Yinghu5 patch 1

.github/ISSUE_TEMPLATE/new_sample.md

@@ -0,0 +1,31 @@
+---
+name: Request to add a oneAPI Sample
+about: Use this template to request to add a new Code Sample
+title: 'Request to Add a oneAPI Sample <YourSampleName>'
+labels: 'enhancement'
+assignees: Project Manager
+---
+
+## Summary
+This is a request for a new code Sample called `YourSampleName`
+
+## Purpose
+Answer the following questions
+* What specifically is this code sample trying to show?
+* Why is this important to the oneAPI ecosystem?
+
+## Domain
+Please supply what [Domain](https://github.com/oneapi-src/oneAPI-samples/wiki/Reviewers-and-Domain-Experts) that you feel represents your Code Sample. (Best Effort)
+
+## Description
+Include a short Description of what the sample while Demonstrate and why it is important to the ecosystem.
+
+## Dependencies
+Please list any dependencies, libraries and images, etc and urls of the download locations
+
+## Proposed folder Location
+Please include the proposed folder location for your sample to reside
+
+## Checklist
+[ ] Samples Working Group Permission accepted on <Insert Date>
+

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,18 +1,23 @@
-# Description
+# Existing Sample Changes
+## Description
 
 Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
 
-Fixes # (issue) 
+Fixes Issue# 
+
+## External Dependencies
+
+List any external dependencies created as a result of this change.
 
 ## Type of change
 
 Please delete options that are not relevant. Add a 'X' to the one that is applicable. 
 
 - [ ] Bug fix (non-breaking change which fixes an issue)
 - [ ] New feature (non-breaking change which adds functionality)
-- [ ] Sample Migration (Moving sample from old repository after completing checklist established)
+- [ ] Implement fixes for ONSAM Jiras
 
-# How Has This Been Tested?
+## How Has This Been Tested?
 
 Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration
 
@@ -21,20 +26,37 @@ Please describe the tests that you ran to verify your changes. Provide instructi
 - [ ] Visual Studio
 - [ ] Eclipse IDE
 - [ ] VSCode
+- [ ] When compiling the compliler flag "-Wall -Wformat-security -Werror=format-security" was used
 
-# Checklist for Moving samples:
-Links and Details can be found in the samples WG Teams Files. 
+**_Delete this line and everything below if this is not a PR for a new code sample_**
 
-- [ ] Review sample design with domain reviewers https://github.com/oneapi-src/oneAPI-samples/wiki/Reviewers-and-Domain-Experts 
-- [ ] Implement coding guidelines and ensure code quality.
-- [ ] Adhere to sample.json specification. https://github.com/oneapi-src/oneAPI-samples/wiki/sample-json-specification
-- [ ] Run jsonlint on sample.json to verify json syntax. www.jsonlint.com
+**_Delete this line and all above it if this PR is for a new code sample_**
+# Adding a New Sample(s)
+
+## Description
+
+Please include a description of the sample
+
+## Checklist
+Administrative
+- [ ] Review sample design with the appropriate [Domain Expert](https://github.com/oneapi-src/oneAPI-samples/wiki/Reviewers-and-Domain-Experts): <insert Name Here>
+- [ ] If you have any new dependencies/binaries, inform the oneAPI Code Samples Project Manager
+
+Code Development
+- [ ] Implement coding guidelines and ensure code quality. [see wiki for details](https://github.com/oneapi-src/oneAPI-samples/wiki/General-Code-Guidelines)
 - [ ] Adhere to readme template 
-- [ ] Ensure/create CI test configurations for sample (ciTests field) https://github.com/oneapi-src/oneAPI-samples/wiki/sample-json-ci-test-object
 - [ ] Enforce format via clang-format config file
+- [ ] Adhere to sample.json specification. https://github.com/oneapi-src/oneAPI-samples/wiki/sample-json-specification
+- [ ] Ensure/create CI test configurations for sample (ciTests field) https://github.com/oneapi-src/oneAPI-samples/wiki/sample-json-ci-test-object
+- [ ] Run jsonlint on sample.json to verify json syntax. www.jsonlint.com
+
+Security and Legal
+- [ ] OSPDT Approval (see Project Manager for assistance)
+- [ ] Compile using the following compiler flags and fix any warnings, the falgs are: "/Wall -Wformat-security -Werror=format-security"
+- [ ] Bandit Scans (Python only)
+- [ ] Virus scan
+
+Review
 - [ ] Review DPC++ code with Paul Peterseon. (GitHub User: pmpeter1)
-- [ ] Review readme with Tom Lenth or Joe Oster. (GitHub User: JoeOster)
+- [ ] Review readme with Tom Lenth(@tomlenth) and/or Project Manager
 - [ ] Tested using Dev Cloud when applicable
-- [ ] Implement fixes for ONSAM Jiras
-- [ ] If you have new dependencies/binaries, inform Samples Project Manager Swapna R Dontharaju (@srdontha) or @JoeOster
-

.github/workflows/github-pages.yml

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+name: github-samples-app
+
+on:
+ push:
+  branches:
+  - master
+
+ workflow_dispatch: 
+
+#  schedule:
+#    - cron: '55 13 * * *'
+
+# Top-level default; empty/no permissions 
+permissions: {}  
+
+jobs:
+  pages:
+    name: Build GitHub Pages
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+      # Above required for publishing to gh-pages; see auth on Ln 67-68
+
+    steps:
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: "3.8"
+
+    - uses: actions/checkout@v3
+      name: Check out app/dev  # checks out app/dev in top-level dir
+      with:
+        ref: 'refs/heads/app/dev'
+
+    - uses: actions/checkout@v3
+      name: Check out master # checks out master in subdirectory
+      with:
+        ref: 'refs/heads/master'
+        path: master
+
+    - name: Build JSON DB
+      run: |
+        python3 -m pip install -r src/requirements.txt
+        echo master
+        python3 src/db.py master
+
+    - name: Remove JSON pre-prod  
+      run: |       
+        rm -rf src/docs/sample_db_pre.json
+
+    - name: Build Sphinx
+      run: |    
+        python3 -m sphinx -W -b html src/docs/ src/docs/_build/
+        echo $PWD
+        echo ${{ github.ref }}
+
+    - name: Add GPU-Occupancy-Calculator
+      env: 
+        GPU_OCC_CALC: src/docs/_build/Tools/GPU-Occupancy-Calculator/
+      run: |
+        mkdir -p ${GPU_OCC_CALC}
+        cp -v ${{ github.workspace }}/master/Tools/GPU-Occupancy-Calculator/index.html ${GPU_OCC_CALC}/index.html
+
+    - name: Push docs
+      if: ${{ github.ref == 'refs/heads/master' }} # only if this workflow is run from the master branch, push docs
+      env:
+        GITHUB_USER: ${{ github.actor }}
+        GITHUB_TOKEN: ${{ github.token }}
+        GITHUB_REPO: ${{ github.repository }} 
+      run: |
+        cd src/docs/_build/
+        touch .nojekyll       
+        git init
+        git remote add origin "https://${GITHUB_USER}:${GITHUB_TOKEN}@github.com/${GITHUB_REPO}"
+        git add -A
+        git status
+        git config --global user.name "GitHub Actions"
+        git config --global user.email "actions@github.com"
+        git commit -sm "$(date)"
+        git branch -M gh-pages
+        git push -u origin -f gh-pages

.gitignore

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+# CMAKE build directories
+build/
+
+# emacs save files
+*~
+

AI-and-Analytics/DevCloudREADME.md

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+## Running Samples In DevCloud 
+### Run Samples in Jupyter Lab
+1.	Open [Intel DevCloud](https://software.intel.com/content/www/us/en/develop/tools/devcloud.html).
+2.	In the upper right corner, click Sign In.
+3.	Log in with your Intel account username and password.
+4.	Open Jupyter lab: https://jupyter.oneapi.devcloud.intel.com/
+
+    a.	If you are redirected to the Intel DevCloud page, scroll to the bottom and select Launch Jupyter Lab.
+![](images/jupyter-button.png)   
+    b.  When Jupyter Lab opens, if prompted for a kernel, select **No Kernel**.
+5.	Close the Welcome page. The Launcher tab will appear.
+6.  On the Launcher tab, click **Terminal**.
+![](images/jupyter-terminal.png)
+
+7.	You will see your login at the prompt.
+8.	Follow the instructions to [get code samples](https://github.com/intel-ai-tce/oneAPI-samples/tree/devcloud/AI-and-Analytics#get-code-samples) and [run samples on DevCloud](https://github.com/intel-ai-tce/oneAPI-samples/tree/devcloud/AI-and-Analytics#how-to-submit-a-workload-to-a-specific-architecture)
+
+
+### Running the Sample in DevCloud with a Local Terminal
+1.	Open a terminal on your Linux system.
+2.	Log in to DevCloud.
+```
+ssh devcloud
+```
+3.	Follow the instructions to [get code samples](https://github.com/intel-ai-tce/oneAPI-samples/tree/devcloud/AI-and-Analytics#get-code-samples) and [run samples on DevCloud](https://github.com/intel-ai-tce/oneAPI-samples/tree/devcloud/AI-and-Analytics#how-to-submit-a-workload-to-a-specific-architecture)
+
+

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

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+#  `Census` Sample: End-to-End Machine Learning Workload
+
+The `Census` sample code illustrates how to use Intel® Distribution of Modin* for ETL operations and ridge regression algorithm from the Intel® Extension for Scikit-learn* library to build and run an end-to-end machine learning (ML) workload.
+
+| Area                     | Description
+|:---                      | :---
+| What you will learn      | How to use Intel Distribution of Modin* and Intel® Extension for Scikit-learn* to build end-to-end ML workloads and gain performance.
+| Time to complete         | 20 minutes
+
+
+## Purpose
+This sample code demonstrates how to run the end-to-end census workload using the AI Toolkit without any external dependencies.
+
+Intel® Distribution of Modin* uses HDK to speed up your Pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Intel® Distribution of Modin* provides integration and compatibility with existing Pandas code. Intel® Extension for Scikit-learn* dynamically patches scikit-learn estimators to use Intel® oneAPI Data Analytics Library (oneDAL) as the underlying solver to get the solution faster.
+
+## Prerequisites
+
+| Optimized for                     | Description
+| :---                              | :---
+| OS                                | 64-bit Ubuntu* 18.04 or higher
+| Hardware                          | Intel Atom® processors <br> Intel® Core™ processor family <br> Intel® Xeon® processor family <br> Intel® Xeon® Scalable processor family
+| Software                          | Intel® AI Analytics Toolkit (AI Kit) (Python version 3.8 or newer, Intel® Distribution of Modin*) <br> Intel® Extension for Scikit-learn* <br> NumPy
+
+The Intel® Distribution of Modin* and Intel® Extension for Scikit-learn* libraries are available together in [Intel® AI Analytics Toolkit (AI Kit)](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html).
+
+
+## Key Implementation Details
+
+This end-to-end workload sample code is implemented for CPU using the Python language. Once you have installed AI Kit, the Conda environment is prepared with Python version 3.8 (or newer), Intel Distribution of Modin*, Intel® Extension for Scikit-Learn, and NumPy. 
+
+In this sample, you will use Intel® Distribution of Modin* to ingest and process U.S. census data from 1970 to 2010 in order to build a ridge regression-based model to find the relation between education and total income earned in the US.
+
+The data transformation stage normalizes the income to yearly inflation, balances the data so each year has a similar number of data points, and extracts the features from the transformed dataset. The feature vectors are input into the ridge regression model to predict the education of each sample.
+
+>**Note**: The dataset is from IPUMS USA, University of Minnesota, [www.ipums.org](https://ipums.org/). <br> 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](https://doi.org/10.18128/D010.V10.0).
+
+
+## Configure the Development Environment
+If you do not already have the AI Kit installed, then download an online or offline installer for the [Intel® AI Analytics Toolkit (AI Kit)](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html) or install the AI Kit using Conda.
+
+>**Note**: See [Install Intel® AI Analytics Toolkit via Conda*](https://software.intel.com/content/www/us/en/develop/documentation/installation-guide-for-intel-oneapi-toolkits-linux/top/installation/install-using-package-managers/conda/install-intel-ai-analytics-toolkit-via-conda.html) in the *Intel® oneAPI Toolkits Installation Guide for Linux* OS* for information on Conda installation and configuration.
+
+The Intel® Distribution of Modin* and the Intel® Extension for Scikit-learn* are ready to use after AI Kit installation with the Conda Package Manager.
+
+## Set Environment Variables
+
+When working with the command-line interface (CLI), you should configure the oneAPI toolkits using environment variables. Set up your CLI environment by sourcing the `setvars` script every time you open a new terminal window. This practice ensures that your compiler, libraries, and tools are ready for development.
+
+### Use Visual Studio Code* (VS 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:
+ 1. Configure the oneAPI environment with the extension **Environment Configurator for Intel® oneAPI Toolkits**.
+ 2. Download a sample using the extension **Code Sample Browser for Intel® oneAPI Toolkits**.
+ 3. Open a terminal in VS Code (**Terminal > New Terminal**).
+ 4. Run the sample in the VS Code terminal using the instructions below.
+ 5. (Linux only) Debug GPU applications with GDB for Intel® oneAPI toolkits using the Generate Launch Configurations extension.
+
+To learn more about the extensions and how to configure the oneAPI environment, see the [Using Visual Studio Code with Intel® oneAPI Toolkits User Guide](https://www.intel.com/content/www/us/en/develop/documentation/using-vs-code-with-intel-oneapi/top.html).
+
+## Configure the Environment
+
+> **Note**: If you have not already done so, set up your CLI
+> environment by sourcing  the `setvars` script in the root of your oneAPI installation.
+>
+> Linux*:
+> - For system wide installations: `. /opt/intel/oneapi/setvars.sh`
+> - For private installations: ` . ~/intel/oneapi/setvars.sh`
+> - For non-POSIX shells, like csh, use the following command: `bash -c 'source <install-dir>/setvars.sh ; exec csh'`
+>
+> For more information on configuring environment variables, see [Use the setvars Script with 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).
+
+### On Linux*
+
+1. Install the Intel® Distribution of Modin* python environment (Only python 3.8 - 3.10 are supported).
+   ```
+   conda create -n modin-hdk python=3.x -y
+   ```
+2. Activate the Conda environment.
+   ```
+   conda activate modin-hdk
+   ```
+3. Install modin-hdk, Intel® Extension for Scikit-learn* and related libraries.
+   ```
+   conda install modin-hdk -c conda-forge -y
+   pip install scikit-learn-intelex
+   pip install matplotlib
+   ```
+4. Install Jupyter Notebook
+   ```
+   pip install jupyter ipykernel
+   ```
+5. Add kernel to Jupyter Notebook.
+   ```
+   python -m ipykernel install --user --name modin-hdk
+   ```
+6. Change to the sample directory, and open Jupyter Notebook.
+   ```
+   jupyter notebook
+   ```
+
+## Run the `Census` Sample
+
+### Run the Jupyter Notebook
+
+1. Open `census_modin.ipynb`.
+2. Click **Run** to run the cells.
+
+   ![Click the Run Button in the Jupyter Notebook](Running_Jupyter_notebook.jpg "Run Button on Jupyter Notebook")
+
+3. Alternatively, run the entire workbook by selecting **Restart kernel and re-run whole notebook**.
+
+### Run as Python File
+1. Open the notebook in Jupyter.
+2. From the **File** menu, select **Download as** > **Python (.py)**.
+
+   ![Download as python file in the Jupyter Notebook](Running_Jupyter_notebook_as_Python.jpg "Download as python file in the Jupyter Notebook")
+
+3. Run the program.
+   ```
+   python census_modin.py
+   ```
+
+   #### Troubleshooting
+   If you receive an error message, troubleshoot the problem using the **Diagnostics Utility for Intel® oneAPI Toolkits**. The diagnostic utility provides configuration and system checks to help find missing dependencies, permissions errors, and other issues. See the [Diagnostics Utility for Intel® oneAPI Toolkits User Guide](https://www.intel.com/content/www/us/en/develop/documentation/diagnostic-utility-user-guide/top.html) for more information on using the utility.
+
+
+### Run Notebook in Intel® DevCloud in JupyterLab*
+
+1. If you do not already have an account, request an Intel® DevCloud account at [Create an Intel® DevCloud Account](https://intelsoftwaresites.secure.force.com/DevCloud/oneapi).
+2. Open a web browser, and navigate to https://devcloud.intel.com. Select **Work with oneAPI**.
+3. From Intel® DevCloud for oneAPI [Get Started](https://devcloud.intel.com/oneapi/get_started), locate the ***Connect with Jupyter* Lab*** section (near the bottom).
+4. Click **Sign in to Connect** button. (If you are already signed in, the link should say ***Launch JupyterLab****.)
+5. Open a terminal from Launcher
+6. Follow [step 1-5](#on-linux) to create conda environment
+7. Clone the samples from GitHub. If the samples are already present, skip this step.
+   ```
+   git clone https://github.com/oneapi-src/oneAPI-samples.git
+   ```
+8. Change to the sample directory.
+9. Open `census_modin.ipynb`.
+10. Select kernel "modin-hdk" 
+11. Click **Run** to run the cells.
+12. Alternatively, run the entire workbook by selecting **Restart kernel and re-run whole notebook**.
+
+## Example Output
+
+This is an example Cell Output for `census_modin.ipynb` run in Jupyter Notebook. 
+![Output](Expected_output.jpg "Expected output for Jupyter Notebook")
+
+
+## License
+
+Code samples are licensed under the MIT license. See [License.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/License.txt) for details.
+
+Third-party program Licenses can be found here: [third-party-programs.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/third-party-programs.txt).