remove unused files

CMakeLists.txt

@@ -155,8 +155,8 @@ endif()
 
 # add libsampler.so
 set(SAMLPER_NAME "${PROJECT_NAME}_sampler")
-set(BOOST_INCLUDE_DIRS "${CMAKE_SOURCE_DIR}/third_party/boost_1_83_0")
-include_directories(${BOOST_INCLUDE_DIRS})
+# set(BOOST_INCLUDE_DIRS "${CMAKE_SOURCE_DIR}/third_party/boost_1_83_0")
+# include_directories(${BOOST_INCLUDE_DIRS})
 
 file(GLOB_RECURSE SAMPLER_SRCS "csrc/sampler/*.cpp")
 add_library(${SAMLPER_NAME} SHARED ${SAMPLER_SRCS})

csrc/sampler/include/temporal_utils.h

@@ -5,9 +5,9 @@
 #include <vector>
 #include <iostream>
 #include <map>
-#include <boost/thread/mutex.hpp>
+// #include <boost/thread/mutex.hpp>
 using namespace std;
-#define MTX boost::mutex
+#define MTX std::mutex
 
 namespace py = pybind11;
 namespace th = torch;

detect_cuda_compute_capabilities.cu

-#include <cuda_runtime.h>
-#include <cstdio>
-int main()
-{
-  int count = 0;
-  if (cudaSuccess != cudaGetDeviceCount(&count)) return -1;
-  if (count == 0) return -1;
-  for (int device = 0; device < count; ++device)
-  {
-    cudaDeviceProp prop;
-    if (cudaSuccess == cudaGetDeviceProperties(&prop, device))
-      std::printf("%d.%d ", prop.major, prop.minor);
-  }
-  return 0;
-}

detect_cuda_version.cc

-#include <cuda.h>
-#include <cstdio>
-int main() {
-  printf("%d.%d", CUDA_VERSION / 1000, (CUDA_VERSION / 10) % 100);
-  return 0;
-}

install.sh

@@ -3,11 +3,11 @@
 mkdir -p build && cd build
 cmake .. \
     -DCMAKE_EXPORT_COMPILE_COMMANDS=ON \
-    -DCMAKE_PREFIX_PATH="/home/zlj/.miniconda3/envs/dgnn/lib/python3.8/site-packages" \
-    -DPython3_ROOT_DIR="/home/zlj/.miniconda3/envs/dgnn" \
-    -DCUDA_TOOLKIT_ROOT_DIR="/home/zlj/local/cuda-12.2" \
+    -DCMAKE_PREFIX_PATH="/home/hwj/.miniconda3/envs/sgl/lib/python3.10/site-packages" \
+    -DPython3_ROOT_DIR="/home/hwj/.miniconda3/envs/sgl" \
+    -DCUDA_TOOLKIT_ROOT_DIR="/home/hwj/.local/cuda-11.8" \
 && make -j32 \
 && rm -rf ../starrygl/lib \
 && mkdir ../starrygl/lib \
 && cp lib*.so ../starrygl/lib/ \
-&& patchelf --set-rpath '$ORIGIN:$ORIGIN/lib' --force-rpath ../starrygl/lib/*.so
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+&& patchelf --set-rpath '$ORIGIN:$ORIGIN/lib' --force-rpath ../starrygl/lib/*.so

requirements.txt

@@ -12,4 +12,5 @@ torch_cluster==1.6.3+pt21cu118
 torch_spline_conv==1.2.2+pt21cu118
 
 ogb
-tqdm
\ No newline at end of file
+tqdm
+networkx
\ No newline at end of file

starrygl/sample/part_utils/partition_tgnn.py

-import parser
 from torch_sparse import SparseTensor
 from torch_geometric.data import Data
 from torch_geometric.utils import degree

tes.py

-from concurrent.futures import ThreadPoolExecutor
-
-def my_function():
-    # 执行一些操作...
-    print('hi')
-    return 'result'
-
-# 创建线程池
-executor = ThreadPoolExecutor()
-
-# 提交任务并获取Future对象
-future = executor.submit(my_function)
-
-# 等待任务执行完成并获取结果
-future.wait()
-result = future.result()
-
-# 打印结果
-print(result)  # 'result'

test.sh

-nohup python train_tgnn.py --dataname TaoBao --world_size 4 --rank 0 > taobao4.out &
-nohup python train_tgnn.py --dataname TaoBao --world_size 4 --rank 1 > taobao4.out &
-nohup python train_tgnn.py --dataname TaoBao --world_size 4 --rank 2 > taobao4.out &
-nohup python train_tgnn.py --dataname TaoBao --world_size 4 --rank 3 > taobao4.out &
-
-nohup python train_tgnn.py --dataname GDELT --world_size 4 --rank 0 > GDELT4.out &
-nohup python train_tgnn.py --dataname GDELT --world_size 4 --rank 1 > GDELT4.out &
-nohup python train_tgnn.py --dataname GDELT --world_size 4 --rank 2 > GDELT4.out &
-nohup python train_tgnn.py --dataname GDELT --world_size 4 --rank 3 > GDELT4.out &
-
-nohup python train_tgnn.py --dataname ML25M --world_size 2 --rank 0 > ML25M2.out &
-nohup python train_tgnn.py --dataname ML25M --world_size 2 --rank 1 > ML25M2.out &
-
-nohup python train_tgnn.py --dataname TaoBao --world_size 2 --rank 0 > TaoBao2.out &
-nohup python train_tgnn.py --dataname TaoBao --world_size 2 --rank 1 > TaoBao2.out &
-
-
-
-nohup python train_tgnn.py --dataname ML25M --world_size 1 --rank 0 > ML25M1.out &
-nohup python train_tgnn.py --dataname TaoBao --world_size 1 --rank 0 > TaoBao1.out &
-nohup python train_tgnn.py --dataname GDELT --world_size 1 --rank 0 > GDELT1.out &
\ No newline at end of file