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[Nano] How-To Guides: Training - PyTorch Lightning (#5643)

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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
This commit is contained in:
Yuwen Hu 2022-09-15 15:26:11 +08:00 committed by GitHub
parent 528ff064f5
commit 12c12a1058
14 changed files with 60 additions and 21 deletions
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docs/readthedocs/source/doc/Nano/Howto/Inference/PyTorch/accelerate_pytorch_inference_onnx.nblink Normal file
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{
"path": "../../../../../../../../python/nano/tutorial/notebook/inference/pytorch/accelerate_pytorch_inference_onnx.ipynb"
}

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"path": "../../../../../../../../python/nano/tutorial/notebook/inference/pytorch/accelerate_pytorch_inference_openvino.ipynb"
}

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"path": "../../../../../../../../python/nano/tutorial/notebook/inference/pytorch/quantize_pytorch_inference_inc.ipynb"
}

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"path": "../../../../../../../../python/nano/tutorial/notebook/inference/pytorch/quantize_pytorch_inference_pot.ipynb"
}

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"path": "../../../../../../../../python/nano/tutorial/notebook/training/pytorch-lightning/accelerate_pytorch_lightning_training_ipex.ipynb"
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"path": "../../../../../../../../python/nano/tutorial/notebook/training/pytorch-lightning/accelerate_pytorch_lightning_training_multi_instance.ipynb"
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"path": "../../../../../../../../python/nano/tutorial/notebook/training/pytorch-lightning/pytorch_lightning_cv_data_pipeline.ipynb"
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"path": "../../../../../../../../python/nano/tutorial/notebook/training/pytorch-lightning/pytorch_lightning_training_bf16.ipynb"
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"path": "../../../../../../../../python/nano/tutorial/notebook/training/pytorch-lightning/pytorch_lightning_training_channels_last.ipynb"
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"path": "../../../../../../python/nano/tutorial/notebook/inference/pytorch/accelerate_pytorch_inference_onnx.ipynb"
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"path": "../../../../../../python/nano/tutorial/notebook/inference/pytorch/accelerate_pytorch_inference_openvino.ipynb"
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docs/readthedocs/source/doc/Nano/Howto/index.rst
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@ -5,22 +5,46 @@ Nano How-to Guides
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.
PyTorch Inference
Training Optimization
-------------------------
* `How to accelerate a PyTorch inference pipeline through ONNXRuntime <accelerate_pytorch_inference_onnx.html>`_
* `How to accelerate a PyTorch inference pipeline through OpenVINO <accelerate_pytorch_inference_openvino.html>`_
* `How to quantize your PyTorch model for inference using Intel Neural Compressor <quantize_pytorch_inference_inc.html>`_
* `How to quantize your PyTorch model for inference using OpenVINO Post-training Optimization Tools <quantize_pytorch_inference_pot.html>`_
PyTorch Lightning
~~~~~~~~~~~~~~~~~~~~~~~~~
* `How to accelerate a PyTorch Lightning application on training workloads through Intel® Extension for PyTorch* <Training/PyTorchLightning/accelerate_pytorch_lightning_training_ipex.html>`_
* `How to accelerate a PyTorch Lightning application on training workloads through multiple instances <Training/PyTorchLightning/accelerate_pytorch_lightning_training_multi_instance.html>`_
* `How to use the channels last memory format in your PyTorch Lightning application for training <Training/PyTorchLightning/pytorch_lightning_training_channels_last.html>`_
* `How to conduct BFloat16 Mixed Precision training in your PyTorch Lightning application <Training/PyTorchLightning/pytorch_lightning_training_bf16.html>`_
* `How to accelerate a computer vision data processing pipeline <Training/PyTorchLightning/pytorch_lightning_cv_data_pipeline.html>`_
.. toctree::
:maxdepth: 1
:hidden:
accelerate_pytorch_inference_onnx
accelerate_pytorch_inference_openvino
quantize_pytorch_inference_inc
quantize_pytorch_inference_pot
Training/PyTorchLightning/accelerate_pytorch_lightning_training_ipex
Training/PyTorchLightning/accelerate_pytorch_lightning_training_multi_instance
Training/PyTorchLightning/pytorch_lightning_training_channels_last
Training/PyTorchLightning/pytorch_lightning_training_bf16
Training/PyTorchLightning/pytorch_lightning_cv_data_pipeline
Inference Optimization
-------------------------
PyTorch
~~~~~~~~~~~~~~~~~~~~~~~~~
* `How to accelerate a PyTorch inference pipeline through ONNXRuntime <Inference/PyTorch/accelerate_pytorch_inference_onnx.html>`_
* `How to accelerate a PyTorch inference pipeline through OpenVINO <Inference/PyTorch/accelerate_pytorch_inference_openvino.html>`_
* `How to quantize your PyTorch model for inference using Intel Neural Compressor <Inference/PyTorch/quantize_pytorch_inference_inc.html>`_
* `How to quantize your PyTorch model for inference using OpenVINO Post-training Optimization Tools <Inference/PyTorch/quantize_pytorch_inference_pot.html>`_
.. toctree::
:maxdepth: 1
:hidden:
Inference/PyTorch/accelerate_pytorch_inference_onnx
Inference/PyTorch/accelerate_pytorch_inference_openvino
Inference/PyTorch/quantize_pytorch_inference_inc
Inference/PyTorch/quantize_pytorch_inference_pot
Install
-------------------------

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{
"path": "../../../../../../python/nano/tutorial/notebook/inference/pytorch/quantize_pytorch_inference_inc.ipynb"
}

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{
"path": "../../../../../../python/nano/tutorial/notebook/inference/pytorch/quantize_pytorch_inference_pot.ipynb"
}