Docs enhancement (#1032)

Signed-off-by: chensuyue <suyue.chen@intel.com>

Author: chensuyue

.azure-pipelines/code-scan-neural-insights.yaml

@@ -11,7 +11,6 @@ pr:
       - neural_insights
       - setup.py
       - .azure-pipelines/code-scan-neural-insights.yml
-      - .azure-pipelines/scripts/codeScan
 
 pool:
   vmImage: "ubuntu-latest"

.azure-pipelines/code-scan-neural-solution.yaml

@@ -11,7 +11,6 @@ pr:
       - neural_solution
       - setup.py
       - .azure-pipelines/code-scan-neural-solution.yml
-      - .azure-pipelines/scripts/codeScan
 
 pool:
   vmImage: "ubuntu-latest"

.azure-pipelines/scripts/codeScan/pyspelling/inc_dict.txt

@@ -2490,6 +2490,7 @@ Thalaiyasingam
 Torr
 QOperator
 MixedPrecisionConfig
+mixedprecision
 contrib
 ONNXConfig
 Arial

docker/README.md

@@ -1,6 +1,6 @@
-## build `Neural Compressor(INC)` Containers:
+## Build Intel Neural Compressor Containers:
 
-### To build the the `Pip` based deployment container:
+### To build the `Pip` based deployment container:
 Please note that `INC_VER` must be set to a valid version published here:
 https://pypi.org/project/neural-compressor/#history
 
@@ -12,7 +12,7 @@ $ IMAGE_TAG=${INC_VER}
 $ docker build --build-arg PYTHON=${PYTHON} --build-arg INC_VER=${INC_VER} -f Dockerfile -t ${IMAGE_NAME}:${IMAGE_TAG} .
 ```
 
-###  To build the the `Pip` based development container:
+###  To build the `Pip` based development container:
 Please note that `INC_BRANCH` must be a set to a valid branch name otherwise, Docker build fails.
 If `${INC_BRANCH}-devel` does not meet Docker tagging requirements described here:
 https://docs.docker.com/engine/reference/commandline/tag/

docs/source/FX.md

@@ -2,7 +2,7 @@ FX
 ====
 1. [Introduction](#introduction)
 2. [FX Mode Support Matrix in Neural Compressor](#fx-mode-support-matrix-in-neural-compressor)
-3. [Get Start](#get-start)
+3. [Get Started](#get-started)
 
     3.1. [Post Training Static Quantization](#post-training-static-quantization)
 
@@ -34,7 +34,7 @@ For detailed description, please refer to [PyTorch FX](https://pytorch.org/docs/
 |Quantization-Aware Training         |✔     |
 
 
-## Get Start
+## Get Started
 
 **Note:** "backend" field indicates the backend used by the user in configure. And the "default" value means it will quantization model with fx backend for PyTorch model.
 

docs/source/adaptor.md

@@ -3,7 +3,7 @@ Adaptor
 1. [Introduction](#introduction)
 2. [Adaptor Support Matrix](#adaptor-support-matrix)
 3. [Working Flow](#working-flow)
-4. [Get Start with Adaptor API](#get-start-with-adaptor-api)
+4. [Get Started with Adaptor API](#get-start-with-adaptor-api)
 
     4.1 [Query API](#query-api)
 
@@ -33,7 +33,7 @@ tuning strategy and vanilla framework quantization APIs.
 ## Working Flow
 Adaptor only provide framework API for tuning strategy. So we can find complete working flow in [tuning strategy working flow](./tuning_strategies.md).
 
-## Get Start with Adaptor API
+## Get Started with Adaptor API
 
 Neural Compressor supports a new adaptor extension by
 implementing a subclass `Adaptor` class in the neural_compressor.adaptor package

docs/source/dataloader.md

@@ -5,7 +5,7 @@ DataLoader
 
 2. [Supported Framework Dataloader Matrix](#supported-framework-dataloader-matrix)
 
-3. [Get Start with Dataloader](#get-start-with-dataloader)
+3. [Get Started with Dataloader](#get-start-with-dataloader)
 
     3.1 [Use Intel® Neural Compressor DataLoader API](#use-intel®-neural-compressor-dataloader-api)
 
@@ -37,7 +37,7 @@ Of cause, users can also use frameworks own dataloader in Neural Compressor.
 | PyTorch       |  ✔  |
 | ONNX Runtime   |  ✔  |
 
-## Get Start with DataLoader
+## Get Started with DataLoader
 
 ### Use Intel® Neural Compressor DataLoader API
 

docs/source/get_started.md

@@ -2,10 +2,6 @@
 
 1. [Quick Samples](#quick-samples)
 
-    1.1 [Quantization with Python API](#quantization-with-python-api)
-
-    1.2 [Quantization with JupyterLab Extension](#quantization-with-jupyterlab-extension)
-
 2. [Validated Models](#validated-models)
 
 ## Quick Samples
@@ -35,14 +31,6 @@ q_model = fit(
     eval_dataloader=dataloader)
 ```
 
-### Quantization with [JupyterLab Extension](/neural_coder/extensions/neural_compressor_ext_lab/README.md)
-
-Search for ```jupyter-lab-neural-compressor``` in the Extension Manager in JupyterLab and install with one click:
-
-<a target="_blank" href="/neural_coder/extensions/screenshots/extmanager.png">
-  <img src="/neural_coder/extensions/screenshots/extmanager.png" alt="Extension" width="35%" height="35%">
-</a>
-
 ## Validated Models
 Intel® Neural Compressor validated the quantization for 10K+ models from popular model hubs (e.g., HuggingFace Transformers, Torchvision, TensorFlow Model Hub, ONNX Model Zoo). 
 Over 30 pruning, knowledge distillation and model export samples are also available. 

docs/source/installation_guide.md

@@ -30,7 +30,7 @@ You can install Neural Compressor using one of three options: Install single com
 
 The following prerequisites and requirements must be satisfied for a successful installation:
 
-- Python version: 3.7 or 3.8 or 3.9 or 3.10
+- Python version: 3.7 or 3.8 or 3.9 or 3.10 or 3.11
 
 > Notes:
 > - If you get some build issues, please check [frequently asked questions](faq.md) at first.
@@ -82,7 +82,7 @@ The AI Kit is distributed through many common channels, including from Intel's w
 
 The following prerequisites and requirements must be satisfied for a successful installation:
 
-- Python version: 3.7 or 3.8 or 3.9 or 3.10
+- Python version: 3.7 or 3.8 or 3.9 or 3.10 or 3.11
 
 ### Install from Binary
 
@@ -127,7 +127,7 @@ The following prerequisites and requirements must be satisfied for a successful
 ### Validated Software Environment
 
 * OS version: CentOS 8.4, Ubuntu 22.04
-* Python version: 3.7, 3.8, 3.9, 3.10
+* Python version: 3.7, 3.8, 3.9, 3.10, 3.11
 
 <table class="docutils">
 <thead>
@@ -148,20 +148,20 @@ The following prerequisites and requirements must be satisfied for a successful
     <td class="tg-7zrl"><a href=https://github.com/tensorflow/tensorflow/tree/v2.12.0>2.12.0</a><br>
     <a href=https://github.com/tensorflow/tensorflow/tree/v2.11.0>2.11.0</a><br>
     <a href=https://github.com/tensorflow/tensorflow/tree/v2.10.1>2.10.1</a><br></td>
-    <td class="tg-7zrl"><a href=https://github.com/Intel-tensorflow/tensorflow/tree/v2.11.0>2.11.0</a><br>
-    <a href=https://github.com/Intel-tensorflow/tensorflow/tree/v2.10.0>2.10.0</a><br>
-    <a href=https://github.com/Intel-tensorflow/tensorflow/tree/v2.9.1>2.9.1</a><br></td>
-    <td class="tg-7zrl"><a href=https://github.com/intel/intel-extension-for-tensorflow/tree/v1.1.0>1.1.0</a><br>
-    <a href=https://github.com/intel/intel-extension-for-tensorflow/tree/v1.0.0>1.0.0</a></td>
-    <td class="tg-7zrl"><a href=https://download.pytorch.org/whl/torch_stable.html>2.0.0+cpu</a><br>
-    <a href=https://download.pytorch.org/whl/torch_stable.html>1.13.0+cpu</a><br>
+    <td class="tg-7zrl"><a href=https://github.com/Intel-tensorflow/tensorflow/tree/v2.12.0>2.12.0</a><br>
+    <a href=https://github.com/Intel-tensorflow/tensorflow/tree/v2.11.0>2.11.0</a><br>
+    <a href=https://github.com/Intel-tensorflow/tensorflow/tree/v2.10.0>2.10.0</a><br></td>
+    <td class="tg-7zrl"><a href=https://github.com/intel/intel-extension-for-tensorflow/tree/v1.2.0>1.2.0</a><br>
+    <a href=https://github.com/intel/intel-extension-for-tensorflow/tree/v1.1.0>1.1.0</a></td>
+    <td class="tg-7zrl"><a href=https://download.pytorch.org/whl/torch_stable.html>2.0.1+cpu</a><br>
+    <a href=https://download.pytorch.org/whl/torch_stable.html>1.13.1+cpu</a><br>
     <a href=https://download.pytorch.org/whl/torch_stable.html>1.12.1+cpu</a><br></td>
-    <td class="tg-7zrl"><a href=https://github.com/intel/intel-extension-for-pytorch/tree/v2.0.0+cpu>2.0.0+cpu</a><br>
-    <a href=https://github.com/intel/intel-extension-for-pytorch/tree/v1.13.0+cpu>1.13.0+cpu</a><br>
+    <td class="tg-7zrl"><a href=https://github.com/intel/intel-extension-for-pytorch/tree/v2.0.100+cpu>2.0.1+cpu</a><br>
+    <a href=https://github.com/intel/intel-extension-for-pytorch/tree/v1.13.100+cpu>1.13.1+cpu</a><br>
     <a href=https://github.com/intel/intel-extension-for-pytorch/tree/v1.12.100>1.12.1+cpu</a><br></td>
-    <td class="tg-7zrl"><a href=https://github.com/microsoft/onnxruntime/tree/v1.14.1>1.14.1</a><br>
-    <a href=https://github.com/microsoft/onnxruntime/tree/v1.13.1>1.13.1</a><br>
-    <a href=https://github.com/microsoft/onnxruntime/tree/v1.12.1>1.12.1</a><br></td>
+    <td class="tg-7zrl"><a href=https://github.com/microsoft/onnxruntime/tree/v1.15.0>1.15.0</a><br>
+    <a href=https://github.com/microsoft/onnxruntime/tree/v1.14.1>1.14.1</a><br>
+    <a href=https://github.com/microsoft/onnxruntime/tree/v1.13.1>1.13.1</a><br></td>
     <td class="tg-7zrl"><a href=https://github.com/apache/incubator-mxnet/tree/1.9.1>1.9.1</a><br></td>
   </tr>
 </tbody>

docs/source/metric.md

@@ -11,7 +11,7 @@ Metrics
 
     2.4. [ONNXRT](#onnxrt)
 
-3. [Get Start with Metric](#get-start-with-metric)
+3. [Get Started with Metric](#get-start-with-metric)
 
     3.1. [Use Intel® Neural Compressor Metric API](#use-intel®-neural-compressor-metric-api)
 
@@ -88,11 +88,11 @@ Neural Compressor supports some built-in metrics that are popularly used in indu
 
 
 
-## Get Start with Metric
+## Get Started with Metric
 
 ### Use Intel® Neural Compressor Metric API
 
-Users can specify an Neural Compressor built-in metric such as shown below:
+Users can specify a Neural Compressor built-in metric such as shown below:
 
 ```python
 from neural_compressor import Metric