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feat(api): pin pytorch versions and update nightly ORT

This commit is contained in:
Sean Sube 2023-03-26 18:21:21 -05:00
parent bb5d0635d1
commit dca8a97796
Signed by: ssube
GPG Key ID: 3EED7B957D362AF1
9 changed files with 93 additions and 92 deletions
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144
README.md
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@ -57,10 +57,9 @@ Please [see the User Guide](https://github.com/ssube/onnx-web/blob/main/docs/use
- [Note about setup paths](#note-about-setup-paths)
- [Create a virtual environment](#create-a-virtual-environment)
- [Install pip packages](#install-pip-packages)
- [For AMD on Linux: Install PyTorch and ONNX ROCm](#for-amd-on-linux-install-pytorch-and-onnx-rocm)
- [For AMD on Windows: Install ONNX DirectML](#for-amd-on-windows-install-onnx-directml)
- [For CPU on Linux: Install PyTorch CPU](#for-cpu-on-linux-install-pytorch-cpu)
- [For CPU on Windows: Install PyTorch CPU](#for-cpu-on-windows-install-pytorch-cpu)
- [For AMD on Linux: PyTorch ROCm and ONNX runtime ROCm](#for-amd-on-linux-pytorch-rocm-and-onnx-runtime-rocm)
- [For AMD on Windows: PyTorch CPU and ONNX runtime DirectML](#for-amd-on-windows-pytorch-cpu-and-onnx-runtime-directml)
- [For CPU everywhere: PyTorch CPU and ONNX runtime CPU](#for-cpu-everywhere-pytorch-cpu-and-onnx-runtime-cpu)
- [For Nvidia everywhere: Install PyTorch GPU and ONNX GPU](#for-nvidia-everywhere-install-pytorch-gpu-and-onnx-gpu)
- [Download and convert models](#download-and-convert-models)
- [Converting your own models](#converting-your-own-models)
@ -96,19 +95,19 @@ Install Git and Python 3.10 for your environment:
- https://gitforwindows.org/
- https://www.python.org/downloads/
The latest version of git should be fine. Python must be 3.10 or earlier, 3.10 seems to work well. If you already have
Python installed for another form of Stable Diffusion, that should work, but make sure to verify the version in the next
step.
The latest version of git should be fine. Python should be 3.9 or 3.10, although 3.8 and 3.11 may work if the correct
packages are available for your platform. If you already have Python installed for another form of Stable Diffusion,
that should work, but make sure to verify the version in the next step.
Make sure you have Python 3.10 or earlier:
Make sure you have Python 3.9 or 3.10:
```shell
> python --version
Python 3.10
```
If your system differentiates between Python 2 and 3, and uses `python3` and `pip3` for the Python 3.x tools, make sure
to adjust the commands shown here. They should otherwise be the same: `python3 --version`.
If your system differentiates between Python 2 and 3 and uses the `python3` and `pip3` commands for the Python 3.x
tools, make sure to adjust the commands shown here. They should otherwise be the same: `python3 --version`.
Once you have those basic packages installed, clone this git repository:
@ -125,7 +124,6 @@ Most of these setup commands should be run in the Python environment and the `ap
```shell
> cd api
> pwd
/home/ssube/code/github/ssube/onnx-web/api
```
@ -140,7 +138,6 @@ Change into the `api/` directory, then create a virtual environment:
```shell
> pip install virtualenv
> python -m venv onnx_env
```
@ -173,101 +170,88 @@ Update pip itself:
### Install pip packages
You can install all of the necessary packages at once using [the `requirements/base.txt` file](./api/requirements/base.txt)
and the `requirements/` file for your platform:
and the `requirements/` file for your platform. Install them in separate commands and make sure to install the
platform-specific packages first:
```shell
> pip install -r requirements/base.txt -r requirements/amd-linux.txt
> pip install -r requirements/amd-linux.txt
> pip install -r requirements/base.txt
# or
> pip install -r requirements/base.txt -r requirements/amd-windows.txt
> pip install -r requirements/amd-windows.txt
> pip install -r requirements/base.txt
# or
> pip install -r requirements/base.txt -r requirements/amd-windows-nightly.txt
> pip install -r requirements/cpu.txt
> pip install -r requirements/base.txt
# or
> pip install -r requirements/base.txt -r requirements/cpu.txt
# or
> pip install -r requirements/base.txt -r requirements/nvidia.txt
> pip install -r requirements/nvidia.txt
> pip install -r requirements/base.txt
```
Only install one of the platform-specific requirements files, otherwise you may end up with the wrong version of
PyTorch or the ONNX runtime. The ONNX runtime nightly packages used by `amd-windows-nightly.txt` can be substantially
faster than the latest release, but may not always be stable.
PyTorch or the ONNX runtime. The full list of available ONNX runtime packages [can be found here
](https://download.onnxruntime.ai/).
If you prefer, you can install all of the packages manually using pip:
If you have successfully installed both of the requirements files for your platform, you do not need to install
any of the packages shown in the following platform-specific sections.
The ONNX runtime nightly packages used by the `requirements/*-nightly.txt` files can be substantially faster than the
last release, but may not always be stable. Many of the nightly packages are specific to one version of Python and
some are only available for Python 3.8 and 3.9, so you may need to find the correct package for your environment. If
you are using Python 3.10, download the `cp310` package. For Python 3.9, download the `cp39` package, and so on.
Installing with pip will figure out the correct package for you.
#### For AMD on Linux: PyTorch ROCm and ONNX runtime ROCm
If you are running on Linux with an AMD GPU, install the ROCm versions of PyTorch and `onnxruntime`:
```shell
> pip install "numpy>=1.20,<1.24"
> pip install "protobuf<4,>=3.20.2"
# stable diffusion and friends
> pip install accelerate diffusers ftfy onnx onnxruntime spacy scipy transformers
# upscaling and face correction
> pip install basicsr facexlib gfpgan realesrgan
# API server
> pip install flask flask-cors flask_executor
> pip install "torch==1.13.1" "torchvision==0.14.1" --extra-index-url https://download.pytorch.org/whl/rocm5.2
# and one of
> pip install https://download.onnxruntime.ai/onnxruntime_training-1.14.1%2Brocm54-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
# or
> pip install https://download.onnxruntime.ai/onnxruntime_training-1.15.0.dev20230326001%2Brocm542-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
```
At the moment, only `numpy` and `protobuf` seem to need a specific version. If you see an error about `np.float`, make
sure you are not using `numpy>=1.24`.
[This SO question](https://stackoverflow.com/questions/74844262/how-to-solve-error-numpy-has-no-attribute-float-in-python)
has more details.
Make sure you have installed ROCm 5.x ([see their documentation
](https://docs.amd.com/bundle/ROCm-Installation-Guide-v5.2.3/page/How_to_Install_ROCm.html#_How_to_Install) for more
details) and that the version of `onnxruntime` matches your ROCm drivers. The version of PyTorch does not need to match
exactly, and they only have limited versions available.
#### For AMD on Linux: Install PyTorch and ONNX ROCm
Ubuntu 20.04 supports ROCm 5.2 and Ubuntu 22.04 supports ROCm 5.4, unless you want to build custom packages. The ROCm
5.x series supports many discrete AMD cards since the Vega 20 architecture, with [a partial list of supported cards
shown here](https://docs.amd.com/bundle/ROCm-Installation-Guide-v5.4.3/page/Prerequisites.html#d5434e465).
If you are running on Linux with an AMD GPU, download and install the ROCm version of `onnxruntime` and the ROCm
version of PyTorch:
```shell
> pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/rocm5.2
> wget https://download.onnxruntime.ai/onnxruntime_training-1.13.0.dev20221021001%2Brocm523-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
> pip install ./onnxruntime_training-1.13.0.dev20221021001%2Brocm523-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
```
Make sure you have installed ROCm 5.x ([see their documentation](https://docs.amd.com/bundle/ROCm-Installation-Guide-v5.2.3/page/How_to_Install_ROCm.html#_How_to_Install) for more details) and that the version of
`onnxruntime` matches your ROCm drivers. See [the full list of available packages](https://download.onnxruntime.ai/)
for more. Ubuntu 20.04 supports ROCm 5.2 and Ubuntu 22.04 supports ROCm 5.4, unless you want to build custom packages.
#### For AMD on Windows: Install ONNX DirectML
#### For AMD on Windows: PyTorch CPU and ONNX runtime DirectML
If you are running on Windows with an AMD GPU, install the DirectML ONNX runtime as well:
```shell
> pip install onnxruntime-directml --force-reinstall
> pip install "numpy>=1.20,<1.24" # the DirectML package will upgrade numpy to 1.24, which will not work
> pip install "torch==1.13.1" "torchvision==0.14.1" --extra-index-url https://download.pytorch.org/whl/cpu
# and one of
> pip install onnxruntime-directml
# or
> pip install ort-nightly-directml --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple/ --force-reinstall
```
You can optionally install the latest DirectML ORT nightly package, which may provide a substantial performance increase
(on my machine, the stable version takes about 30sec/image vs 9sec/image for the nightly).
Downloads can be found at https://aiinfra.visualstudio.com/PublicPackages/_artifacts/feed/ORT-Nightly. You can install
through pip or download the package file. If you are using Python 3.10, download the `cp310` package. For Python 3.9,
download the `cp39` package, and so on. Installing with pip will figure out the correct version:
If you DirectML package upgrades numpy to an incompatible version >= 1.24, downgrade it:
```shell
> pip install --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple/ ort-nightly-directml --force-reinstall
> pip install "numpy>=1.20,<1.24" --force-reinstall # the DirectML package will upgrade numpy to 1.24, which will not work
```
Make sure to include the `--force-reinstall` flag, since it requires some older versions of other packages, and will
overwrite the versions you currently have installed.
You can optionally install the latest DirectML ORT nightly package, which may provide a substantial performance
increase.
#### For CPU on Linux: Install PyTorch CPU
#### For CPU everywhere: PyTorch CPU and ONNX runtime CPU
If you are running with a CPU and no hardware acceleration, install `onnxruntime` and the CPU version of PyTorch:
```shell
> pip install torch --extra-index-url https://download.pytorch.org/whl/cpu
```
#### For CPU on Windows: Install PyTorch CPU
If you are running with a CPU and no hardware acceleration, install `onnxruntime` and the CPU version of PyTorch:
```shell
> pip install torch
> pip install "torch==1.13.1" "torchvision==0.14.1" --extra-index-url https://download.pytorch.org/whl/cpu
# and
> pip install onnxruntime
# or
> pip install ort-nightly --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple/ --force-reinstall
```
#### For Nvidia everywhere: Install PyTorch GPU and ONNX GPU
@ -276,9 +260,11 @@ If you are running with an Nvidia GPU on any operating system, install `onnxrunt
PyTorch:
```shell
> pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/cu117
> pip install "torch==1.13.1" "torchvision==0.14.1" --extra-index-url https://download.pytorch.org/whl/cu117
# and
> pip install onnxruntime-gpu
# or
> pip install ort-nightly-gpu --extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple/ --force-reinstall
```
Make sure you have installed CUDA 11.x and that the version of PyTorch matches the version of CUDA

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api/requirements/amd-linux-nightly.txt Normal file
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@ -0,0 +1,4 @@
--extra-index-url https://download.pytorch.org/whl/rocm5.2
torch==1.13.1
torchvision==0.14.1
https://download.onnxruntime.ai/onnxruntime_training-1.15.0.dev20230326001%2Brocm54-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

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api/requirements/amd-linux.txt
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@ -1,4 +1,4 @@
--extra-index-url https://download.pytorch.org/whl/rocm5.4
torch>=1.12,<2
torchvision>=0.13,<0.15
onnxruntime>=1.13
--extra-index-url https://download.pytorch.org/whl/rocm5.2
torch==1.13.1
torchvision==0.14.1
https://download.onnxruntime.ai/onnxruntime_training-1.14.1%2Brocm54-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

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api/requirements/amd-windows-nightly.txt
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@ -1,5 +1,5 @@
--extra-index-url https://download.pytorch.org/whl/cpu
torch>=1.12,<2
torchvision>=0.13,<0.15
torch==1.13.1
torchvision==0.14.1
--extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple/
ort-nightly-directml

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api/requirements/amd-windows.txt
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@ -1,4 +1,4 @@
--extra-index-url https://download.pytorch.org/whl/cpu
torch>=1.12,<2
torchvision>=0.13,<0.15
onnxruntime-directml
torch==1.13.1
torchvision==0.14.1
onnxruntime-directml>=1.13

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api/requirements/cpu-nightly.txt Normal file
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@ -0,0 +1,5 @@
--extra-index-url https://download.pytorch.org/whl/cpu
torch==1.13.1
torchvision==0.14.1
--extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple/
ort-nightly

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api/requirements/cpu.txt
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@ -1,3 +1,4 @@
--extra-index-url https://download.pytorch.org/whl/cpu
torch>=1.12,<2
torchvision>=0.13,<0.15
torch==1.13.1
torchvision==0.14.1
onnxruntime>=1.13

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api/requirements/nvidia-nightly.txt Normal file
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@ -0,0 +1,5 @@
--extra-index-url https://download.pytorch.org/whl/cu117
torch==1.13.1
torchvision==0.14.1
--extra-index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple/
ort-nightly-gpu

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api/requirements/nvidia.txt
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@ -1,4 +1,4 @@
--extra-index-url https://download.pytorch.org/whl/cu117
torch>=1.12,<2
torchvision>=0.13,<0.15
torch==1.13.1
torchvision==0.14.1
onnxruntime-gpu>=1.13