Hi @ptrblck,
Thank you for your quick responses.
I encountered this problem in the evaluation mode (prior to training), and the GPU memory remains “constantly occupied” even after the evaluation has been completed.
I am finding ways to release this “occupied” GPU memory so that the training mode is executed without any GPU memory shortage issue.
And this problem only occurs if the pre-trained ResNet50 is used. Is that bcoz of the model complexity where a large portion of the GPU memory is allocated and kept in the cache even in the evaluation mode?