Update README.md to development (#2323)

* Update README.md

* update readme

Author: ZhaoqiongZ

AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/README.md

@@ -48,64 +48,120 @@ The sample uses pretrained model provided by Intel and published as part of [Int
 ## Environment Setup
 You will need to download and install the following toolkits, tools, and components to use the sample.
 
+
 **1. Get Intel® AI Tools**
 
-Required AI Tools: <https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-tools-selector.html>
-<br>If you have not already, select and install these Tools via [AI Tools Selector](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-tools-selector.html). AI and Analytics samples are validated on AI Tools Offline Installer. It is recommended to select Offline Installer option in AI Tools Selector.   
+Required AI Tools:  Intel® Extension for PyTorch* - GPU
+
+If you have not already, select and install these Tools via [AI Tools Selector](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-tools-selector.html). AI and Analytics samples are validated on AI Tools Offline Installer. It is recommended to select Offline Installer option in AI Tools Selector.
+
+>**Note**: If Docker option is chosen in AI Tools Selector, refer to [Working with Preset Containers](https://github.com/intel/ai-containers/tree/main/preset) to learn how to run the docker and samples.
+
+**2. (Offline Installer) Activate the AI Tools bundle base environment**
 
-**2. Install dependencies**
+If the default path is used during the installation of AI Tools:
 ```
-pip install -r requirements.txt
+source $HOME/intel/oneapi/intelpython/bin/activate
+```
+If a non-default path is used:
 ```
-**Install Jupyter Notebook** by running `pip install notebook`. Alternatively, see [Installing Jupyter](https://jupyter.org/install) for detailed installation instructions.
+source <custom_path>/bin/activate
+```
+ 
+**3. (Offline Installer) Activate relevant Conda environment**
+
+```
+conda activate pytorch-gpu 
+``` 
+
+**4. Clone the GitHub repository**
+
+``` 
+git git clone https://github.com/oneapi-src/oneAPI-samples.git
+cd oneAPI-samples/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/
+```
+
+**5. Install dependencies**
+
+>**Note**: Before running the following commands, make sure your Conda/Python environment with AI Tools installed is activated
+
+```
+pip install -r requirements.txt
+pip install notebook
+``` 
+For Jupyter Notebook, refer to [Installing Jupyter](https://jupyter.org/install) for detailed installation instructions.
 
 
 ## Run the Sample
 >**Note**: Before running the sample, make sure [Environment Setup](#environment-setup) is completed.
+
 Go to the section which corresponds to the installation method chosen in [AI Tools Selector](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-tools-selector.html) to see relevant instructions:
 * [AI Tools Offline Installer (Validated)](#ai-tools-offline-installer-validated)
+* [Conda/PIP](#condapip) 
 * [Docker](#docker)
 
 ### AI Tools Offline Installer (Validated)  
-1. If you have not already done so, activate the AI Tools bundle base environment. If you used the default location to install AI Tools, open a terminal and type the following
+
+**1. Register Conda kernel to Jupyter Notebook kernel**
+
+If the default path is used during the installation of AI Tools:
 ```
-source $HOME/intel/oneapi/intelpython/bin/activate
+$HOME/intel/oneapi/intelpython/envs/pytorch-gpu/bin/python -m ipykernel install --user --name=pytorch-gpu
 ```
-If you used a separate location, open a terminal and type the following
+If a non-default path is used:
 ```
-source <custom_path>/bin/activate
+<custom_path>/bin/python -m ipykernel install --user --name=pytorch-gpu
 ```
-2. Clone the GitHub repository:
-``` 
-git clone https://github.com/oneapi-src/oneAPI-samples.git
-cd oneAPI-samples/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/
+**2. Launch Jupyter Notebook** 
+
+```
+jupyter notebook --ip=0.0.0.0 --port 8888 --allow-root
+```
+**3. Follow the instructions to open the URL with the token in your browser**
+
+**4. Select the Notebook**
+
+```
+ResNet50_Inference.ipynb
 ```
-3. Run the Python script.
+
+**5. Change the kernel to `pytorch-gpu`**
+
+**6. Run every cell in the Notebook in sequence**
+
+### Conda/PIP
+> **Note**: Before running the instructions below, make sure your Conda/Python environment with AI Tools installed is activated
+
+**1. Register Conda/Python kernel to Jupyter Notebook kernel** 
+
+For Conda:
 ```
-python Intel_Extension_For_PyTorch_Hello_World.py
+<CONDA_PATH_TO_ENV>/bin/python -m ipykernel install --user --name=pytorch-gpu
 ```
-You will see the DNNL verbose trace after exporting the `DNNL_VERBOSE`:
+To know <CONDA_PATH_TO_ENV>, run `conda env list` and find your Conda environment path.
+
+For PIP:
 ```
-export DNNL_VERBOSE=1
+python -m ipykernel install --user --name=pytorch-gpu
 ```
->**Note**: Read more information about the mkldnn log at [https://oneapi-src.github.io/oneDNN/dev_guide_verbose.html](https://oneapi-src.github.io/oneDNN/dev_guide_verbose.html).
 
-4. Launch Jupyter Notebook: 
-> **Note**: You might need to register Conda kernel to Jupyter Notebook kernel, 
-feel free to check [the instruction](https://github.com/IntelAI/models/tree/master/docs/notebooks/perf_analysis#option-1-conda-environment-creation)
+**2. Launch Jupyter Notebook**
+
 ```
 jupyter notebook --ip=0.0.0.0 --port 8888 --allow-root
 ```
 
-4. Follow the instructions to open the URL with the token in your browser.
-5. Locate and select the Notebook:
+**3. Follow the instructions to open the URL with the token in your browser**
+
+**4. Select the Notebook**
+
 ```
 ResNet50_Inference.ipynb
 ```
-6. Change your Jupyter Notebook kernel to **PyTorch** or **PyTorch-GPU**.
 
-7. Run every cell in the Notebook in sequence.
+**5. Change the kernel to `pytorch-gpu`**
 
+**6. Run every cell in the Notebook in sequence**
 
 
 ### Docker
@@ -121,6 +177,11 @@ With successful execution, it will print out `[CODE_SAMPLE_COMPLETED_SUCCESSFULL
 ## 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.
+[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)
+
+*Other names and brands may be claimed as the property of others. [Trademarks](https://www.intel.com/content/www/us/en/legal/trademarks.html)
 
-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).