prepare 0.1

scripts/lint.sh

@@ -6,6 +6,13 @@ cd $(dirname $0)/..
 list_py_srcs() {
     find ./benchmarks -type f | grep .py$
     find ./srcs/python -type f | grep .py$
+    find ./tests/python -type f | grep .py$
+}
+
+list_cpp_srcs() {
+    find ./srcs/cpp -type f | grep .cpp$
+    find ./srcs/cpp -type f | grep .hpp$
+    find ./srcs/cpp -type f | grep .cu$
 }
 
 fmt_py() {
@@ -15,12 +22,24 @@ fmt_py() {
     yapf -i $1
 }
 
+fmt_cpp() {
+    clang-format -i $1
+}
+
 fmt_all_py() {
     for src in $(list_py_srcs); do
         echo "fmt_py $src"
         fmt_py $src
     done
 }
 
+fmt_all_cpp() {
+    for src in $(list_cpp_srcs); do
+        echo "fmt_py $src"
+        fmt_cpp $src
+    done
+}
+
 # TODO: also format c++ code
 fmt_all_py
+fmt_all_cpp

setup.py

@@ -63,10 +63,10 @@ def create_extension(with_cuda=False):
 
 setup(
     name='torch_quiver',
-    version='0.0.23',
+    version='0.1.0',
     author='Zeyuan Tan',
     author_email='[email protected]',
-    url='https://github.com/xpex-ai/gpex',
+    url='https://github.com/quiver-team/torch-quiver',
     description=('Distributed Graph Learning Library for Pytorch Geometric'),
     keywords=['pytorch', 'distributed', 'graph'],
     license='Apache',

srcs/cpp/include/quiver/cuda_random.cu.hpp

@@ -4,24 +4,6 @@
 
 constexpr int WARP_SIZE = 32;
 
-/**
- * @brief Perform row-wise sampling on a CSR matrix, and generate a COO matrix,
- * without replacement.
- *
- * @tparam T The ID type used for matrices.
- * @tparam BLOCK_ROWS The number of rows covered by each threadblock.
- * @param rand_seed The random seed to use.
- * @param num_picks The number of non-zeros to pick per row.
- * @param num_rows The number of rows to pick.
- * @param in_rows The set of rows to pick.
- * @param in_ptr The indptr array of the input CSR.
- * @param in_index The indices array of the input CSR.
- * @param data The data array of the input CSR.
- * @param out_ptr The offset to write each row to in the output COO.
- * @param out_rows The rows of the output COO (output).
- * @param out_cols The columns of the output COO (output).
- * @param out_idxs The data array of the output COO (output).
- */
 template <typename T, int BLOCK_WARPS, int TILE_SIZE>
 __global__ void CSRRowWiseSampleKernel(
     const uint64_t rand_seed, int num_picks, const int64_t num_rows,