TensorFlow : Install2025/10/02

	Install TensorFlow which is the Machine Learning Library. Set up TensorFlow to use the NVIDIA GPU installed in it.
[1]	Install CUDA, refer to here.
[2]	Install Python 3, refer to here.
[3]	Install cuDNN (CUDA Deep Neural Network library) and other required packages.

root@dlp:~#

apt -y install nvidia-cudnn python3-pip python3-dev gcc g++ make

[4]	Login as a common user and prepare Python virtual environment to install TensorFlow.

debian@dlp:~$

python3 -m venv --system-site-packages ~/tensorflow

debian@dlp:~$

source ~/tensorflow/bin/activate

(tensorflow) debian@dlp:~$

[5]	Install TensorFlow.

(tensorflow) debian@dlp:~$

pip3 install --upgrade tensorflow[and-cuda]

# verify to run TensorFlow

(tensorflow) debian@dlp:~$

python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"

2025-10-01 04:06:27.705497: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]

(tensorflow) debian@dlp:~$ python3 -c "from tensorflow.python.client import device_lib; device_lib.list_local_devices()" 
2025-10-01 04:09:28.221160: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
I0000 00:00:1759306170.118694    8651 gpu_device.cc:2020] Created device /device:GPU:0 with 10393 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3060, pci bus id: 0000:05:00.0, compute capability: 8.6

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