feat(docs): add platform/model compatibility list
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# Very Rough Benchmarks
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CUDA > ROCm > DirectML > drawing it yourself > CPU
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Using 25 steps of Euler A in txt2img, 512x512.
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- CPU:
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@ -9,6 +11,8 @@ Using 25 steps of Euler A in txt2img, 512x512.
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- 7950X: 3.5s/it, 90sec/image
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- GPU:
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- AMD:
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- 6900XT: 3.5it/s, 9sec/image
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- 6900XT
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- Win10, DirectML: 3.5it/s, 9sec/image
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- Ubuntu 20.04, ROCm 5.2: 4.5it/s, 6sec/image
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- Nvidia:
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- 4090: 6.5it/s, 4sec/image
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# Compatibility
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## Contents
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- [Compatibility](#compatibility)
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- [Contents](#contents)
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- [Driver Versions](#driver-versions)
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- [Container/Platform Acceleration](#containerplatform-acceleration)
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- [Container Notes](#container-notes)
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- [Model/Platform Acceleration](#modelplatform-acceleration)
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- [Model Notes](#model-notes)
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## Driver Versions
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- CUDA
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- 11.6
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- 11.7
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- ROCm
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- 5.2
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- 5.4 seems like it might work
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## Container/Platform Acceleration
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| Runtime | CUDA | DirectML | ROCm | CPU |
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| ------- | ---- | -------- | -------- | --- |
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| docker | yes | no, 1 | maybe, 2 | yes |
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| podman | 3 | no, 1 | maybe, 2 | yes |
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### Container Notes
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1. no package available: https://github.com/ssube/onnx-web/issues/63
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2. should work but testing failed: https://github.com/ssube/onnx-web/issues/10
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3. should work, not tested: https://gist.github.com/bernardomig/315534407585d5912f5616c35c7fe374
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## Model/Platform Acceleration
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| Model | CUDA | DirectML | ROCm | CPU |
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| ---------------- | ---- | -------- | ----- | --- |
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| Stable Diffusion | yes | yes | yes | yes |
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| Real ESRGAN | yes | yes | no, 1 | yes |
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| GFPGAN | 2 | 2 | 2 | yes |
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### Model Notes
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1. Real ESRGAN running on ROCm crashes with an error:
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```none
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File "/home/ssube/onnx-web/api/onnx_web/upscale.py", line 67, in __call__
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output = self.session.run([output_name], {
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File "/home/ssube/onnx-web/api/onnx_env/lib/python3.8/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 200, in run
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return self._sess.run(output_names, input_feed, run_options)
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onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Non-zero status code returned while running FusedConv node. Name:'/body/body.0/rdb1/conv1/Conv' Status Message: MIOPEN failure 1: miopenStatusNotInitialized ; GPU=0 ; hostname=ssube-notwin ; expr=status_;
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```
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2. GFPGAN seems to always be running in CPU mode
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This is the user guide for ONNX web, a web GUI for running ONNX models with hardware acceleration on both AMD and Nvidia
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system, with a CPU software fallback.
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The API runs on both Linux and Windows and provides access to the major functionality of diffusers, along with metadata
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about the available models and accelerators, and the output of previous runs. Hardware acceleration is supported on both
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AMD and Nvidia for both Linux and Windows, with a CPU fallback capable of running on laptop-class machines.
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The API is written in Python and runs on both Linux and Windows and provides access to the major functionality of
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diffusers, along with metadata about the available models and accelerators, and the output of previous runs. Hardware
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acceleration is supported on both AMD and Nvidia for both Linux and Windows, with a CPU fallback capable of running on
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laptop-class machines.
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The GUI is hosted on Github Pages and runs in all major browsers, including on mobile devices. It allows you to select
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the model and accelerator being used for each image pipeline. Image parameters are shown for each of the major modes,
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and you can either upload or paint the mask for inpainting and outpainting. The last few output images are shown below
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the image controls, making it easy to refer back to previous parameters or save an image from earlier.
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The GUI is written in Javascript, hosted on Github Pages, and runs in all major browsers, including on mobile devices.
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It allows you to select the model and accelerator being used for each image pipeline. Image parameters are shown for
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each of the major modes, and you can either upload or paint the mask for inpainting and outpainting. The last few output
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images are shown below the image controls, making it easy to refer back to previous parameters or save an image from
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earlier.
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Please see [the server admin guide](server-admin.md) for details on how to configure and run the server.
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@ -92,7 +94,7 @@ will need a simple drawing component, but anything more complicated, like layers
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the Gimp, Krita, or Photoshop.
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This is _not_ a tool for building new ML models. While I am open to some training features, like Dreambooth and anything
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needed to convert models, that is not the focus and should be limited features that support the other tabs.
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needed to convert models, that is not the focus and should be limited to features that support the other tabs.
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### ONNX models
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