TF2 Model: How run training on GPU, and evaluation on CPU
In my case, the solution is into evaluation function define:
os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
I run training phase of TF2 model (based on object detection pre-trained models from TF2-Models Zoo) on GPU (Nvidia 3070).
Is there some way to define evaluation phase (for checkpoints created by training) on CPU?

Cause train phase allocates almost all memory of GPU, I cant run both of them (train and eval) on GPU.

OS - Ubuntu 20.04

GPU - Nvidia 3070 (driver 460)

TF - 2.4.1

Python - 3.8.5


Thank you.