AI-samples-Readme-Updates (oneapi-src#848)

* AI-samples-Readme-Updates

For each readme in the AI-and-Analytics folder, I reviewed and updated to include consistent instructions for:
- Using VS Code
- sourcing or running setvars
- troubleshooting with the diagnostics utility

* shortened setvars section

Author: bdmoore1

AI-and-Analytics/End-to-end-Workloads/Census/README.md

@@ -20,7 +20,7 @@ Data transformation stage normalizes the income to the yearly inflation, balance
 Dataset is from IPUMS USA, University of Minnesota, [www.ipums.org](https://ipums.org/) (Steven Ruggles, Sarah Flood, Ronald Goeken, Josiah Grover, Erin Meyer, Jose Pacas and Matthew Sobek. IPUMS USA: Version 10.0 [dataset]. Minneapolis, MN: IPUMS, 2020. https://doi.org/10.18128/D010.V10.0)
 
 ## Key Implementation Details
-This end-to-end workload sample code is implemented for CPU using the Python language.  With the installation of Intel AI Analytics Toolkit, the conda environment is prepared with Python version 3.7, Intel Distribution of Modin* , Ray, Intel® Extension for Scikit-Learn, NumPy following which the sample code can be directly run using the underlying steps in this README. 
+This end-to-end workload sample code is implemented for CPU using the Python language.  With the installation of Intel AI Analytics Toolkit, the conda environment is prepared with Python version 3.7, Intel Distribution of Modin* , Ray, Intel® Extension for Scikit-Learn, NumPy following which the sample code can be directly run using the underlying steps in this README.
 
 ## License
 
@@ -77,3 +77,23 @@ Run the Program
 ##### Expected Printed Output:
 Expected Cell Output shown for census_modin.ipynb:
 ![Output](Expected_output.jpg "Expected output for Jupyter Notebook")
+
+If an error occurs, troubleshoot the problem using the Diagnostics Utility for Intel® oneAPI Toolkits.
+[Learn more](https://software.intel.com/content/www/us/en/develop/documentation/diagnostic-utility-user-guide/top.html).
+
+### Using Visual Studio Code*  (Optional)
+
+You can use Visual Studio Code (VS Code) extensions to set your environment,
+create launch configurations, and browse and download samples.
+
+The basic steps to build and run a sample using VS Code include:
+ - Download a sample using the extension **Code Sample Browser for Intel oneAPI Toolkits**.
+ - Configure the oneAPI environment with the extension **Environment Configurator for Intel oneAPI Toolkits**.
+ - Open a Terminal in VS Code (**Terminal>New Terminal**).
+ - Run the sample in the VS Code terminal using the instructions below.
+ - (Linux only) Debug your GPU application with GDB for Intel® oneAPI toolkits using the Generate Launch Configurations extension.
+
+To learn more about the extensions, see
+[Using Visual Studio Code with Intel® oneAPI Toolkits](https://software.intel.com/content/www/us/en/develop/documentation/using-vs-code-with-intel-oneapi/top.html).
+
+After learning how to use the extensions for Intel oneAPI Toolkits, return to this readme for instructions on how to build and run a sample.

AI-and-Analytics/End-to-end-Workloads/LidarObjectDetection-PointPillars/README.md

@@ -66,7 +66,19 @@ To learn more about the extensions and how to configure the oneAPI environment,
 After learning how to use the extensions for Intel oneAPI Toolkits, return to this readme for instructions on how to build and run a sample.
 
 ### Build process (Local or Remote Host Installation)
-Perform the following steps:
+
+> **Note**: If you have not already done so, set up your CLI
+> environment by sourcing  the `setvars` script located in
+> the root of your oneAPI installation.
+>
+> Linux Sudo: . /opt/intel/oneapi/setvars.sh
+>
+> Linux User: . ~/intel/oneapi/setvars.sh
+>
+> Windows: C:\Program Files(x86)\Intel\oneAPI\setvars.bat
+>
+>For more information on environment variables, see Use the setvars Script for [Linux or macOS](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/oneapi-development-environment-setup/use-the-setvars-script-with-linux-or-macos.html), or [Windows](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/oneapi-development-environment-setup/use-the-setvars-script-with-windows.html).
+
 1. Prepare the environment to be able to use the Intel® Distribution of OpenVINO™ toolkit and oneAPI
 ```
 $ source /opt/intel/openvino_2021/bin/setupvars.sh
@@ -81,6 +93,17 @@ $ make
 ```
 Please note that cmake will also download the ONNX models required for the two inference steps executed with the Intel® Distribution of OpenVINO™ toolkit.
 
+If an error occurs, you can get more details by running `make` with the
+`VERBOSE=1` argument:
+
+ ``make VERBOSE=1``
+
+ For more comprehensive
+troubleshooting, use the Diagnostics Utility for Intel® oneAPI Toolkits, which
+provides system checks to find missing dependencies and permissions errors.
+[Learn more](https://software.intel.com/content/www/us/en/develop/documentation/diagnostic-utility-user-guide/top.html).
+
+
 ## Running the `PointPillars` Sample Program
 After a successful build, the sample program can be run as follows:
 ```

AI-and-Analytics/End-to-end-Workloads/README.md

@@ -29,3 +29,17 @@ Third party program Licenses can be found here:
 # Using Samples in the Intel oneAPI DevCloud
 To get started using samples in the DevCloud, refer to [Using AI samples in Intel oneAPI DevCloud](https://github.com/intel-ai-tce/oneAPI-samples/tree/devcloud/AI-and-Analytics#using-samples-in-intel-oneapi-devcloud).
 
+### Using Visual Studio Code*  (Optional)
+
+You can use Visual Studio Code (VS Code) extensions to set your environment, create launch configurations,
+and browse and download samples.
+
+The basic steps to build and run a sample using VS Code include:
+ - Download a sample using the extension **Code Sample Browser for Intel oneAPI Toolkits**.
+ - Configure the oneAPI environment with the extension **Environment Configurator for Intel oneAPI Toolkits**.
+ - Open a Terminal in VS Code (**Terminal>New Terminal**).
+ - Run the sample in the VS Code terminal using the instructions below.
+ - (Linux only) Debug your GPU application with GDB for Intel® oneAPI toolkits using the Generate Launch Configurations extension.
+
+To learn more about the extensions, see
+[Using Visual Studio Code with Intel® oneAPI Toolkits](https://software.intel.com/content/www/us/en/develop/documentation/using-vs-code-with-intel-oneapi/top.html).

AI-and-Analytics/Features-and-Functionality/IntelPython_XGBoost_Performance/README.md

@@ -30,12 +30,20 @@ XGBoost is ready for use once you finish the Intel® oneAPI AI Analytics Toolkit
 
 You can refer to the oneAPI [main page](https://software.intel.com/en-us/oneapi) for toolkit installation and the Toolkit [Getting Started Guide for Linux](https://software.intel.com/en-us/get-started-with-intel-oneapi-linux-get-started-with-the-intel-ai-analytics-toolkit) for post-installation steps and scripts.
 
-
+> **Note**: If you have not already done so, set up your CLI
+> environment by sourcing  the `setvars` script located in
+> the root of your oneAPI installation.
+>
+> Linux Sudo: . /opt/intel/oneapi/setvars.sh
+>
+> Linux User: . ~/intel/oneapi/setvars.sh
+>
+> Windows: C:\Program Files(x86)\Intel\oneAPI\setvars.bat
+>
+>For more information on environment variables, see Use the setvars Script for [Linux or macOS](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/oneapi-development-environment-setup/use-the-setvars-script-with-linux-or-macos.html), or [Windows](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/oneapi-development-environment-setup/use-the-setvars-script-with-windows.html).
 
 ### Activate conda environment With Root Access
 
-Please follow the Getting Started Guide steps (above) to set up your oneAPI environment with the `setvars.sh` script. Then navigate in Linux shell to your oneapi installation path, typically `/opt/intel/oneapi/` when installed as root or sudo, and `~/intel/oneapi/` when not installed as a superuser. If you customized the installation folder, the `setvars.sh` file is in your custom folder.
-
 Intel Python environment will be active by default. However, if you activated another environment, you can return with the following command:
 
 #### On a Linux* System

AI-and-Analytics/Features-and-Functionality/IntelPython_XGBoost_daal4pyPrediction/README.md

@@ -33,9 +33,20 @@ XGBoost* is ready for use once you finish the Intel® oneAPI AI Analytics Toolki
 You can refer to the oneAPI [main page](https://software.intel.com/en-us/oneapi) for toolkit installation and the Toolkit [Getting Started Guide for Linux](https://software.intel.com/en-us/get-started-with-intel-oneapi-linux-get-started-with-the-intel-ai-analytics-toolkit) for post-installation steps and scripts.
 
 
-### Activate conda environment With Root Access
+> **Note**: If you have not already done so, set up your CLI
+> environment by sourcing  the `setvars` script located in
+> the root of your oneAPI installation.
+>
+> Linux Sudo: . /opt/intel/oneapi/setvars.sh
+>
+> Linux User: . ~/intel/oneapi/setvars.sh
+>
+> Windows: C:\Program Files(x86)\Intel\oneAPI\setvars.bat
+>
+>For more information on environment variables, see Use the setvars Script for [Linux or macOS](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/oneapi-development-environment-setup/use-the-setvars-script-with-linux-or-macos.html), or [Windows](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/oneapi-development-environment-setup/use-the-setvars-script-with-windows.html).
+
 
-Please follow the Getting Started Guide steps (above) to set up your oneAPI environment with the `setvars.sh` script. Then navigate in Linux shell to your oneapi installation path, typically `/opt/intel/oneapi/` when installed as root or sudo, and `~/intel/oneapi/` when not installed as a superuser. If you customized the installation folder, the `setvars.sh` file is in your custom folder.
+### Activate conda environment With Root Access
 
 Intel Python environment will be active by default. However, if you activated another environment, you can return with the following command:
 

AI-and-Analytics/Features-and-Functionality/IntelPython_daal4py_DistributedKMeans/README.md

@@ -1,5 +1,5 @@
-# `Intel Python daal4py Distributed K-Means` Sample 
-This sample code shows how to train and predict with a distributed k-means model using the python API package daal4py for oneAPI Data Analytics Library. It assumes you have a working version of the Intel MPI library installed, and it demonstrates how to use software products that can be found in the [oneAPI Data Analytics Library](https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/onedal.html) or [Intel® oneAPI AI Analytics Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html). 
+# `Intel Python daal4py Distributed K-Means` Sample
+This sample code shows how to train and predict with a distributed k-means model using the python API package daal4py for oneAPI Data Analytics Library. It assumes you have a working version of the Intel MPI library installed, and it demonstrates how to use software products that can be found in the [oneAPI Data Analytics Library](https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/onedal.html) or [Intel® oneAPI AI Analytics Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html).
 
 | Optimized for                     | Description
 | :---                              | :---
@@ -29,13 +29,23 @@ If you are running this sample on the DevCloud, see [Running Samples on the Inte
 
 ## Building daal4py for CPU
 
-oneAPI Data Analytics Library is ready for use once you finish the Intel® oneAPI AI Analytics Toolkit installation and have run the post installation script.
+The Intel(R) oneAPI Data Analytics Library is ready for use once you finish the Intel® oneAPI AI Analytics Toolkit installation and have run the post installation script.
 
-You can refer to the oneAPI [main page](https://software.intel.com/en-us/oneapi) for toolkit installation and the Toolkit [Getting Started Guide for Linux](https://software.intel.com/en-us/get-started-with-intel-oneapi-linux-get-started-with-the-intel-ai-analytics-toolkit) for post-installation steps and scripts.
+You can refer to the oneAPI [main page](https://software.intel.com/en-us/oneapi) for toolkit installation and the Toolkit [Getting Started Guide for Linux](https://www.intel.com/content/www/us/en/develop/documentation/get-started-with-ai-linux/top.html) for post-installation steps and scripts.
 
-### Activate conda environment With Root Access
+> **Note**: If you have not already done so, set up your CLI
+> environment by sourcing  the `setvars` script located in
+> the root of your oneAPI installation.
+>
+> Linux Sudo: . /opt/intel/oneapi/setvars.sh
+>
+> Linux User: . ~/intel/oneapi/setvars.sh
+>
+> Windows: C:\Program Files(x86)\Intel\oneAPI\setvars.bat
+>
+>For more information on environment variables, see Use the setvars Script for [Linux or macOS](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/oneapi-development-environment-setup/use-the-setvars-script-with-linux-or-macos.html), or [Windows](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/oneapi-development-environment-setup/use-the-setvars-script-with-windows.html).
 
-Please follow the Getting Started Guide steps (above) to set up your oneAPI environment with the `setvars.sh` script. Then navigate in Linux shell to your oneapi installation path, typically `/opt/intel/oneapi/` when installed as root or sudo, and `~/intel/oneapi/` when not installed as a superuser. If you customized the installation folder, the `setvars.sh` file is in your custom folder.
+### Activate conda environment With Root Access
 
 Intel Python environment will be active by default. However, if you activated another environment, you can return with the following command:
 
@@ -99,7 +109,7 @@ The basic steps to build and run a sample using VS Code include:
  - Run the sample in the VS Code terminal using the instructions below.
 
 To learn more about the extensions and how to configure the oneAPI environment, see
-[Using Visual Studio Code with Intel® oneAPI Toolkits](https://software.intel.com/content/www/us/en/develop/documentation/using-vs-code-with-intel-oneapi/top.html).
+[Using Visual Studio Code with Intel® oneAPI Toolkits](https://www.intel.com/content/www/us/en/develop/documentation/using-vs-code-with-intel-oneapi/top.html).
 
 After learning how to use the extensions for Intel oneAPI Toolkits, return to this readme for instructions on how to build and run a sample.
 

AI-and-Analytics/Features-and-Functionality/IntelPython_daal4py_DistributedLinearRegression/README.md

@@ -1,6 +1,6 @@
 # `Intel Python daal4py Distributed Linear Regression Sample`
 
-This sample code shows how to train and predict with a distributed linear regression model using the python API package daal4py for oneAPI Data Analytics Library. It assumes you have a working version of the Intel® MPI Library installed, and it demonstrates how to use software products that can be found in the [oneAPI Data Analytics Library](https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/onedal.html) or [Intel® oneAPI AI Analytics Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html). 
+This sample code shows how to train and predict with a distributed linear regression model using the python API package daal4py for oneAPI Data Analytics Library. It assumes you have a working version of the Intel® MPI Library installed, and it demonstrates how to use software products that can be found in the [oneAPI Data Analytics Library](https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/onedal.html) or [Intel® oneAPI AI Analytics Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html).
 
 | Optimized for                     | Description
 | :---                              | :---
@@ -34,11 +34,20 @@ oneAPI Data Analytics Library is ready for use once you finish the Intel® oneAP
 
 You can refer to the oneAPI [main page](https://software.intel.com/en-us/oneapi) for toolkit installation and the Toolkit [Getting Started Guide for Linux](https://software.intel.com/en-us/get-started-with-intel-oneapi-linux-get-started-with-the-intel-ai-analytics-toolkit) for post-installation steps and scripts.
 
+> **Note**: If you have not already done so, set up your CLI
+> environment by sourcing  the `setvars` script located in
+> the root of your oneAPI installation.
+>
+> Linux Sudo: . /opt/intel/oneapi/setvars.sh
+>
+> Linux User: . ~/intel/oneapi/setvars.sh
+>
+> Windows: C:\Program Files(x86)\Intel\oneAPI\setvars.bat
+>
+>For more information on environment variables, see Use the setvars Script for [Linux or macOS](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/oneapi-development-environment-setup/use-the-setvars-script-with-linux-or-macos.html), or [Windows](https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/oneapi-development-environment-setup/use-the-setvars-script-with-windows.html).
 
 ### Activate conda environment With Root Access
 
-Please follow the Getting Started Guide steps (above) to set up your oneAPI environment with the `setvars.sh` script. Then navigate in Linux shell to your oneapi installation path, typically `/opt/intel/oneapi/` when installed as root or sudo, and `~/intel/oneapi/` when not installed as a superuser. If you customized the installation folder, the `setvars.sh` file is in your custom folder.
-
 Intel Python environment will be active by default. However, if you activated another environment, you can return with the following command:
 
 #### On a Linux* System

AI-and-Analytics/Features-and-Functionality/IntelScikitLearn_Extensions_SVC_Adult/README.md

@@ -78,6 +78,12 @@ Classification report for SVC trained with the original scikit-learn:
    macro avg       0.76      0.74      0.75      9769
 weighted avg       0.82      0.82      0.82      9769
 ```
+
+
+If an error occurs, troubleshoot the problem using the Diagnostics Utility for Intel® oneAPI Toolkits.
+[Learn more](https://software.intel.com/content/www/us/en/develop/documentation/diagnostic-utility-user-guide/top.html)
+
+
 ### Using Visual Studio Code*  (VS Code)
 
 You can use VS Code extensions to set your environment, create launch configurations,

AI-and-Analytics/Features-and-Functionality/IntelTensorFlow_Horovod_Multinode_Training/README.md

@@ -90,6 +90,9 @@ Example:
     horovodrun -n 2 -H host1,host2 `pwd`/TensorFlow_Multinode_Training_with_Horovod.py
 ```
 
+If an error occurs, troubleshoot the problem using the Diagnostics Utility for Intel® oneAPI Toolkits.
+[Learn more](https://software.intel.com/content/www/us/en/develop/documentation/diagnostic-utility-user-guide/top.html)
+
 ### Using Visual Studio Code*  (VS Code)
 
 You can use VS Code extensions to set your environment, create launch configurations,