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Added extra steps to update the Cudnnn DLL found in the Torch packages #4459

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Merged
merged 8 commits into from
Sep 7, 2023
Merged

Added extra steps to update the Cudnnn DLL found in the Torch packages #4459

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04c0a83
Added extra steps to update the Cudnnn DLL found in the Torch packages
Keerigan45 Sep 5, 2023
53f2369
Update 030_INSTALL_CUDA_AND_ROCM.md
hipsterusername Sep 5, 2023
3afa73c
Update 030_INSTALL_CUDA_AND_ROCM.md
Millu Sep 6, 2023
6506ce3
Updated "\" to be escaped in markdown
Millu Sep 6, 2023
e16598c
Merge branch 'main' into patch-2
Millu Sep 6, 2023
cfc4caf
Update 030_INSTALL_CUDA_AND_ROCM.md
Keerigan45 Sep 7, 2023
40a0b2c
Update 030_INSTALL_CUDA_AND_ROCM.md
Keerigan45 Sep 7, 2023
252adb9
Fixed typos
Millu Sep 7, 2023
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24 changes: 24 additions & 0 deletions docs/installation/030_INSTALL_CUDA_AND_ROCM.md
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Expand Up @@ -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
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