea or request a new feature title: '[enhancement]: ' labels: ['enhancement'] # assignees: @@ -9,14 +9,14 @@ body: - type: markdown attributes: value: | - Thanks for taking the time to fill out this Feature request! + Thanks for taking the time to fill out this feature request! - type: checkboxes attributes: label: Is there an existing issue for this? description: | Please make use of the [search function](https://github.com/invoke-ai/InvokeAI/labels/enhancement) - to see if a simmilar issue already exists for the feature you want to request + to see if a similar issue already exists for the feature you want to request options: - label: I have searched the existing issues required: true @@ -36,7 +36,7 @@ body: label: What should this feature add? description: Please try to explain the functionality this feature should add placeholder: | - Instead of one huge textfield, it would be nice to have forms for bug-reports, feature-requests, ... + Instead of one huge text field, it would be nice to have forms for bug-reports, feature-requests, ... Great benefits with automatic labeling, assigning and other functionalitys not available in that form via old-fashioned markdown-templates. I would also love to see the use of a moderator bot 🤖 like https://github.com/marketplace/actions/issue-moderator-with-commands to auto close old issues and other things @@ -51,6 +51,6 @@ body: - type: textarea attributes: - label: Aditional Content + label: Additional Content description: Add any other context or screenshots about the feature request here. - placeholder: This is a Mockup of the design how I imagine it + placeholder: This is a mockup of the design how I imagine it diff --git a/docs/installation/030_INSTALL_CUDA_AND_ROCM.md b/docs/installation/030_INSTALL_CUDA_AND_ROCM.md index 314043f538..7f8af06b58 100644 --- a/docs/installation/030_INSTALL_CUDA_AND_ROCM.md +++ b/docs/installation/030_INSTALL_CUDA_AND_ROCM.md @@ -57,6 +57,30 @@ familiar with containerization technologies such as Docker. For downloads and instructions, visit the [NVIDIA CUDA Container Runtime Site](https://developer.nvidia.com/nvidia-container-runtime) +### cuDNN Installation for 40/30 Series Optimization* (Optional) + +1. Find the InvokeAI folder +2. Click on .venv folder - e.g., YourInvokeFolderHere\\.venv +3. Click on Lib folder - e.g., YourInvokeFolderHere\\.venv\Lib +4. Click on site-packages folder - e.g., YourInvokeFolderHere\\.venv\Lib\site-packages +5. Click on Torch directory - e.g., YourInvokeFolderHere\InvokeAI\\.venv\Lib\site-packages\torch +6. Click on the lib folder - e.g., YourInvokeFolderHere\\.venv\Lib\site-packages\torch\lib +7. Copy everything inside the folder and save it elsewhere as a backup. +8. Go to __https://developer.nvidia.com/cudnn__ +9. Login or create an Account. +10. Choose the newer version of cuDNN. **Note:** +There are two versions, 11.x or 12.x for the differents architectures(Turing,Maxwell Etc...) of GPUs. +You can find which version you should download from [this link](https://docs.nvidia.com/deeplearning/cudnn/support-matrix/index.html). +13. Download the latest version and extract it from the download location +14. Find the bin folder E\cudnn-windows-x86_64-__Whatever Version__\bin +15. Copy and paste the .dll files into YourInvokeFolderHere\\.venv\Lib\site-packages\torch\lib **Make sure to copy, and not move the files** +16. If prompted, replace any existing files + +**Notes:** +* If no change is seen or any issues are encountered, follow the same steps as above and paste the torch/lib backup folder you made earlier and replace it. If you didn't make a backup, you can also uninstall and reinstall torch through the command line to repair this folder. +* This optimization is intended for the newer version of graphics card (40/30 series) but results have been seen with older graphics card. + + ### Torch Installation When installing torch and torchvision manually with `pip`, remember to provide