snap-stanford / caw Goto Github PK

Hi dear authors,
I have noticed that the processed file contains node features and edge features for all datasets. As far as I know, the original ENRON/UCI/social-evolution datasets do not contain any node/edge features. I have checked your paper, but the paper doesn't mention any details for initializing node or edge features. Can you describe the details of initializing node or edge features in these .npy files? Thanks!

The baseline's code link is unvaild, and it seems that the repo doesn't provide, too.

Nice work!
I had some questions regarding the datasets used for the experiments.

The UCI dataset mentioned in the paper (Appendix C page 16) references (http://konect.cc/networks/opsahl-ucforum/).
The dataset is between users and forums (a bipartite network.) Has 1,421 total nodes with 899 users and 522 forums. It has 33,720 interactions.

However, the processed data provided in this repo and probably used to report numbers in the paper has 1,899 total nodes and 59,835 interactions.

On closer look at the processed dataset I find that you have actually used the UCI Messages dataset (http://konect.cc/networks/opsahl-ucsocial/) dataset which is not bipartite and the interactions are messages between user nodes.

If not, it would be great if you can clarify this discrepancy. Either the description in paper about the UCI dataset is incorrect or the processed dataset provided is wrong.

I tried to run CAWN on reddit dataset. The command I tried is:
python main.py -d reddit --pos_dim 108 --bs 100 --n_degree 32 1 1 --mode t --bias 1e-8 --pos_enc lp --walk_pool sum --gpu 1
I found that the memory cost of the training process continues to increase. Why is that?

in the log the results are changed

Hello!
I tried your execution command for the UCI dataset in READEME.md, but I didn't get good experimental results like the paper. I tried to adjust the relevant parameter information, but there was no greater improvement. I would like to ask how can I reproduce the experimental results in the paper?
Thank you~

It first through the following warning when I try to compile pytorch using source file

CMake Warning (dev) at /usr/share/cmake3/Modules/FindPackageHandleStandardArgs.cmake:272 (message):
The package name passed to find_package_handle_standard_args (OpenMP_CXX)
does not match the name of the calling package (OpenMP). This can lead to
problems in calling code that expects find_package result variables
(e.g., _FOUND) to follow a certain pattern.
Call Stack (most recent call first):
cmake/Modules/FindOpenMP.cmake:565 (find_package_handle_standard_args)
cmake/Modules/FindMKL.cmake:213 (FIND_PACKAGE)
cmake/Modules/FindMKL.cmake:307 (CHECK_ALL_LIBRARIES)
cmake/Dependencies.cmake:140 (find_package)
CMakeLists.txt:564 (include)
This warning is for project developers. Use -Wno-dev to suppress it.

And,

• MKL OpenMP type: GNU
  -- MKL OpenMP library: -fopenmp
  -- Brace yourself, we are building NNPACK
  -- NNPACK backend is x86-64
  -- Failed to find LLVM FileCheck
  -- git Version: v1.4.0-505be96a
  -- Version: 1.4.0
  -- Performing Test HAVE_STD_REGEX -- compiled but failed to run
  -- Performing Test HAVE_GNU_POSIX_REGEX -- failed to compile
  -- Performing Test HAVE_POSIX_REGEX -- compiled but failed to run
  CMake Error at third_party/benchmark/CMakeLists.txt:231 (message):
  Failed to determine the source files for the regular expression backend

and it exit with saying -- Configuring incomplete, errors occurred!

Any help how to configure OpenMP?