Pytorch ImageNet training codes with various tricks, lr schedulers, distributed training, mixed precision training, DALI dataloader etc. We hope this repo can help ImageNet experiments in NAS researches.

CUDA_VISIBLE_DEVICES=0 python -u train.py --train_root /path/to/imagenet/train_set --val_root /path/to/imagenet/val_set --train_list /path/to/imagenet/train_list --val_list /path/to/imagenet/val_list

Please refer to train_example.sh for more details.

CUDA_VISIBLE_DEVICES=0 python -u test.py --val_root /path/to/imagenet/val_set --val_list /path/to/imagenet/val_list --weights /path/to/pretrained_weights

Please refer to test_example.sh for more details.

Please refer to profile_example.py for more details.

Python == 3.7.6
pytorch == 1.5.1
torchvision == 0.6.1
nvidia.dali == 0.22.0
cuDNN == 7.6.5
apex from this link

This repo is released under the MIT license. Please see the LICENSE file for more information.