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NXP backend: Fix missing NXP backend documentation page in release 1.0 documentation #14851
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StrycekSimon
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| Original file line number | Diff line number | Diff line change |
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| @@ -1,5 +1,40 @@ | ||
| # NXP eIQ Neutron Backend | ||
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| See | ||
| [NXP eIQ Neutron Backend](https://github.com/pytorch/executorch/blob/main/backends/nxp/README.md) | ||
| for current status about running ExecuTorch on NXP eIQ Neutron Backend. | ||
| This manual page is dedicated to introduction of using the ExecuTorch with NXP eIQ Neutron Backend. | ||
| NXP offers accelerated machine learning models inference on edge devices. | ||
| To learn more about NXP's machine learning acceleration platform, please refer to [the official NXP website](https://www.nxp.com/applications/technologies/ai-and-machine-learning:MACHINE-LEARNING). | ||
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| <div class="admonition tip"> | ||
| For up-to-date status about running ExecuTorch on Neutron Backend please visit the <a href="https://github.com/pytorch/executorch/blob/main/backends/nxp/README.md">manual page</a>. | ||
| </div> | ||
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| ## Features | ||
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| Executorch v1.0 supports running machine learning models on selected NXP chips (for now only i.MXRT700). | ||
| Among currently supported machine learning models are: | ||
| - Convolution-based neutral networks | ||
| - Full support for MobileNetv2 and CifarNet | ||
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| ## Prerequisites (Hardware and Software) | ||
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| In order to succesfully build executorch project and convert models for NXP eIQ Neutron Backend you will need a computer running Windows or Linux. | ||
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| If you want to test the runtime, you'll also need: | ||
| - Hardware with NXP's [i.MXRT700](https://www.nxp.com/products/i.MX-RT700) chip or a testing board like MIMXRT700-AVK | ||
| - [MCUXpresso IDE](https://www.nxp.com/design/design-center/software/development-software/mcuxpresso-software-and-tools-/mcuxpresso-integrated-development-environment-ide:MCUXpresso-IDE) or [MCUXpresso Visual Studio Code extension](https://www.nxp.com/design/design-center/software/development-software/mcuxpresso-software-and-tools-/mcuxpresso-for-visual-studio-code:MCUXPRESSO-VSC) | ||
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| ## Using NXP backend | ||
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| To test converting a neural network model for inference on NXP eIQ Neutron Backend, you can use our example script: | ||
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| ```shell | ||
| # cd to the root of executorch repository | ||
| ./examples/nxp/aot_neutron_compile.sh [model (cifar10 or mobilenetv2)] | ||
| ``` | ||
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| For a quick overview how to convert a custom PyTorch model, take a look at our [exmple python script](https://github.com/pytorch/executorch/tree/release/1.0/examples/nxp/aot_neutron_compile.py). | ||
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| ## Runtime Integration | ||
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| To learn how to run the converted model on the NXP hardware, use one of our example projects on using executorch runtime from MCUXpresso IDE example projects list. | ||
| For more finegrained tutorial, visit [this manual page](https://mcuxpresso.nxp.com/mcuxsdk/latest/html/middleware/eiq/executorch/docs/nxp/topics/example_applications.html). |
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We just did a big refactoring (and will cherry-pick onto release/1.0 branch soon)
#14720
here's the preview:
https://docs.pytorch.org/executorch/main/
Please rebase to latest main and change appropriately.
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I was not sure if the new look of documentation is supposed to be a part of the release so I raised PRs to both main and release/1.0. I am closing this one since the PR to main was merged already.