Update 030_INSTALL_CUDA_AND_ROCM.md

This commit is contained in:
Millun Atluri 2023-09-06 13:55:33 +10:00 committed by GitHub
parent 53f2369d18
commit 3afa73cd33
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23

View File

@ -57,31 +57,26 @@ familiar with containerization technologies such as Docker.
For downloads and instructions, visit the [NVIDIA CUDA Container For downloads and instructions, visit the [NVIDIA CUDA Container
Runtime Site](https://developer.nvidia.com/nvidia-container-runtime) Runtime Site](https://developer.nvidia.com/nvidia-container-runtime)
### (Optional) Cudnnn Installation for 40 series Optimization* ### cuDNN Installation for 40/30 Series Optimization* (Optional)
1) Find the InvokeAI folder 1. Find the InvokeAI folder
2) Click on .venv folder - e.g., YourInvokeFolderHere\.venv 2. Click on .venv folder - e.g., YourInvokeFolderHere\.venv
3) Click on Lib folder - e.g., YourInvokeFolderHere\.venv\Lib 3. Click on Lib folder - e.g., YourInvokeFolderHere\.venv\Lib
4) Click on site-packages folder - e.g., YourInvokeFolderHere\.venv\Lib\site-packages 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 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 6. Click on the lib folder - e.g., YourInvokeFolderHere\.venv\Lib\site-packages\torch\lib
7) __Copy everything inside the folder as a Backup in whatever folder you want, it's just in case.__ 7. Copy everything inside the folder and save it elsewhere as a backup.
8) Go to https://developer.nvidia.com/cudnn 8. Go to https://developer.nvidia.com/cudnn
9) Log-in Or Create an account if you're not already connected 9. Log-in Or Create An account
10) Download the latest version 10. Download the latest version and extract it from the download location
11) Go to the folder and extract it. 12. Find the bin folder E\cudnn-windows-x86_64-__Whatever Version__\bin
12) Find the bin folder E\cudnn-windows-x86_64-__Whatever Version__\bin 13. Copy and paste the 7 .dll files into YourInvokeFolderHere\.venv\Lib\site-packages\torch\lib **Make sure to copy, and not move the files**
13) Copy the 7 dll files 14. If prompted, replace any existing files
14) Go Back to YourInvokeFolderHere\.venv\Lib\site-packages\torch\lib
15) Paste the 7 dll took earlier. It should ask for replacement, accept it. **Notes:**
16) Enjoy ! * 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.
__Very Important: You should Copy everything inside the folder of the torch lib. You do not moove It.__
*Note:
If _no change is seen or a bug appears__ follow the same step instead just copy the Torch/lib back up 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 normally intented for the newer version of graphics card (4th series 3th series) but results have been seen with older graphics card.
So giving a try could be good.
### Torch Installation ### Torch Installation