Install Tensorflow/Keras in WSL2 for Applications of Deep Neural Networks

Deep learning has become a powerful tool in the field of artificial intelligence, and Tensorflow and Keras are two of the most popular libraries for building and training deep neural networks. If you’re using Windows Subsystem for Linux 2 (WSL2) and want to take advantage of these libraries, you’ll need to install them within your WSL2 environment. In this article, we’ll walk you through the process of installing Tensorflow and Keras in WSL2 for your deep learning applications.

Step 1: Set Up WSL2

If you haven’t already set up WSL2 on your Windows machine, you’ll need to do so before you can install Tensorflow and Keras. Follow the instructions provided by Microsoft to enable WSL2 on your system.

Step 2: Install Python and Pip

Once you have WSL2 up and running, open the terminal and install Python and Pip by running the following commands:

sudo apt update
sudo apt install python3 python3-pip

Step 3: Install Tensorflow and Keras

Now that Python and Pip are installed, you can use Pip to install Tensorflow and Keras. Run the following commands in the terminal:

pip install tensorflow
pip install keras

These commands will download and install the latest versions of Tensorflow and Keras in your WSL2 environment.

Step 4: Verify Your Installation

To ensure that Tensorflow and Keras have been installed correctly, you can create a simple Python script to test them. Use your favorite text editor to create a file called test_tensorflow.py with the following contents:

import tensorflow as tf
import keras

print(tf.__version__)
print(keras.__version__)

Save the file and run it in the terminal with the command python test_tensorflow.py. If everything is set up correctly, you should see the versions of Tensorflow and Keras printed to the console.

Conclusion

With Tensorflow and Keras installed in your WSL2 environment, you’re now ready to start building and training deep neural networks for your applications. These libraries provide a wealth of tools and utilities for working with complex neural networks, and WSL2 allows you to take advantage of their power from within your Windows environment. Happy coding!