[Nano] Improve How-to Guides Navigations (#7396)
* Remove deprecated option enable_auto_doc_ref for recommonmark * Add first level navigation structure for Nano how-to guides * Update navigation for How-to Training part * Update navigation for How-to Inference part * Update navigation for How-to Preprocessing/Install part and other small fixes * Fix wrong link path caused by position changes of how-to install related guides * Small fix
This commit is contained in:
Yuwen Hu
GitHub
parent
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commit
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18 changed files with 252 additions and 42 deletions
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@ -101,43 +101,87 @@ subtrees:
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title: "How-to Guides"
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Preprocessing/PyTorch/accelerate_pytorch_cv_data_pipeline
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- file: doc/Nano/Howto/Training/PyTorchLightning/accelerate_pytorch_lightning_training_ipex
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- file: doc/Nano/Howto/Training/PyTorchLightning/accelerate_pytorch_lightning_training_multi_instance
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- file: doc/Nano/Howto/Training/PyTorchLightning/pytorch_lightning_training_channels_last
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- file: doc/Nano/Howto/Training/PyTorchLightning/pytorch_lightning_training_bf16
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- file: doc/Nano/Howto/Training/PyTorch/convert_pytorch_training_torchnano
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- file: doc/Nano/Howto/Training/PyTorch/use_nano_decorator_pytorch_training
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- file: doc/Nano/Howto/Training/PyTorch/accelerate_pytorch_training_ipex
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- file: doc/Nano/Howto/Training/PyTorch/accelerate_pytorch_training_multi_instance
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- file: doc/Nano/Howto/Training/PyTorch/pytorch_training_channels_last
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- file: doc/Nano/Howto/Training/PyTorch/accelerate_pytorch_training_bf16
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- file: doc/Nano/Howto/Training/TensorFlow/accelerate_tensorflow_training_multi_instance
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- file: doc/Nano/Howto/Training/TensorFlow/tensorflow_training_embedding_sparseadam
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- file: doc/Nano/Howto/Training/TensorFlow/tensorflow_training_bf16
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- file: doc/Nano/Howto/Training/General/choose_num_processes_training
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- file: doc/Nano/Howto/Inference/OpenVINO/openvino_inference
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- file: doc/Nano/Howto/Inference/OpenVINO/openvino_inference_async
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- file: doc/Nano/Howto/Inference/OpenVINO/accelerate_inference_openvino_gpu
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- file: doc/Nano/Howto/Inference/PyTorch/accelerate_pytorch_inference_onnx
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- file: doc/Nano/Howto/Inference/PyTorch/accelerate_pytorch_inference_openvino
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- file: doc/Nano/Howto/Inference/PyTorch/accelerate_pytorch_inference_jit_ipex
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- file: doc/Nano/Howto/Inference/PyTorch/multi_instance_pytorch_inference
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- file: doc/Nano/Howto/Inference/PyTorch/quantize_pytorch_inference_inc
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- file: doc/Nano/Howto/Inference/PyTorch/quantize_pytorch_inference_pot
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- file: doc/Nano/Howto/Inference/PyTorch/pytorch_context_manager
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- file: doc/Nano/Howto/Inference/PyTorch/pytorch_save_and_load_ipex
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- file: doc/Nano/Howto/Inference/PyTorch/pytorch_save_and_load_jit
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- file: doc/Nano/Howto/Inference/PyTorch/pytorch_save_and_load_onnx
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- file: doc/Nano/Howto/Inference/PyTorch/pytorch_save_and_load_openvino
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- file: doc/Nano/Howto/Inference/PyTorch/inference_optimizer_optimize
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- file: doc/Nano/Howto/Inference/TensorFlow/accelerate_tensorflow_inference_onnx
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- file: doc/Nano/Howto/Inference/TensorFlow/accelerate_tensorflow_inference_openvino
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- file: doc/Nano/Howto/Inference/TensorFlow/tensorflow_inference_bf16
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- file: doc/Nano/Howto/Inference/TensorFlow/tensorflow_save_and_load_onnx
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- file: doc/Nano/Howto/Inference/TensorFlow/tensorflow_save_and_load_openvino
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- file: doc/Nano/Howto/install_in_colab
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- file: doc/Nano/Howto/windows_guide
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- file: doc/Nano/Howto/Preprocessing/index
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Preprocessing/PyTorch/index
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title: "PyTorch"
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Preprocessing/PyTorch/accelerate_pytorch_cv_data_pipeline
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- file: doc/Nano/Howto/Training/index
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Training/PyTorchLightning/index
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title: "PyTorch Lightning"
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Training/PyTorchLightning/accelerate_pytorch_lightning_training_ipex
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- file: doc/Nano/Howto/Training/PyTorchLightning/accelerate_pytorch_lightning_training_multi_instance
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- file: doc/Nano/Howto/Training/PyTorchLightning/pytorch_lightning_training_channels_last
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- file: doc/Nano/Howto/Training/PyTorchLightning/pytorch_lightning_training_bf16
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- file: doc/Nano/Howto/Training/PyTorch/index
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title: "PyTorch"
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Training/PyTorch/convert_pytorch_training_torchnano
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- file: doc/Nano/Howto/Training/PyTorch/use_nano_decorator_pytorch_training
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- file: doc/Nano/Howto/Training/PyTorch/accelerate_pytorch_training_ipex
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- file: doc/Nano/Howto/Training/PyTorch/accelerate_pytorch_training_multi_instance
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- file: doc/Nano/Howto/Training/PyTorch/pytorch_training_channels_last
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- file: doc/Nano/Howto/Training/PyTorch/accelerate_pytorch_training_bf16
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- file: doc/Nano/Howto/Training/TensorFlow/index
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title: "TensorFlow"
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Training/TensorFlow/accelerate_tensorflow_training_multi_instance
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- file: doc/Nano/Howto/Training/TensorFlow/tensorflow_training_embedding_sparseadam
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- file: doc/Nano/Howto/Training/TensorFlow/tensorflow_training_bf16
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- file: doc/Nano/Howto/Training/General/index
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title: "General"
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Training/General/choose_num_processes_training
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- file: doc/Nano/Howto/Inference/index
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Inference/OpenVINO/index
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title: "OpenVINO"
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Inference/OpenVINO/openvino_inference
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- file: doc/Nano/Howto/Inference/OpenVINO/openvino_inference_async
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- file: doc/Nano/Howto/Inference/OpenVINO/accelerate_inference_openvino_gpu
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- file: doc/Nano/Howto/Inference/PyTorch/index
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title: "PyTorch"
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Inference/PyTorch/accelerate_pytorch_inference_onnx
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- file: doc/Nano/Howto/Inference/PyTorch/accelerate_pytorch_inference_openvino
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- file: doc/Nano/Howto/Inference/PyTorch/accelerate_pytorch_inference_jit_ipex
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- file: doc/Nano/Howto/Inference/PyTorch/multi_instance_pytorch_inference
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- file: doc/Nano/Howto/Inference/PyTorch/quantize_pytorch_inference_inc
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- file: doc/Nano/Howto/Inference/PyTorch/quantize_pytorch_inference_pot
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- file: doc/Nano/Howto/Inference/PyTorch/pytorch_context_manager
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- file: doc/Nano/Howto/Inference/PyTorch/pytorch_save_and_load_ipex
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- file: doc/Nano/Howto/Inference/PyTorch/pytorch_save_and_load_jit
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- file: doc/Nano/Howto/Inference/PyTorch/pytorch_save_and_load_onnx
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- file: doc/Nano/Howto/Inference/PyTorch/pytorch_save_and_load_openvino
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- file: doc/Nano/Howto/Inference/PyTorch/inference_optimizer_optimize
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- file: doc/Nano/Howto/Inference/TensorFlow/index
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title: "TensorFlow"
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Inference/TensorFlow/accelerate_tensorflow_inference_onnx
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- file: doc/Nano/Howto/Inference/TensorFlow/accelerate_tensorflow_inference_openvino
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- file: doc/Nano/Howto/Inference/TensorFlow/tensorflow_inference_bf16
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- file: doc/Nano/Howto/Inference/TensorFlow/tensorflow_save_and_load_onnx
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- file: doc/Nano/Howto/Inference/TensorFlow/tensorflow_save_and_load_openvino
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- file: doc/Nano/Howto/Install/index
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subtrees:
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- entries:
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- file: doc/Nano/Howto/Install/install_in_colab
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- file: doc/Nano/Howto/Install/windows_guide
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- file: doc/Nano/Overview/known_issues
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title: "Tips and Known Issues"
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- file: doc/Nano/Overview/troubshooting
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@ -269,8 +269,7 @@ def setup(app):
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'auto_toc_tree_section': 'Contents',
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'enable_math': False,
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'enable_inline_math': False,
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'enable_eval_rst': True,
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'enable_auto_doc_ref': True,
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'enable_eval_rst': True
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}, True)
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app.add_transform(AutoStructify)
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@ -0,0 +1,6 @@
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Inference Optimization: For OpenVINO Users
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=============================================
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* `How to run inference on OpenVINO model <openvino_inference.html>`_
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* `How to run asynchronous inference on OpenVINO model <openvino_inference_async.html>`_
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* `How to accelerate a PyTorch / TensorFlow inference pipeline on Intel GPUs through OpenVINO <accelerate_inference_openvino_gpu.html>`_
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Inference Optimization: For PyTorch Users
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=============================================
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* `How to accelerate a PyTorch inference pipeline through ONNXRuntime <accelerate_pytorch_inference_onnx.html>`_
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* `How to accelerate a PyTorch inference pipeline through OpenVINO <accelerate_pytorch_inference_openvino.html>`_
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* `How to accelerate a PyTorch inference pipeline through JIT/IPEX <accelerate_pytorch_inference_jit_ipex.html>`_
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* `How to accelerate a PyTorch inference pipeline through multiple instances <multi_instance_pytorch_inference.html>`_
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* `How to quantize your PyTorch model for inference using Intel Neural Compressor <quantize_pytorch_inference_inc.html>`_
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* `How to quantize your PyTorch model for inference using OpenVINO Post-training Optimization Tools <quantize_pytorch_inference_pot.html>`_
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* |pytorch_inference_context_manager_link|_
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* `How to save and load optimized IPEX model <pytorch_save_and_load_ipex.html>`_
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* `How to save and load optimized JIT model <pytorch_save_and_load_jit.html>`_
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* `How to save and load optimized ONNXRuntime model <pytorch_save_and_load_onnx.html>`_
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* `How to save and load optimized OpenVINO model <pytorch_save_and_load_openvino.html>`_
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* `How to find accelerated method with minimal latency using InferenceOptimizer <inference_optimizer_optimize.html>`_
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.. |pytorch_inference_context_manager_link| replace:: How to use context manager through ``get_context``
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.. _pytorch_inference_context_manager_link: pytorch_context_manager.html
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Inference Optimization: For TensorFlow Users
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=============================================
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* `How to accelerate a TensorFlow inference pipeline through ONNXRuntime <accelerate_tensorflow_inference_onnx.html>`_
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* `How to accelerate a TensorFlow inference pipeline through OpenVINO <accelerate_tensorflow_inference_openvino.html>`_
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* `How to conduct BFloat16 Mixed Precision inference in a TensorFlow Keras application <tensorflow_inference_bf16.html>`_
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* `How to save and load optimized ONNXRuntime model in TensorFlow <tensorflow_save_and_load_onnx.html>`_
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* `How to save and load optimized OpenVINO model in TensorFlow <tensorflow_save_and_load_openvino.html>`_
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33
docs/readthedocs/source/doc/Nano/Howto/Inference/index.rst
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33
docs/readthedocs/source/doc/Nano/Howto/Inference/index.rst
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Inference Optimization
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=========================
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Here you could find detailed guides on how to apply BigDL-Nano to optimize your inference workloads. Select your desired use case below for further navigation:
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.. grid:: 1 2 2 2
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.. grid-item::
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.. button-link:: OpenVINO/index.html
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:color: primary
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:expand:
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:outline:
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I use **OpenVINO** toolkit.
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.. grid-item::
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.. button-link:: PyTorch/index.html
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:color: primary
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:expand:
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:outline:
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I am a **PyTorch** user.
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.. grid-item::
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.. button-link:: TensorFlow/index.html
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:color: primary
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:expand:
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:outline:
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I am a **TensorFlow** user.
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7
docs/readthedocs/source/doc/Nano/Howto/Install/index.rst
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7
docs/readthedocs/source/doc/Nano/Howto/Install/index.rst
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Install
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=========================
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Here you could find detailed guides on how to install BigDL-Nano for different use cases:
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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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Preprocessing Optimization: For PyTorch Users
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==============================================
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* `How to accelerate a computer vision data processing pipeline <accelerate_pytorch_cv_data_pipeline.html>`_
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Preprocessing Optimization
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===========================
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Here you could find detailed guides on how to apply BigDL-Nano to accelerate your data preprocess pipeline. Select your desired use case below for further navigation:
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.. grid:: 1 2 2 2
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.. grid-item::
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.. button-link:: PyTorch/index.html
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:color: primary
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:expand:
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:outline:
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I am a **PyTorch** user.
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Training Optimization: General Tips
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====================================
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* `How to choose the number of processes for multi-instance training <choose_num_processes_training.html>`_
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Training Optimization: For PyTorch Users
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=========================================
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* |convert_pytorch_training_torchnano|_
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* |use_nano_decorator_pytorch_training|_
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* `How to accelerate a PyTorch application on training workloads through Intel® Extension for PyTorch* <accelerate_pytorch_training_ipex.html>`_
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* `How to accelerate a PyTorch application on training workloads through multiple instances <accelerate_pytorch_training_multi_instance.html>`_
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* `How to use the channels last memory format in your PyTorch application for training <pytorch_training_channels_last.html>`_
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* `How to conduct BFloat16 Mixed Precision training in your PyTorch application <accelerate_pytorch_training_bf16.html>`_
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.. |use_nano_decorator_pytorch_training| replace:: How to accelerate your PyTorch training loop with ``@nano`` decorator
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.. _use_nano_decorator_pytorch_training: use_nano_decorator_pytorch_training.html
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.. |convert_pytorch_training_torchnano| replace:: How to convert your PyTorch training loop to use ``TorchNano`` for acceleration
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.. _convert_pytorch_training_torchnano: convert_pytorch_training_torchnano.html
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Training Optimization: For PyTorch Lightning Users
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===================================================
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* `How to accelerate a PyTorch Lightning application on training workloads through Intel® Extension for PyTorch* <accelerate_pytorch_lightning_training_ipex.html>`_
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* `How to accelerate a PyTorch Lightning application on training workloads through multiple instances <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 <pytorch_lightning_training_channels_last.html>`_
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* `How to conduct BFloat16 Mixed Precision training in your PyTorch Lightning application <pytorch_lightning_training_bf16.html>`_
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Training Optimization: For TensorFlow Users
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============================================
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* `How to accelerate a TensorFlow Keras application on training workloads through multiple instances <accelerate_tensorflow_training_multi_instance.html>`_
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* |tensorflow_training_embedding_sparseadam_link|_
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* `How to conduct BFloat16 Mixed Precision training in your TensorFlow application <tensorflow_training_bf16.html>`_
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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: tensorflow_training_embedding_sparseadam.html
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42
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42
docs/readthedocs/source/doc/Nano/Howto/Training/index.rst
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Training Optimization
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=========================
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Here you could find detailed guides on how to apply BigDL-Nano to optimize your training workloads. Select your desired use case below for further navigation:
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.. grid:: 1 2 2 2
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.. grid-item::
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.. button-link:: PyTorchLightning/index.html
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:color: primary
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:expand:
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:outline:
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I am a **PyTorch Lightning** user.
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.. grid-item::
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.. button-link:: PyTorch/index.html
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:color: primary
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:expand:
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:outline:
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I am a **PyTorch** user.
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.. grid-item::
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.. button-link:: TensorFlow/index.html
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:color: primary
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:expand:
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:outline:
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I am a **TensorFlow** user.
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.. grid-item::
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.. button-link:: General/index.html
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:color: primary
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:expand:
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:outline:
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I want to know general optimization tips.
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@ -89,5 +89,5 @@ TensorFlow
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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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* `How to install BigDL-Nano in Google Colab <Install/install_in_colab.html>`_
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* `How to install BigDL-Nano on Windows <Install/windows_guide.html>`_
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@ -91,7 +91,7 @@ For Linux, Ubuntu (22.04/20.04/18.04) is recommended.
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For Windows OS, users could only run `bigdl-nano-init` every time they open a new cmd terminal.
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We recommend using Windows Subsystem for Linux 2 (WSL2) to run BigDL-Nano. Please refer to [Nano Windows install guide](../Howto/windows_guide.md) for instructions.
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||||
We recommend using Windows Subsystem for Linux 2 (WSL2) to run BigDL-Nano. Please refer to [Nano Windows install guide](../Howto/Install/windows_guide.md) for instructions.
|
||||
|
||||
### Install on MacOS
|
||||
#### MacOS with Intel Chip
|
||||
|
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|
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Reference in a new issue