Installing TensorFlow

In this example, we will install TensorFlow.

Step 1: Request an interactive session on a GPU node with Ampere architecture GPUs

interact -q gpu -g 1 -f ampere -m 20g -n 4

Here, -f = feature. We only need to build on Ampere once.

Step 2: Once your session has started on a compute node, run nvidia-smi to verify the GPU and then load the appropriate modules

module load python/3.11.0 openssl/3.0.0 cuda/11.7.1 cudnn/8.2.0

Step 3: Create and activate the virtual environment

virtualenv -p python3 tensorflow.venv
source tensorflow.venv/bin/activate

Step 4: Install the required packages

pip install --upgrade pip
 pip install tensorflow

Step 5: Test that PyTorch is able to detect GPUs

python
>>> import tensorflow as tf
>>> tf.test.is_gpu_available(cuda_only=False, min_cuda_compute_capability=None)
True

If the above function returns True, then you are all set.