From 2001a6513a56f2775968e31924f007d4d3f0ff45 Mon Sep 17 00:00:00 2001
From: Noha Ihab <49988746+NohaIhab@users.noreply.github.com>
Date: Tue, 20 Aug 2024 17:01:26 +0300
Subject: [PATCH] docs: Add how-to guide to create Intel Notebook  (#163)

* docs: create Intel Notebook how-to guide

* link intel gpu guide

* fixing link

* add command to confirm devices and expected output

---------

Co-authored-by: afgambin <angel.fernandez@canonical.com>
---
 docs/.custom_wordlist.txt        |  4 +++
 docs/how-to/jupyter-notebook.rst | 51 ++++++++++++++++++++++++++++++--
 2 files changed, 53 insertions(+), 2 deletions(-)

diff --git a/docs/.custom_wordlist.txt b/docs/.custom_wordlist.txt
index 3ee7cbd..73bcb77 100644
--- a/docs/.custom_wordlist.txt
+++ b/docs/.custom_wordlist.txt
@@ -15,7 +15,10 @@ initialized
 initializing
 intel
 io
+intel
+IPEX
 ipynb
+ITEX
 Jupyter
 jupyter
 JupyterLab
@@ -52,4 +55,5 @@ Tensorflow
 toolkits
 Validator
 WSL
+XPU
 yaml
diff --git a/docs/how-to/jupyter-notebook.rst b/docs/how-to/jupyter-notebook.rst
index a16b9e9..84a9e9f 100644
--- a/docs/how-to/jupyter-notebook.rst
+++ b/docs/how-to/jupyter-notebook.rst
@@ -47,11 +47,11 @@ You should expect an output like this:
 Create an NVIDIA GPU-enabled notebook
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-You can create a Jupyter Notebook containing CUDA runtimes and ML frameworks, and access its JupyterLab server.
+You can create an NVIDIA GPU-enabled Jupyter Notebook containing CUDA runtimes and ML frameworks, and access its JupyterLab server.
 
 .. note::
 
-   To launch a GPU-enabled notebook, you must first :ref:`install <install_nvidia_operator>`
+   To launch an NVIDIA GPU-enabled notebook, you must first :ref:`install <install_nvidia_operator>`
    the NVIDIA Operator and :ref:`verify <verify_nvidia_operator>` DSS can detect the GPU.
    See :ref:`nvidia_gpu` for more details.
 
@@ -83,6 +83,53 @@ Confirm the GPU is detected and usable by running:
 
    tf.config.list_physical_devices('GPU')
 
+Create an Intel GPU-enabled notebook
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+You can create an Intel GPU-enabled Jupyter Notebook with `Intel Extension for PyTorch (IPEX) <https://github.com/intel/intel-extension-for-pytorch?tab=readme-ov-file#intel-extension-for-pytorch>`_ 
+or `Intel Extension for TensorFlow (ITEX) <https://github.com/intel/intel-extension-for-tensorflow?tab=readme-ov-file#intel-extension-for-tensorflow>`_.
+
+.. note::
+
+   To launch an Intel GPU-enabled notebook, you must first :ref:`enable_intel_gpu`.
+
+To see the list of available Intel images, run:
+
+.. code-block:: bash
+
+   dss create --help | grep intel
+
+You should see an output similar to this:
+
+.. code-block:: bash
+
+        - intel-pytorch = intel/intel-extension-for-pytorch:2.1.20-xpu-idp-jupyter
+        - intel-tensorflow = intel/intel-extension-for-tensorflow:2.15.0-xpu-idp-jupyter
+
+Select one of them and create a notebook as follows:
+
+.. code-block:: bash
+
+   dss create my-itex-notebook --image=intel-tensorflow
+
+Confirm the GPU is detected and usable by running:
+
+.. code-block:: python
+
+   import tensorflow as tf
+
+   tf.config.experimental.list_physical_devices()
+
+For example, you should expect an output like the following for a host system containing an Intel CPU and a single Intel GPU:
+
+.. code-block:: python
+
+    [PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU'), PhysicalDevice(name='/physical_device:XPU:0', device_type='XPU')]
+
+.. note::
+
+    Intel denotes XPU the combination of an Intel CPU with GPU.
+
 List created notebooks
 ----------------------