fbd5a57f93
* add windows user guide * modifiy win user guides * Add jupyter setup guide and known issues * Add tips for yolov3 example * update win guide * update win guide * update win guide reference * update win guide reference * update win guide reference * format fix * revise nano and chronos windows guide * fix windows guide reference in nano install Co-authored-by: aixideng <aixi.deng@intel.com>
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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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TensorFlow
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~~~~~~~~~~~~~~~~~~~~~~~~~
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* `How to accelerate a TensorFlow Keras application on training workloads through multiple instances <Training/TensorFlow/accelerate_tensorflow_training_multi_instance.html>`_
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* |tensorflow_training_embedding_sparseadam_link|_
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.. |tensorflow_training_embedding_sparseadam_link| replace:: How to optimize your model with a sparse ``Embedding`` layer and ``SparseAdam`` optimizer
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.. _tensorflow_training_embedding_sparseadam_link: Training/TensorFlow/tensorflow_training_embedding_sparseadam.html
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.. toctree::
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:maxdepth: 1
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:hidden:
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Training/TensorFlow/accelerate_tensorflow_training_multi_instance
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Training/TensorFlow/tensorflow_training_embedding_sparseadam
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General
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~~~~~~~~~~~~~~~~~~~~~~~~~
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* `How to choose the number of processes for multi-instance training <Training/General/choose_num_processes_training.html>`_
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.. toctree::
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:maxdepth: 1
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:hidden:
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Training/General/choose_num_processes_training
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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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* `How to install BigDL-Nano on Windows <windows_guide.html>`_
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.. toctree::
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:maxdepth: 1
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:hidden:
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install_in_colab
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windows_guide |