Prototype features are not available as part of binary distributions like PyPI or Conda (except maybe behind run-time flags). To test these features we would, depending on the feature, recommend building from master or using the nightly wheels that are made available on pytorch.org.
Level of commitment: We are committing to gathering high bandwidth feedback only on these features. Based on this feedback and potential further engagement between community members, we as a community will decide if we want to upgrade the level of commitment or to fail fast.
.. customcarditem:: :header: FX Graph Mode Quantization User Guide :card_description: Learn about FX Graph Mode Quantization. :image: ../_static/img/thumbnails/cropped/generic-pytorch-logo.png :link: ../prototype/fx_graph_mode_quant_guide.html :tags: FX,Quantization
.. customcarditem:: :header: FX Graph Mode Post Training Dynamic Quantization :card_description: Learn how to do post training dynamic quantization in graph mode based on torch.fx. :image: ../_static/img/thumbnails/cropped/generic-pytorch-logo.png :link: ../prototype/fx_graph_mode_ptq_dynamic.html :tags: FX,Quantization
.. customcarditem:: :header: FX Graph Mode Post Training Static Quantization :card_description: Learn how to do post training static quantization in graph mode based on torch.fx. :image: ../_static/img/thumbnails/cropped/generic-pytorch-logo.png :link: ../prototype/fx_graph_mode_ptq_static.html :tags: FX,Quantization
.. customcarditem:: :header: Graph Mode Dynamic Quantization on BERT :card_description: Learn how to do post training dynamic quantization with graph mode quantization on BERT models. :image: ../_static/img/thumbnails/cropped/graph-mode-dynamic-bert.png :link: ../prototype/graph_mode_dynamic_bert_tutorial.html :tags: Text,Quantization
.. customcarditem:: :header: PyTorch Numeric Suite Tutorial :card_description: Learn how to use the PyTorch Numeric Suite to support quantization debugging efforts. :image: ../_static/img/thumbnails/cropped/generic-pytorch-logo.png :link: ../prototype/numeric_suite_tutorial.html :tags: Debugging,Quantization
.. customcarditem:: :header: Use iOS GPU in PyTorch :card_description: Learn how to run your models on iOS GPU. :image: ../_static/img/thumbnails/cropped/ios.png :link: ../prototype/ios_gpu_workflow.html :tags: Mobile
.. customcarditem:: :header: Convert MobileNetV2 to NNAPI :card_description: Learn how to prepare a computer vision model to use Android’s Neural Networks API (NNAPI). :image: ../_static/img/thumbnails/cropped/android.png :link: ../prototype/nnapi_mobilenetv2.html :tags: Mobile
.. customcarditem:: :header: PyTorch Vulkan Backend User Workflow :card_description: Learn how to use the Vulkan backend on mobile GPUs. :image: ../_static/img/thumbnails/cropped/android.png :link: ../prototype/vulkan_workflow.html :tags: Mobile
.. customcarditem:: :header: Tracing-based Selective Build Mobile Interpreter in Android and iOS :card_description: Learn how to optimize the mobile interpreter size with a tracing-based selective build. :image: ../_static/img/thumbnails/cropped/mobile.png :link: ../prototype/tracing_based_selective_build.html :tags: Mobile
.. customcarditem:: :header: Convert Mobilenetv2 to Core ML :card_description: Learn how to prepare a computer vision model to use the PyTorch Core ML mobile backend. :image: ../_static/img/thumbnails/cropped/ios.png :link: ../prototype/ios_coreml_workflow.html :tags: Mobile
.. customcarditem:: :header: Skipping Module Parameter Initialization in PyTorch 1.10 :card_description: Describes skipping parameter initialization during module construction in PyTorch 1.10, avoiding wasted computation. :image: ../_static/img/thumbnails/cropped/generic-pytorch-logo.png :link: ../prototype/skip_param_init.html :tags: Modules
.. customcarditem:: :header: Model Freezing in TorchScript :card_description: Freezing is the process of inlining Pytorch module parameters and attributes values into the TorchScript internal representation. :image: ../_static/img/thumbnails/cropped/generic-pytorch-logo.png :link: ../prototype/torchscript_freezing.html :tags: TorchScript
.. customcarditem:: :header: Using torch.vmap :card_description: Learn about torch.vmap, an autovectorizer for PyTorch operations. :image: ../_static/img/thumbnails/cropped/generic-pytorch-logo.png :link: ../prototype/vmap_recipe.html :tags: vmap
.. toctree:: :hidden: prototype/fx_graph_mode_quant_guide.html prototype/fx_graph_mode_ptq_dynamic.html prototype/fx_graph_mode_ptq_static.html prototype/graph_mode_dynamic_bert_tutorial.html prototype/ios_gpu_workflow.html prototype/nnapi_mobilenetv2.html prototype/tracing_based_selective_build.html prototype/ios_coreml_workflow.html prototype/numeric_suite_tutorial.html prototype/torchscript_freezing.html prototype/vmap_recipe.html prototype/vulkan_workflow.html