fix link errors in examples, rm examples.md (#2382)

Co-authored-by: ZhangJianyu <zhang.jianyu@outlook.com>

docs/build_docs/build.sh

@@ -91,6 +91,7 @@ cp -f "../CODE_OF_CONDUCT.md" "./source/"
 
 sed -i 's/.md/.html/g' ./source/get_started.md
 sed -i 's/.md/.html/g' ./source/docs/install/install_for_cpp.md
+sed -i 's/.md/.html/g' ./source/examples/README.md
 
 sed -i 's/pluggable-device-for-tensorflow.html/pluggable-device-for-tensorflow.md/g' ./source/get_started.md
 sed -i 's/third-party-programs\/THIRD-PARTY-PROGRAMS/https:\/\/github.com\/intel\/intel-extension-for-tensorflow\/blob\/main\/third-party-programs\/THIRD-PARTY-PROGRAMS/g' ./source/get_started.md

docs/build_docs/source/index.rst

@@ -9,7 +9,7 @@ Welcome to Intel ® Extension for TensorFlow* documentation!
    docs/guide/infrastructure.md
    docs/guide/features.rst
    docs/install/installation_guide.rst
-   examples/examples.md
+   examples/README.md
    docs/guide/practice_guide.md
    docs/guide/FAQ.md
    docs/community/releases.md

examples/README.md

@@ -1,19 +1,26 @@
 # Examples
 
-A wide variety of examples are provided to demonstrate the usage of Intel® Extension for TensorFlow*. 
+## Prepare for Running
+
+Before running the training/inference code based on Intel® Extension for TensorFlow*, there are several prepare steps to be executed. Please refer to [Common Guide for Running](./common_guide_running.md).
+
+## Examples
+
+A wide variety of examples are provided to demonstrate the usage of Intel® Extension for TensorFlow*.
 
 |Name|Description|Hardware|
 |-|-|-|
 |[Quick Example](quick_example.md)|Quick example to verify Intel® Extension for TensorFlow* and running environment.|CPU & GPU|
-|[ResNet50 Inference](./infer_resnet50)|ResNet50 inference on Intel CPU or GPU without code changes.|CPU & GPU|
-|[BERT Training for Classifying Text](./train_bert)|BERT training with Intel® Extension for TensorFlow* on Intel CPU or GPU.<br>Use the TensorFlow official example without code change.|CPU & GPU|
-|[Speed up Inference of Inception v4 by Advanced Automatic Mixed Precision via Docker Container or Bare Metal](./infer_inception_v4_amp)|Test and compare the performance of inference with FP32 and Advanced Automatic Mixed Precision (AMP) (mix BF16/FP16 and FP32).<br>Shows the acceleration of inference by Advanced AMP on Intel CPU and GPU via Docker Container or Bare Metal.|CPU & GPU|
-|[Accelerate AlexNet by Quantization with Intel® Extension for TensorFlow*](./accelerate_alexnet_by_quantization)| An end-to-end example to show a pipeline to build up a CNN model to <br>recognize handwriting number and speed up AI model with quantization <br>by Intel® Neural Compressor and Intel® Extension for TensorFlow* on Intel GPU.|GPU|
-|[Accelerate Deep Learning Training and Inference for Model Zoo Workloads on Intel GPU](./model_zoo_example)|Examples on running Model Zoo workloads on Intel GPU with the optimizations from Intel® Extension for TensorFlow*.|GPU|
-|[Quantize Inception V3 by Intel® Extension for TensorFlow* on Intel® Xeon®](./quantize_inception_v3)|An end-to-end example to show how Intel® Extension for TensorFlow* provides quantization feature by cooperating with Intel® Neural Compressor and oneDNN Graph. It will provide better quantization: better performance and accuracy loss is in controlled.|CPU|
-|[ResNet50 and Mnist training with Horovod](./train_horovod)|ResNet50 and Mnist distributed training examples on Intel GPU.|GPU|
-|[Stable Diffusion Inference for Text2Image on Intel GPU](./stable_diffussion_inference)|Example for running Stable Diffusion Text2Image inference on Intel GPU with the optimizations from Intel® Extension for TensorFlow*.|GPU|
-|[Accelerate ResNet50 Training by XPUAutoShard on Intel GPU](./train_resnet50_with_autoshard)|Example on running ResNet50 training on Intel GPU with the XPUAutoShard feature.|GPU|
-|[Accelerate BERT-Large Pretraining on Intel GPU](./pretrain_bert)|Example on running BERT-Large pretraining on Intel GPU with the optimizations from Intel® Extension for TensorFlow*.|GPU|
-|[Accelerate Mask R-CNN Training w/o horovod on Intel GPU](./train_maskrcnn)|Example on running Mask R-CNN training on Intel GPU with the optimizations from Intel® Extension for TensorFlow*.|GPU|
-|[Accelerate 3D-UNet Training w/o horovod for medical image segmentation on Intel GPU](./train_3d_unet)|Example on running 3D-UNet training for medical image segmentation on Intel GPU with the optimizations from Intel® Extension for TensorFlow*.|GPU|
+|[ResNet50 Inference](./infer_resnet50/README.md)|ResNet50 inference on Intel CPU or GPU without code changes.|CPU & GPU|
+|[BERT Training for Classifying Text](./train_bert/README.md)|BERT training with Intel® Extension for TensorFlow* on Intel CPU or GPU.<br>Use the TensorFlow official example without code change.|CPU & GPU|
+|[Speed up Inference of Inception v4 by Advanced Automatic Mixed Precision via Docker Container or Bare Metal](./infer_inception_v4_amp/README.md)|Test and compare the performance of inference with FP32 and Advanced Automatic Mixed Precision (AMP) (mix BF16/FP16 and FP32).<br>Shows the acceleration of inference by Advanced AMP on Intel CPU and GPU via Docker Container or Bare Metal.|CPU & GPU|
+|[Accelerate AlexNet by Quantization with Intel® Extension for TensorFlow*](./accelerate_alexnet_by_quantization/README.md)| An end-to-end example to show a pipeline to build up a CNN model to <br>recognize handwriting number and speed up AI model with quantization <br>by Intel® Neural Compressor and Intel® Extension for TensorFlow* on Intel GPU.|GPU|
+|[Accelerate Deep Learning Training and Inference for Model Zoo Workloads on Intel GPU](./model_zoo_example/README.md)|Examples on running Model Zoo workloads on Intel GPU with the optimizations from Intel® Extension for TensorFlow*.|GPU|
+|[Quantize Inception V3 by Intel® Extension for TensorFlow* on Intel® Xeon®](./quantize_inception_v3/README.md)|An end-to-end example to show how Intel® Extension for TensorFlow* provides quantization feature by cooperating with Intel® Neural Compressor and oneDNN Graph. It will provide better quantization: better performance and accuracy loss is in controlled.|CPU|
+|[Mnist training with Intel® Optimization for Horovod*](./train_horovod/mnist/README.md)|Mnist distributed training example on Intel GPU. |GPU|
+|[ResNet50 training with Intel® Optimization for Horovod*](./train_horovod/resnet50/README.md)|ResNet50 distributed training example on Intel GPU. |GPU|
+|[Stable Diffusion Inference for Text2Image on Intel GPU](./stable_diffussion_inference/README.md)|Example for running Stable Diffusion Text2Image inference on Intel GPU with the optimizations from Intel® Extension for TensorFlow*.|GPU|
+|[Accelerate ResNet50 Training by XPUAutoShard on Intel GPU](./train_resnet50_with_autoshard/README.md)|Example on running ResNet50 training on Intel GPU with the XPUAutoShard feature.|GPU|
+|[Accelerate BERT-Large Pretraining on Intel GPU](./pretrain_bert/README.md)|Example on running BERT-Large pretraining on Intel GPU with the optimizations from Intel® Extension for TensorFlow*.|GPU|
+|[Accelerate Mask R-CNN Training w/o horovod on Intel GPU](./train_maskrcnn/README.md)|Example on running Mask R-CNN training on Intel GPU with the optimizations from Intel® Extension for TensorFlow*.|GPU|
+|[Accelerate 3D-UNet Training w/o horovod for medical image segmentation on Intel GPU](./train_3d_unet/README.md)|Example on running 3D-UNet training for medical image segmentation on Intel GPU with the optimizations from Intel® Extension for TensorFlow*.|GPU|