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Copy file name to clipboardExpand all lines: _templates/layout.html
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</noscript>
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<scripttype="text/javascript">
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varcollapsedSections=['PyTorch Recipes','Learning PyTorch','Image and Video','Audio','Text','Backends','Reinforcement Learning','Deploying PyTorch Models in Production','Code Transforms with FX','Frontend APIs','Extending PyTorch','Model Optimization','Parallel and Distributed Training','Mobile'];
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varcollapsedSections=['PyTorch Recipes','Learning PyTorch','Image and Video','Audio','Text','Backends','Reinforcement Learning','Deploying PyTorch Models in Production','Profiling PyTorch','Code Transforms with FX','Frontend APIs','Extending PyTorch','Model Optimization','Parallel and Distributed Training','Edge with ExecuTorch','Recommendation Systems','Multimodality'];
:card_description: Learn how to use Facebook Data-efficient Image Transformers DeiT and script and optimize it for mobile.
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:image: _static/img/thumbnails/cropped/mobile.png
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:link: beginner/vt_tutorial.html
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:tags: Model-Optimization,Best-Practice,Mobile
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.. customcarditem::
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:header: Parametrizations Tutorial
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:card_description: Learn how to use torch.nn.utils.parametrize to put constraints on your parameters (e.g. make them orthogonal, symmetric positive definite, low-rank...)
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:link: intermediate/FSDP_adavnced_tutorial.html
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:tags: Parallel-and-Distributed-Training
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..Mobile
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..Edge
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.. customcarditem::
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:header:Image Segmentation DeepLabV3 on iOS
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:card_description:A comprehensive step-by-step tutorial on how to prepare and run the PyTorch DeepLabV3 image segmentation model on iOS.
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:image: _static/img/thumbnails/cropped/ios.png
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:link:beginner/deeplabv3_on_ios.html
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:tags:Mobile
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:header:Exporting to ExecuTorch Tutorial
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:card_description:Learn about how to use ExecuTorch, a unified ML stack for lowering PyTorch models to edge devices.
:card_description: Explore how to set up the ExecuTorch iOS Demo App, which uses the MobileNet v3 model to process live camera images leveraging three different backends: XNNPACK, Core ML, and Metal Performance Shaders (MPS).
:card_description: Learn how to set up the ExecuTorch Android Demo App for image segmentation tasks using the DeepLab v3 model and XNNPACK FP32 backend.
:card_description: Learn to accelerate your program using ExecuTorch by applying delegates through three methods: lowering the whole module, composing it with another module, and partitioning parts of a module.
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