README

Install tensorflow-gpu in venv

1. Navigate to the venv folder, e.g.: C:\Users\AStringfield\repositories\FashionMNIST\venv
2. Run the pip commmand: pip pip install tensorflow-gpu

Note

At the time of installing, the recommended tensorflow-gpu version based on the installed versions of CUDA and cuDNN libraries was tensorflow-gpu-2.6, which had previously been used with success (installed in the base Python directory, not the new venv for this project). However, when I ran the pip command listed above, this installed tensorflow-gpu-2.7. Even though the CUDA/cuDNN dependencies hadn't been installed for this version, running the following test script indicated that tensorflow was able to detect my graphics card with no problem:

import tensorflow as tf
with tf.compat.v1.Session() as sess:
    devices = sess.list_devices()
devices

2021-11-07 07:14:16.970792: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-11-07 07:14:17.482152: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 2154 MB memory:  -> device: 0, name: Quadro T1000 with Max-Q Design, pci bus id: 0000:01:00.0, compute capability: 7.5

This was then validated by running training on a test model in tf_gpu_validation.py and observing the GPU usage