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Restructure ET documentation with 'Platform First' model (#14720)
### Summary [PLEASE REMOVE] See [CONTRIBUTING.md's Pull Requests](https://github.com/pytorch/executorch/blob/main/CONTRIBUTING.md#pull-requests) for ExecuTorch PR guidelines. [PLEASE REMOVE] If this PR closes an issue, please add a `Fixes #<issue-id>` line. [PLEASE REMOVE] If this PR introduces a fix or feature that should be the upcoming release notes, please add a "Release notes: <area>" label. For a list of available release notes labels, check out [CONTRIBUTING.md's Pull Requests](https://github.com/pytorch/executorch/blob/main/CONTRIBUTING.md#pull-requests). ### Test plan [PLEASE REMOVE] How did you test this PR? Please write down any manual commands you used and note down tests that you have written if applicable.
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‎docs/source/advanced-topics-section.md‎

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(advanced-topics-section)=
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# Advanced
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Deep dive into ExecuTorch's advanced features for optimization, customization, and integration.
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This section covers advanced concepts for developers who need to customize ExecuTorch for specific use cases, optimize performance, or integrate with custom hardware backends.
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## Quantization & Optimization
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Techniques for model compression and performance optimization.
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**→ {doc}`quantization-optimization` — Quantization strategies and performance optimization**
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Key topics:
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- Quantization strategies and techniques
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- Performance profiling and optimization
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## Model Export
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Learn the core ExecuTorch workflow, exporting PyTorch models to the `.pte` format for edge deployment.
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**→ {doc}`using-executorch-export`** - Model Export & Lowering
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Key topics:
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- Export and Lowering Workflow
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- Hardware Backend Selection & Optimization
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- Dynamic Shapes & Advanced Model Features
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## Kernel Library
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Deep dive into ExecuTorch's kernel implementation and customization.
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**→ {doc}`kernel-library-advanced` — Kernel library deep dive and customization**
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Key topics:
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- Kernel library architecture
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- Custom kernel implementation
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- Selective build and optimization
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## Backend & Delegates
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**→ {doc}`backend-delegate-advanced` — Backend delegate integration**
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Key topics:
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- Learn how to integrate Backend Delegate into ExecuTorch and more
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- XNNPACK Delegate Internals
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- Debugging Delegation
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## Runtime & Integration
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Advanced runtime features and backend integration.
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**→ {doc}`runtime-integration-advanced` — Runtime customization and backend integration**
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Key topics:
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- Backend delegate implementation
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- Platform abstraction layer
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- Custom runtime integration
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## Compiler & IR
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Advanced compiler features and intermediate representation details.
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**→ {doc}`compiler-ir-advanced` — Compiler passes and IR specification**
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Key topics:
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- Custom compiler passes
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- Memory planning strategies
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- Backend dialect and EXIR
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- Ops set definition
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## File Formats
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ExecuTorch file format specifications and internals.
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**→ {doc}`file-formats-advanced` — PTE and PTD file format specifications**
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Key topics:
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- PTE file format internals
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- PTD file format specification
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- Custom file format handling
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## Next Steps
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After exploring advanced topics:
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- **{doc}`tools-sdk-section`** - Developer tools for debugging and profiling
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- **{doc}`api-section`** - Complete API reference documentation
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```{toctree}
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:hidden:
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:maxdepth: 2
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:caption: Advanced Topics
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quantization-optimization
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using-executorch-export
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kernel-library-advanced
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backend-delegate-advanced
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runtime-integration-advanced
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compiler-ir-advanced
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file-formats-advanced

‎docs/source/android-arm-vgf.md‎

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```{include} backends-arm-vgf.md

‎docs/source/android-backends.md‎

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(android-backends)=
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# Backends
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Available hardware acceleration backends for Android deployment.
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## CPU Acceleration
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- {doc}`android-xnnpack` — XNNPACK CPU acceleration
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## GPU Acceleration
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- {doc}`android-vulkan` — Vulkan GPU acceleration
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## NPU/Accelerator Backends
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- {doc}`android-qualcomm` — Qualcomm AI Engine (NPU)
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- {doc}`android-mediatek` — MediaTek NPU acceleration
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- {doc}`android-arm-vgf` — ARM VGF Backend
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- {doc}`android-samsung-exynos` — Samsung Exynos NPU
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```{toctree}
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:hidden:
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android-xnnpack
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android-vulkan
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android-qualcomm
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android-mediatek
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android-arm-vgf
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android-samsung-exynos

‎docs/source/android-examples.md‎

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# Examples & Demos
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- [Working with LLMs - Android Examples](https://github.com/meta-pytorch/executorch-examples/tree/main/llm/android)
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- [Demo Apps](https://github.com/meta-pytorch/executorch-examples/tree/main/dl3/android/DeepLabV3Demo#executorch-android-demo-app)
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- {doc}`tutorial-arm-vgf` — Export a simple PyTorch model for the ExecuTorch VGF backend
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```{toctree}
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:hidden:
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tutorial-arm-vgf

‎docs/source/android-mediatek.md‎

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```{include} backends-mediatek.md

‎docs/source/android-qualcomm.md‎

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```{include} backends-qualcomm.md

‎docs/source/android-samsung-exynos.md‎

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```{include} backends-samsung-exynos.md

‎docs/source/android-section.md‎

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(android-section)=
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# Android
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Deploy ExecuTorch on Android devices with hardware acceleration support.
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## Quick Start & Integration
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- {doc}`using-executorch-android` — Complete Android integration guide
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## Backends
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- {doc}`android-backends` — Available Android backends and acceleration options
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## Examples & Demos
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- {doc}`android-examples` — Explore Android Examples & Demos
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```{toctree}
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:hidden:
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using-executorch-android
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android-backends
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android-examples

‎docs/source/android-vulkan.md‎

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```{include} backends-vulkan.md

‎docs/source/android-xnnpack.md‎

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```{include} backends-xnnpack.md

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