install tensorflow keras in wsl2 for windows with nvidia gpu

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installing tensorflow with keras on windows subsystem for linux 2 (wsl2) using an nvidia gpu involves several steps, including setting up wsl2, installing necessary drivers, and finally installing tensorflow with keras. below is a step-by-step tutorial to help you through the process.

step 1: install wsl2

1. **enable wsl**:
open powershell as administrator and run the following commands:

this command installs wsl and the latest ubuntu distribution by default. you may need to restart your computer.

2. **set wsl2 as default**:
after rebooting, open powershell again and run:


3. **install a linux distribution**:
if ubuntu wasn't installed by default, you can install it from the microsoft store.

step 2: install nvidia drivers

1. **install nvidia driver**:
download and install the latest nvidia driver that supports wsl2 from the nvidia website. make sure it's compatible with your gpu.

2. **install cuda toolkit**:
you don’t need to install cuda separately as the tensorflow package includes it. however, ensure that your nvidia driver is up to date.

step 3: update ubuntu and install dependencies

1. **launch your wsl2 ubuntu terminal**:
you can find it by searching "ubuntu" in the start menu.

2. **update and upgrade packages**:


3. **install essential packages**:


step 4: set up a python virtual environment (optional but recommended)

1. **install `venv`**:


2. **create a virtual environment**:


3. **activate the virtual environment**:


step 5: install tensorflow with keras

1. **upgrade pip**:


2. **install tensorflow**:


3. **verify the installation**:
you can run the following python code to verify that tensorflow is installed correctly and can access the gpu.



step 6: run a simple tensorflow/keras example

you can use the following example to verify that tensorflow with keras is working properly.

1. **create a new script `keras_example.py`**:


2. **add the following cod ...

#TensorFlow #WSL2 #NVIDIA_GPU

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