HawKsword/Non-local_pytorch

Implementation of Non-local Block.

Non-local_pytorch

• Implementation of Non-local Neural Block.

Statement

• You can find different kinds of non-local block in lib/.
• The code is tested on MNIST dataset. You can select the type of non-local block in lib/network.py.
• If there is something wrong in my code, please contact me, thanks!

Environment

• python 3.6
• pytorch 0.4.1

Update Records

1. Figure out how to implement the concatenation type, and add the code to lib/.
2. Fix the bug in lib/non_local.py (old version) when using multi-gpu. Someone shares the reason with me, and you can find it in here.
3. Fix the error of 3D pooling in lib/non_local.py (old version). Appreciate protein27 for pointing it out.
4. For convenience, I split the lib/non_local.py into four python files, and move the old versions (lib/non_loca.py and lib/non_local_simple_version.py) into lib/backup/.
5. modify the code to support pytorch 0.4.1, and move the code supporting pytorch 0.3.1
   to Non-Local_pytorch_0.3.1/.

Running Steps

1. Select the type of non-local block in lib/network.py.

   from lib.non_local_concatenation import NONLocalBlock2D
   from lib.non_local_gaussian import NONLocalBlock2D
   from lib.non_local_embedded_gaussian import NONLocalBlock2D
   from lib.non_local_dot_product import NONLocalBlock2D
   

2. Run demo_MNIST.py with one GPU or multi GPU.

   CUDA_VISIBLE_DEVICES=0,1 python demo_MNIST.py
   
   

Todo

• Experiments on Charades dataset.
• Experiments on COCO dataset.

Related Repositories

1. Non-local ResNet-50 TSM (Paper) on Kinetics dataset. They report that their model achieves a good performance of 75.6% on Kinetics, which is even higher than Non-local ResNet-50 I3D (Here).