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* Rearrange file structure for PyTorch Inference for docs and add titles for PyTorch-Lightning Training * Add How-to guide: How to accelerate a PyTorch-Lightning application on training workloads through Intel® Extension for PyTorch* * Add how-to guide: How to accelerate a PyTorch-Lightning application on training workloads through multiple instances * Revise: remove '-' in 'PyTorch-Lightning' and some other changes * Add How-to guides: How to use the channels last memory format in your PyTorch Lightning application for training * Add how-to guide: Use BFloat16 Mixed Precision for PyTorch Lightning Training * Add How-to guide: How to accelerate a computer vision data processing pipeline * Small Revision: change comments in several code cells * Disable other nano tests temporarily * Add github action tests for Nano Training PyTorch Lightning tests * Enable other nano tests again * Small revisions: typos and explanation texts changes * Revise: update based on comments
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Nano How-to Guides
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=========================
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.. note::
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This page is still a work in progress. We are adding more guides.
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In Nano How-to Guides, you could expect to find multiple task-oriented, bite-sized, and executable examples. These examples will show you various tasks that BigDL-Nano could help you accomplish smoothly.
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Training Optimization
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-------------------------
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PyTorch Lightning
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~~~~~~~~~~~~~~~~~~~~~~~~~
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* `How to accelerate a PyTorch Lightning application on training workloads through Intel® Extension for PyTorch* <Training/PyTorchLightning/accelerate_pytorch_lightning_training_ipex.html>`_
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* `How to accelerate a PyTorch Lightning application on training workloads through multiple instances <Training/PyTorchLightning/accelerate_pytorch_lightning_training_multi_instance.html>`_
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* `How to use the channels last memory format in your PyTorch Lightning application for training <Training/PyTorchLightning/pytorch_lightning_training_channels_last.html>`_
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* `How to conduct BFloat16 Mixed Precision training in your PyTorch Lightning application <Training/PyTorchLightning/pytorch_lightning_training_bf16.html>`_
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* `How to accelerate a computer vision data processing pipeline <Training/PyTorchLightning/pytorch_lightning_cv_data_pipeline.html>`_
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.. toctree::
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:maxdepth: 1
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:hidden:
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Training/PyTorchLightning/accelerate_pytorch_lightning_training_ipex
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Training/PyTorchLightning/accelerate_pytorch_lightning_training_multi_instance
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Training/PyTorchLightning/pytorch_lightning_training_channels_last
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Training/PyTorchLightning/pytorch_lightning_training_bf16
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Training/PyTorchLightning/pytorch_lightning_cv_data_pipeline
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Inference Optimization
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-------------------------
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PyTorch
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~~~~~~~~~~~~~~~~~~~~~~~~~
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* `How to accelerate a PyTorch inference pipeline through ONNXRuntime <Inference/PyTorch/accelerate_pytorch_inference_onnx.html>`_
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* `How to accelerate a PyTorch inference pipeline through OpenVINO <Inference/PyTorch/accelerate_pytorch_inference_openvino.html>`_
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* `How to quantize your PyTorch model for inference using Intel Neural Compressor <Inference/PyTorch/quantize_pytorch_inference_inc.html>`_
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* `How to quantize your PyTorch model for inference using OpenVINO Post-training Optimization Tools <Inference/PyTorch/quantize_pytorch_inference_pot.html>`_
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.. toctree::
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:maxdepth: 1
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:hidden:
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Inference/PyTorch/accelerate_pytorch_inference_onnx
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Inference/PyTorch/accelerate_pytorch_inference_openvino
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Inference/PyTorch/quantize_pytorch_inference_inc
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Inference/PyTorch/quantize_pytorch_inference_pot
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Install
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-------------------------
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* `How to install BigDL-Nano in Google Colab <install_in_colab.html>`_
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.. toctree::
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:maxdepth: 1
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:hidden:
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install_in_colab |