TensorFlow GPU Installation Guide

Test whether your current environment already supports:

import tensorflow as tf

if tf.test.gpu_device_name():
    print(f"Default GPU device: {
      
      tf.test.gpu_device_name()}")
else:
    print("GPU device not found. Please check your settings.")

If the GPU is properly configured, there will be:

Default GPU device: /device:GPU:0

Install TensorFlow using pip

Note: TensorFlow 2.10 is the last TensorFlow release. Supported GPUs on native Windows. Starting with TensorFlow 2.11, you need to install TensorFlow in WSL2, or install TensorFlow-cpu

The default has been followed: Miniconda

Create a new conda environment

conda create --name tfGPU python=3.9

GPU installation

First install the NVIDIA GPU driver,

Then install CUDA, cuDNN with conda

conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0

Install TensorFlow

First upgrade the latest pip

pip install --upgrade pip

TensorFlow 2.10 is the last TensorFlow release. Supported GPUs on native Windows.
So install a version prior to 2.11

pip install "tensorflow<2.11" 

Verify TensorFlow CPU installation

python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"

Output tensor tensor data, it is installed.

Verify TensorFlow GPU installation

python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"