Hi, I used a ResNet34 backbone to train on (1, 128, 128) images with a batch size of 128. The total allocated memory is >35GB. According to the post, a ResNet50 on (3,256,256) images with a batch size of 96 only consumes 10GB. I am wondering if anyone else experiences the same issue and if there is any clue as to why this network takes such a lot of memory.
Hi, I used a ResNet34 backbone to train on (1, 128, 128) images with a batch size of 128. The total allocated memory is >35GB. According to the post, a ResNet50 on (3,256,256) images with a batch size of 96 only consumes 10GB. I am wondering if anyone else experiences the same issue and if there is any clue as to why this network takes such a lot of memory.