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* Add nbsphinx extension for docs * Add specific ipynb files to readthedocs folder and add links to Nano Tutorials index page * Disable execution of ipynb notebook * Remove outputs of two ipynb files * Rename titles and add navigation texts to seq_and_func.ipynb under readthedocs folder * Rename titles and add navigation texts to custom.ipynb file under readthedocs folder
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4.4 KiB
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77 lines
No EOL
4.4 KiB
Markdown
# Nano Tutorial
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- [**BigDL-Nano PyTorch Training Quickstart**](./pytorch_train_quickstart.html)
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> [View source on GitHub][Nano_pytorch_training]
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In this guide we will describe how to scale out PyTorch programs using Nano
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- [**BigDL-Nano PyTorch ONNXRuntime Acceleration Quickstart**](./pytorch_onnxruntime.html)
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> [View source on GitHub][Nano_pytorch_onnxruntime]
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In this guide we will describe how to apply ONNXRuntime Acceleration on inference pipeline with the APIs delivered by BigDL-Nano
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- [**BigDL-Nano PyTorch OpenVINO Acceleration Quickstart**](./pytorch_openvino.html)
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> [View source on GitHub][Nano_pytorch_openvino]
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In this guide we will describe how to apply OpenVINO Acceleration on inference pipeline with the APIs delivered by BigDL-Nano
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- [**BigDL-Nano PyTorch Quantization with INC Quickstart**](./pytorch_quantization_inc.html)
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> [View source on GitHub][Nano_pytorch_Quantization_inc]
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In this guide we will describe how to obtain a quantized model with the APIs delivered by BigDL-Nano
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- [**BigDL-Nano PyTorch Quantization with ONNXRuntime accelerator Quickstart**](./pytorch_quantization_inc_onnx.html)
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> [View source on GitHub][Nano_pytorch_quantization_inc_onnx]
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In this guide we will describe how to obtain a quantized model running inference in the ONNXRuntime engine with the APIs delivered by BigDL-Nano
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- [**BigDL-Nano PyTorch Quantization with POT Quickstart**](./pytorch_quantization_openvino.html)
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> [View source on GitHub][Nano_pytorch_quantization_openvino]
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In this guide we will describe how to obtain a quantized model with the APIs delivered by BigDL-Nano
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- [**BigDL-Nano Hyperparameter Tuning (Tensorflow Sequential/Functional API) Quickstart**](../Tutorials/seq_and_func.html)
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> [Run in Google Colab][Nano_hpo_tf_seq_func_colab] [View source on GitHub][Nano_hpo_tf_seq_func]
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In this guide we will describe how to use Nano's built-in HPO utils to do hyperparameter tuning for models defined using Tensorflow Sequential or Functional API.
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- [**BigDL-Nano Hyperparameter Tuning (Tensorflow Subclassing Model) Quickstart**](../Tutorials/custom.html)
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> [Run in Google Colab][Nano_hpo_tf_subclassing_colab] [View source on GitHub][Nano_hpo_tf_subclassing]
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In this guide we will describe how to use Nano's built-in HPO utils to do hyperparameter tuning for models defined by subclassing tf.keras.Model.
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[Nano_pytorch_training]: <https://github.com/intel-analytics/BigDL/blob/main/python/nano/notebooks/pytorch/tutorial/pytorch_train.ipynb>
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[Nano_pytorch_onnxruntime]: <https://github.com/intel-analytics/BigDL/blob/main/python/nano/notebooks/pytorch/tutorial/pytorch_inference_onnx.ipynb>
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[Nano_pytorch_openvino]: <https://github.com/intel-analytics/BigDL/blob/main/python/nano/notebooks/pytorch/tutorial/pytorch_inference_openvino.ipynb>
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[Nano_pytorch_Quantization_inc]: <https://github.com/intel-analytics/BigDL/blob/main/python/nano/notebooks/pytorch/tutorial/pytorch_quantization_inc.ipynb>
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[Nano_pytorch_quantization_inc_onnx]: <https://github.com/intel-analytics/BigDL/blob/main/python/nano/notebooks/pytorch/tutorial/pytorch_quantization_inc.ipynb>
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[Nano_pytorch_quantization_openvino]: <https://github.com/intel-analytics/BigDL/blob/main/python/nano/notebooks/pytorch/tutorial/pytorch_quantization_openvino.ipynb>
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[Nano_hpo_tf_seq_func]: <https://github.com/intel-analytics/BigDL/blob/main/python/nano/notebooks/hpo/seq_and_func.ipynb>
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[Nano_hpo_tf_seq_func_colab]: <https://colab.research.google.com/github/intel-analytics/BigDL/blob/main/python/nano/notebooks/hpo/seq_and_func.ipynb>
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[Nano_hpo_tf_subclassing]: <https://github.com/intel-analytics/BigDL/blob/main/python/nano/notebooks/hpo/custom.ipynb>
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[Nano_hpo_tf_subclassing_colab]: <https://colab.research.google.com/github/intel-analytics/BigDL/blob/main/python/nano/notebooks/hpo/custom.ipynb> |