imagenet-multiGPU.torchnet

_Inspired by imagenet-multiGPU.torch, uses torchnet dataloaders and engines.

• ClassificationLogger is a combination of meters which can be used anywhere.
• RandomDataset is useful for random sampling.

Trained Model

Pretrained Alexnet using this code

(Logs at http://imgur.com/a/QWlYr)

(Final Train Acc: 59.33% | Val Acc: 58.59% | Val mAP: 0.62 after 55 epochs)

• Note

1. For the script to work without GPU, lots of lines (like cutorch.synchronize()) will have to be removed.
2. You will need to prepare the val folder into the flat folder style. See imagenet-multiGPU.torch for instructions.
3. setGPU() does not work with multiple GPUs (probably change the createDataParallelTable to setGPU() )