Commit ec7c59f0 authored by rusty1s's avatar rusty1s
Browse files

initialize random seed

parent 84b46170
...@@ -15,6 +15,8 @@ ego_k_hop_sample_adj_cpu(torch::Tensor rowptr, torch::Tensor col, ...@@ -15,6 +15,8 @@ ego_k_hop_sample_adj_cpu(torch::Tensor rowptr, torch::Tensor col,
torch::Tensor idx, int64_t depth, torch::Tensor idx, int64_t depth,
int64_t num_neighbors, bool replace) { int64_t num_neighbors, bool replace) {
srand(time(NULL) + 1000 * getpid()); // Initialize random seed.
std::vector<torch::Tensor> out_rowptrs(idx.numel() + 1); std::vector<torch::Tensor> out_rowptrs(idx.numel() + 1);
std::vector<torch::Tensor> out_cols(idx.numel()); std::vector<torch::Tensor> out_cols(idx.numel());
std::vector<torch::Tensor> out_n_ids(idx.numel()); std::vector<torch::Tensor> out_n_ids(idx.numel());
......
...@@ -101,6 +101,8 @@ hgt_sample_cpu(const c10::Dict<rel_t, torch::Tensor> &colptr_dict, ...@@ -101,6 +101,8 @@ hgt_sample_cpu(const c10::Dict<rel_t, torch::Tensor> &colptr_dict,
const c10::Dict<node_t, vector<int64_t>> &num_samples_dict, const c10::Dict<node_t, vector<int64_t>> &num_samples_dict,
const int64_t num_hops) { const int64_t num_hops) {
srand(time(NULL) + 1000 * getpid()); // Initialize random seed.
// Create a mapping to convert single string relations to edge type triplets: // Create a mapping to convert single string relations to edge type triplets:
unordered_map<rel_t, edge_t> to_edge_type; unordered_map<rel_t, edge_t> to_edge_type;
for (const auto &kv : colptr_dict) { for (const auto &kv : colptr_dict) {
......
...@@ -11,6 +11,8 @@ tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor> ...@@ -11,6 +11,8 @@ tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor>
sample(const torch::Tensor &colptr, const torch::Tensor &row, sample(const torch::Tensor &colptr, const torch::Tensor &row,
const torch::Tensor &input_node, const vector<int64_t> num_neighbors) { const torch::Tensor &input_node, const vector<int64_t> num_neighbors) {
srand(time(NULL) + 1000 * getpid()); // Initialize random seed.
// Initialize some data structures for the sampling process: // Initialize some data structures for the sampling process:
vector<int64_t> samples; vector<int64_t> samples;
unordered_map<int64_t, int64_t> to_local_node; unordered_map<int64_t, int64_t> to_local_node;
...@@ -121,6 +123,8 @@ hetero_sample(const vector<node_t> &node_types, ...@@ -121,6 +123,8 @@ hetero_sample(const vector<node_t> &node_types,
const c10::Dict<rel_t, vector<int64_t>> &num_neighbors_dict, const c10::Dict<rel_t, vector<int64_t>> &num_neighbors_dict,
const int64_t num_hops) { const int64_t num_hops) {
srand(time(NULL) + 1000 * getpid()); // Initialize random seed.
// Create a mapping to convert single string relations to edge type triplets: // Create a mapping to convert single string relations to edge type triplets:
unordered_map<rel_t, edge_t> to_edge_type; unordered_map<rel_t, edge_t> to_edge_type;
for (const auto &k : edge_types) for (const auto &k : edge_types)
......
...@@ -11,6 +11,8 @@ sample_adj_cpu(torch::Tensor rowptr, torch::Tensor col, torch::Tensor idx, ...@@ -11,6 +11,8 @@ sample_adj_cpu(torch::Tensor rowptr, torch::Tensor col, torch::Tensor idx,
CHECK_CPU(idx); CHECK_CPU(idx);
CHECK_INPUT(idx.dim() == 1); CHECK_INPUT(idx.dim() == 1);
srand(time(NULL) + 1000 * getpid()); // Initialize random seed.
auto rowptr_data = rowptr.data_ptr<int64_t>(); auto rowptr_data = rowptr.data_ptr<int64_t>();
auto col_data = col.data_ptr<int64_t>(); auto col_data = col.data_ptr<int64_t>();
auto idx_data = idx.data_ptr<int64_t>(); auto idx_data = idx.data_ptr<int64_t>();
......
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