mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
Revert torch to use cu121 (#5091)
## What type of PR is this? (check all applicable)
- [ ] Refactor
- [ ] Feature
- [ ] Bug Fix
- [X] 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
automatically close the issue.
-->
- 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?
This commit is contained in:
Millun Atluri
GitHub
commit
a047bad391
@ -161,7 +161,7 @@ the command `npm install -g yarn` if needed)
|
||||
_For Windows/Linux with an NVIDIA GPU:_
|
||||
|
||||
```terminal
|
||||
pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu118
|
||||
pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu121
|
||||
```
|
||||
|
||||
_For Linux with an AMD GPU:_
|
||||
|
||||
@ -471,7 +471,7 @@ Then type the following commands:
|
||||
|
||||
=== "NVIDIA System"
|
||||
```bash
|
||||
pip install torch torchvision --force-reinstall --extra-index-url https://download.pytorch.org/whl/cu118
|
||||
pip install torch torchvision --force-reinstall --extra-index-url https://download.pytorch.org/whl/cu121
|
||||
pip install xformers
|
||||
```
|
||||
|
||||
|
||||
@ -148,7 +148,7 @@ manager, please follow these steps:
|
||||
=== "CUDA (NVidia)"
|
||||
|
||||
```bash
|
||||
pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu118
|
||||
pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu121
|
||||
```
|
||||
|
||||
=== "ROCm (AMD)"
|
||||
@ -327,7 +327,7 @@ installation protocol (important!)
|
||||
|
||||
=== "CUDA (NVidia)"
|
||||
```bash
|
||||
pip install -e .[xformers] --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu118
|
||||
pip install -e .[xformers] --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu121
|
||||
```
|
||||
|
||||
=== "ROCm (AMD)"
|
||||
@ -375,7 +375,7 @@ you can do so using this unsupported recipe:
|
||||
mkdir ~/invokeai
|
||||
conda create -n invokeai python=3.10
|
||||
conda activate invokeai
|
||||
pip install InvokeAI[xformers] --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu118
|
||||
pip install InvokeAI[xformers] --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu121
|
||||
invokeai-configure --root ~/invokeai
|
||||
invokeai --root ~/invokeai --web
|
||||
```
|
||||
|
||||
@ -85,7 +85,7 @@ You can find which version you should download from [this link](https://docs.nvi
|
||||
|
||||
When installing torch and torchvision manually with `pip`, remember to provide
|
||||
the argument `--extra-index-url
|
||||
https://download.pytorch.org/whl/cu118` as described in the [Manual
|
||||
https://download.pytorch.org/whl/cu121` as described in the [Manual
|
||||
Installation Guide](020_INSTALL_MANUAL.md).
|
||||
|
||||
## :simple-amd: ROCm
|
||||
|
||||
@ -28,7 +28,7 @@ command line, then just be sure to activate it's virtual environment.
|
||||
Then run the following three commands:
|
||||
|
||||
```sh
|
||||
pip install xformers~=0.0.19
|
||||
pip install xformers~=0.0.22
|
||||
pip install triton # WON'T WORK ON WINDOWS
|
||||
python -m xformers.info output
|
||||
```
|
||||
@ -42,7 +42,7 @@ If all goes well, you'll see a report like the
|
||||
following:
|
||||
|
||||
```sh
|
||||
xFormers 0.0.20
|
||||
xFormers 0.0.22
|
||||
memory_efficient_attention.cutlassF: available
|
||||
memory_efficient_attention.cutlassB: available
|
||||
memory_efficient_attention.flshattF: available
|
||||
@ -59,14 +59,14 @@ swiglu.gemm_fused_operand_sum: available
|
||||
swiglu.fused.p.cpp: available
|
||||
is_triton_available: True
|
||||
is_functorch_available: False
|
||||
pytorch.version: 2.0.1+cu118
|
||||
pytorch.version: 2.1.0+cu121
|
||||
pytorch.cuda: available
|
||||
gpu.compute_capability: 8.9
|
||||
gpu.name: NVIDIA GeForce RTX 4070
|
||||
build.info: available
|
||||
build.cuda_version: 1108
|
||||
build.python_version: 3.10.11
|
||||
build.torch_version: 2.0.1+cu118
|
||||
build.torch_version: 2.1.0+cu121
|
||||
build.env.TORCH_CUDA_ARCH_LIST: 5.0+PTX 6.0 6.1 7.0 7.5 8.0 8.6
|
||||
build.env.XFORMERS_BUILD_TYPE: Release
|
||||
build.env.XFORMERS_ENABLE_DEBUG_ASSERTIONS: None
|
||||
@ -92,33 +92,22 @@ installed from source. These instructions were written for a system
|
||||
running Ubuntu 22.04, but other Linux distributions should be able to
|
||||
adapt this recipe.
|
||||
|
||||
#### 1. Install CUDA Toolkit 11.8
|
||||
#### 1. Install CUDA Toolkit 12.1
|
||||
|
||||
You will need the CUDA developer's toolkit in order to compile and
|
||||
install xFormers. **Do not try to install Ubuntu's nvidia-cuda-toolkit
|
||||
package.** It is out of date and will cause conflicts among the NVIDIA
|
||||
driver and binaries. Instead install the CUDA Toolkit package provided
|
||||
by NVIDIA itself. Go to [CUDA Toolkit 11.8
|
||||
Downloads](https://developer.nvidia.com/cuda-11-8-0-download-archive)
|
||||
by NVIDIA itself. Go to [CUDA Toolkit 12.1
|
||||
Downloads](https://developer.nvidia.com/cuda-12-1-0-download-archive)
|
||||
and use the target selection wizard to choose your platform and Linux
|
||||
distribution. Select an installer type of "runfile (local)" at the
|
||||
last step.
|
||||
|
||||
This will provide you with a recipe for downloading and running a
|
||||
install shell script that will install the toolkit and drivers. For
|
||||
example, the install script recipe for Ubuntu 22.04 running on a
|
||||
x86_64 system is:
|
||||
install shell script that will install the toolkit and drivers.
|
||||
|
||||
```
|
||||
wget https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
|
||||
sudo sh cuda_11.8.0_520.61.05_linux.run
|
||||
```
|
||||
|
||||
Rather than cut-and-paste this example, We recommend that you walk
|
||||
through the toolkit wizard in order to get the most up to date
|
||||
installer for your system.
|
||||
|
||||
#### 2. Confirm/Install pyTorch 2.01 with CUDA 11.8 support
|
||||
#### 2. Confirm/Install pyTorch 2.1.0 with CUDA 12.1 support
|
||||
|
||||
If you are using InvokeAI 3.0.2 or higher, these will already be
|
||||
installed. If not, you can check whether you have the needed libraries
|
||||
@ -133,7 +122,7 @@ Then run the command:
|
||||
python -c 'exec("import torch\nprint(torch.__version__)")'
|
||||
```
|
||||
|
||||
If it prints __1.13.1+cu118__ you're good. If not, you can install the
|
||||
If it prints __2.1.0+cu121__ you're good. If not, you can install the
|
||||
most up to date libraries with this command:
|
||||
|
||||
```sh
|
||||
|
||||
@ -460,10 +460,10 @@ def get_torch_source() -> (Union[str, None], str):
|
||||
url = "https://download.pytorch.org/whl/cpu"
|
||||
|
||||
if device == "cuda":
|
||||
url = "https://download.pytorch.org/whl/cu118"
|
||||
url = "https://download.pytorch.org/whl/cu121"
|
||||
optional_modules = "[xformers,onnx-cuda]"
|
||||
if device == "cuda_and_dml":
|
||||
url = "https://download.pytorch.org/whl/cu118"
|
||||
url = "https://download.pytorch.org/whl/cu121"
|
||||
optional_modules = "[xformers,onnx-directml]"
|
||||
|
||||
# in all other cases, Torch wheels should be coming from PyPi as of Torch 1.13
|
||||
|
||||
Loading…
Reference in New Issue
Block a user