intel · chensuyue · Dec 29, 2022 · Dec 29, 2022 · Dec 29, 2022 · Dec 29, 2022
diff --git a/docs/source/api-documentation/adaptor/onnxrt.rst b/docs/source/api-documentation/adaptor/onnxrt.rst
@@ -1,4 +1,4 @@
-ONNXRT
+ONNX Runtime
 ==============
 
 .. autoapisummary::

diff --git a/docs/source/api-documentation/apis.rst b/docs/source/api-documentation/apis.rst
@@ -6,7 +6,7 @@ The following API information is available:
 .. toctree::
    :maxdepth: 1
 
-   new_api
+   basic_api
    adaptor
    strategy
    model
diff --git a/docs/source/api-documentation/basic_api.rst b/docs/source/api-documentation/basic_api.rst
@@ -0,0 +1,14 @@
+User facing APIs
+###########
+
+The user facing APIs information is available:
+
+.. toctree::
+   :maxdepth: 1
+
+   basic_api/quantization
+   basic_api/mix_precision
+   basic_api/benchmark
+   basic_api/objective
+   basic_api/training
+   basic_api/config
diff --git a/...e/api-documentation/new_api/benchmark.rst → ...api-documentation/basic_api/benchmark.rst b/...e/api-documentation/new_api/benchmark.rst → ...api-documentation/basic_api/benchmark.rst
diff --git a/...urce/api-documentation/new_api/config.rst → ...ce/api-documentation/basic_api/config.rst b/...urce/api-documentation/new_api/config.rst → ...ce/api-documentation/basic_api/config.rst
diff --git a/...i-documentation/new_api/mix_precision.rst → ...documentation/basic_api/mix_precision.rst b/...i-documentation/new_api/mix_precision.rst → ...documentation/basic_api/mix_precision.rst
diff --git a/...e/api-documentation/new_api/objective.rst → ...api-documentation/basic_api/objective.rst b/...e/api-documentation/new_api/objective.rst → ...api-documentation/basic_api/objective.rst
diff --git a/...pi-documentation/new_api/quantization.rst → ...-documentation/basic_api/quantization.rst b/...pi-documentation/new_api/quantization.rst → ...-documentation/basic_api/quantization.rst
diff --git a/...ce/api-documentation/new_api/training.rst → .../api-documentation/basic_api/training.rst b/...ce/api-documentation/new_api/training.rst → .../api-documentation/basic_api/training.rst
diff --git a/docs/source/api-documentation/new_api.rst b/docs/source/api-documentation/new_api.rst
diff --git a/examples/README.md b/examples/README.md
@@ -535,7 +535,7 @@ Intel® Neural Compressor validated examples with multiple compression technique
     <td>SD Diffusion</td>
     <td>Text to Image</td>
     <td>Post-Training Static Quantization</td>
-    <td><a href="./pytorch/nlp/huggingface_models/text-to-image/quantization/ptq_static/fx">fx</a></td>
+    <td><a href="./pytorch/nlp/huggingface_models/text-to-image/quantization">fx</a></td>
   </tr>
 </tbody>
 </table>
@@ -1109,7 +1109,7 @@ Intel® Neural Compressor validated examples with multiple compression technique
     <td>Emotion FERPlus</td>
     <td>Body Analysis</td>
     <td>Post-Training Static Quantization</td>
-    <td><a href="/onnxrt/body_analysis/onnx_model_zoo/emotion_ferplus/quantization/ptq">qlinearops</a></td>
+    <td><a href="./onnxrt/body_analysis/onnx_model_zoo/emotion_ferplus/quantization/ptq">qlinearops</a></td>
   </tr>
   <tr>
     <td>Ultra Face</td>

diff --git a/examples/onnxrt/README.md b/examples/onnxrt/README.md
diff --git a/examples/onnxrt/body_analysis/onnx_model_zoo/arcface/quantization/ptq/README.md b/examples/onnxrt/body_analysis/onnx_model_zoo/arcface/quantization/ptq/README.md
@@ -4,8 +4,9 @@
 This example load a face recognition model from [ONNX Model Zoo](https://github.com/onnx/models) and confirm its accuracy and speed based on [Refined MS-Celeb-1M](https://s3.amazonaws.com/onnx-model-zoo/arcface/dataset/faces_ms1m_112x112.zip). You need to download this dataset yourself.
 
 ### Environment
-onnx: 1.11.0
-onnxruntime: 1.10.0
+onnx: 1.12.0  
+onnxruntime: 1.13.1
+> Validated framework versions can be found in main readme.
 
 ### Prepare model
 Download model from [ONNX Model Zoo](https://github.com/onnx/models)

diff --git a/.../onnxrt/body_analysis/onnx_model_zoo/emotion_ferplus/quantization/ptq/README.md b/.../onnxrt/body_analysis/onnx_model_zoo/emotion_ferplus/quantization/ptq/README.md
@@ -4,8 +4,9 @@
 This example load an model converted from [ONNX Model Zoo](https://github.com/onnx/models) and confirm its accuracy and speed based on [Emotion FER dataset](https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data). You need to download this dataset yourself.
 
 ### Environment
-onnx: 1.11.0
-onnxruntime: 1.10.0
+onnx: 1.12.0  
+onnxruntime: 1.13.1
+> Validated framework versions can be found in main readme.
 
 ### Prepare model
 Download model from [ONNX Model Zoo](https://github.com/onnx/models)

diff --git a/examples/onnxrt/body_analysis/onnx_model_zoo/ultraface/quantization/ptq/README.md b/examples/onnxrt/body_analysis/onnx_model_zoo/ultraface/quantization/ptq/README.md
@@ -4,8 +4,9 @@
 This example load an model converted from [ONNX Model Zoo](https://github.com/onnx/models) and confirm its accuracy and speed based on [WIDER FACE dataset (Validation Images)](http://shuoyang1213.me/WIDERFACE/). You need to download this dataset yourself.
 
 ### Environment
-onnx: 1.11.0
-onnxruntime: 1.10.0
+onnx: 1.12.0  
+onnxruntime: 1.13.1
+> Validated framework versions can be found in main readme.
 
 ### Prepare model
 Download model from [ONNX Model Zoo](https://github.com/onnx/models)

diff --git a/examples/onnxrt/image_recognition/onnx_model_zoo/fcn/quantization/ptq/README.md b/examples/onnxrt/image_recognition/onnx_model_zoo/fcn/quantization/ptq/README.md
@@ -4,8 +4,9 @@
 This example load an object detection model converted from [ONNX Model Zoo](https://github.com/onnx/models) and confirm its accuracy and speed based on [MS COCO 2017 dataset](https://cocodataset.org/#download). You need to download this dataset yourself.
 
 ### Environment
-onnx: 1.9.0
-onnxruntime: 1.10.0
+onnx: 1.12.0  
+onnxruntime: 1.13.1
+> Validated framework versions can be found in main readme.
 
 ### Prepare model
 Download model from [ONNX Model Zoo](https://github.com/onnx/models)

diff --git a/...s/onnxrt/image_recognition/onnx_model_zoo/squeezenet/quantization/ptq/README.md b/...s/onnxrt/image_recognition/onnx_model_zoo/squeezenet/quantization/ptq/README.md
@@ -4,8 +4,9 @@
 This example load an image classification model from [ONNX Model Zoo](https://github.com/onnx/models) and confirm its accuracy and speed based on [ILSVR2012 validation Imagenet dataset](http://www.image-net.org/challenges/LSVRC/2012/downloads). You need to download this dataset yourself.
 
 ### Environment
-onnx: 1.9.0
-onnxruntime: 1.10.0
+onnx: 1.12.0  
+onnxruntime: 1.13.1
+> Validated framework versions can be found in main readme.
 
 ### Prepare model
 Download model from [ONNX Model Zoo](https://github.com/onnx/models)

diff --git a/examples/onnxrt/image_recognition/unet/quantization/ptq/readme.md b/examples/onnxrt/image_recognition/unet/quantization/ptq/readme.md
@@ -3,8 +3,9 @@
 This is an experimental example to quantize unet model. We use dummy data to do quantization and evaluation, so the accuracy is not guaranteed.
 
 ### Environment
-onnx: 1.12.0
-onnxruntime: 1.12.1
+onnx: 1.12.0  
+onnxruntime: 1.13.1
+> Validated framework versions can be found in main readme.
 
 ### Prepare model
 

diff --git a/examples/onnxrt/nlp/onnx_model_zoo/BiDAF/quantization/ptq/README.md b/examples/onnxrt/nlp/onnx_model_zoo/BiDAF/quantization/ptq/README.md
@@ -1,10 +1,11 @@
 # Evaluate performance of ONNX Runtime(BiDAF) 
 
-This example load a a neural network for answering a query about a given context paragraph. It is converted from [ONNX Model Zoo](https://github.com/onnx/models) and confirm its accuracy and speed based on [SQuAD v1.1](https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/).
+This example loads a neural network for answering a query about a given context paragraph. It is converted from [ONNX Model Zoo](https://github.com/onnx/models) and confirm its accuracy and speed based on [SQuAD v1.1](https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/).
 
 ### Environment
-onnx: 1.11.0
-onnxruntime: 1.10.0
+onnx: 1.12.0  
+onnxruntime: 1.13.1
+> Validated framework versions can be found in main readme. 
 
 ### Prepare model
 Download model from [ONNX Model Zoo](https://github.com/onnx/models)

diff --git a/examples/onnxrt/nlp/onnx_model_zoo/bert-squad/quantization/ptq/readme.md b/examples/onnxrt/nlp/onnx_model_zoo/bert-squad/quantization/ptq/readme.md
@@ -4,8 +4,9 @@
 This example load a language translation model and confirm its accuracy and speed based on [SQuAD]((https://rajpurkar.github.io/SQuAD-explorer/)) task. 
 
 ### Environment
-onnx: 1.9.0
-onnxruntime: 1.10.0
+onnx: 1.12.0  
+onnxruntime: 1.13.1
+> Validated framework versions can be found in main readme.
 
 ### Prepare dataset
 You should download SQuAD dataset from [SQuAD dataset link](https://rajpurkar.github.io/SQuAD-explorer/).

diff --git a/examples/onnxrt/nlp/onnx_model_zoo/gpt2/quantization/ptq/readme.md b/examples/onnxrt/nlp/onnx_model_zoo/gpt2/quantization/ptq/readme.md
@@ -4,9 +4,10 @@
 This example load a language translation model and confirm its accuracy and speed based on [WikiText](https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/) dataset. 
 
 ### Environment
-onnx: 1.7.0
-onnxruntime: 1.8.0
+onnx: 1.12.0  
+onnxruntime: 1.13.1
 transformers: 3.2.0
+> Validated framework versions can be found in main readme.
 
 ### Prepare dataset
 Please download [WikiText-2 dataset](https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-raw-v1.zip).

diff --git a/examples/onnxrt/nlp/onnx_model_zoo/mobilebert/quantization/ptq/readme.md b/examples/onnxrt/nlp/onnx_model_zoo/mobilebert/quantization/ptq/readme.md
@@ -4,8 +4,9 @@
 This example load a language translation model and confirm its accuracy and speed based on [SQuAD]((https://rajpurkar.github.io/SQuAD-explorer/)) task. 
 
 ### Environment
-onnx: 1.9.0
-onnxruntime: 1.10.0
+onnx: 1.12.0  
+onnxruntime: 1.13.1
+> Validated framework versions can be found in main readme.
 
 ### Prepare dataset
 Download pretrained bert model. We will refer to `vocab.txt` file.

diff --git a/examples/onnxrt/object_detection/onnx_model_zoo/DUC/quantization/ptq/README.md b/examples/onnxrt/object_detection/onnx_model_zoo/DUC/quantization/ptq/README.md
@@ -4,8 +4,9 @@
 This example load an object detection model converted from [ONNX Model Zoo](https://github.com/onnx/models) and confirm its accuracy and speed based on [cityscapes dataset](https://www.cityscapes-dataset.com/downloads/). You need to download this dataset yourself.
 
 ### Environment
-onnx: 1.9.0
-onnxruntime: 1.10.0
+onnx: 1.12.0  
+onnxruntime: 1.13.1
+> Validated framework versions can be found in main readme.
 
 ### Prepare model
 Download model from [ONNX Model Zoo](https://github.com/onnx/models)