Replace unordered_map with phmap in hetero_sample (#266)

csrc/cpu/neighbor_sample_cpu.cpp

@@ -2,8 +2,6 @@
 
 #include "utils.h"
 
-#include "parallel_hashmap/phmap.h"
-
 #ifdef _WIN32
 #include <process.h>
 #endif
@@ -142,21 +140,21 @@ hetero_sample(const vector<node_t> &node_types,
               const int64_t num_hops) {
 
   // Create a mapping to convert single string relations to edge type triplets:
-  unordered_map<rel_t, edge_t> to_edge_type;
+  phmap::flat_hash_map<rel_t, edge_t> to_edge_type;
   for (const auto &k : edge_types)
     to_edge_type[get<0>(k) + "__" + get<1>(k) + "__" + get<2>(k)] = k;
 
   // Initialize some data structures for the sampling process:
-  unordered_map<node_t, vector<int64_t>> samples_dict;
-  unordered_map<node_t, unordered_map<int64_t, int64_t>> to_local_node_dict;
-  unordered_map<node_t, vector<int64_t>> root_time_dict;
+  phmap::flat_hash_map<node_t, vector<int64_t>> samples_dict;
+  phmap::flat_hash_map<node_t, phmap::flat_hash_map<int64_t, int64_t>> to_local_node_dict;
+  phmap::flat_hash_map<node_t, vector<int64_t>> root_time_dict;
   for (const auto &node_type : node_types) {
     samples_dict[node_type];
     to_local_node_dict[node_type];
     root_time_dict[node_type];
   }
 
-  unordered_map<rel_t, vector<int64_t>> rows_dict, cols_dict, edges_dict;
+  phmap::flat_hash_map<rel_t, vector<int64_t>> rows_dict, cols_dict, edges_dict;
   for (const auto &kv : colptr_dict) {
     const auto &rel_type = kv.key();
     rows_dict[rel_type];
@@ -188,7 +186,7 @@ hetero_sample(const vector<node_t> &node_types,
     }
   }
 
-  unordered_map<node_t, pair<int64_t, int64_t>> slice_dict;
+  phmap::flat_hash_map<node_t, pair<int64_t, int64_t>> slice_dict;
   for (const auto &kv : samples_dict)
     slice_dict[kv.first] = {0, kv.second.size()};
 
@@ -339,7 +337,7 @@ hetero_sample(const vector<node_t> &node_types,
   }
 
   if (!directed) { // Construct the subgraph among the sampled nodes:
-    unordered_map<int64_t, int64_t>::iterator iter;
+    phmap::flat_hash_map<int64_t, int64_t>::iterator iter;
     for (const auto &kv : colptr_dict) {
       const auto &rel_type = kv.key();
       const auto &edge_type = to_edge_type[rel_type];

csrc/cpu/utils.h

 #pragma once
 
 #include "../extensions.h"
+#include "parallel_hashmap/phmap.h"
 
 #define CHECK_CPU(x) AT_ASSERTM(x.device().is_cpu(), #x " must be CPU tensor")
 #define CHECK_INPUT(x) AT_ASSERTM(x, "Input mismatch")
@@ -27,7 +28,7 @@ inline torch::Tensor from_vector(const std::vector<scalar_t> &vec,
 
 template <typename key_t, typename scalar_t>
 inline c10::Dict<key_t, torch::Tensor>
-from_vector(const std::unordered_map<key_t, std::vector<scalar_t>> &vec_dict,
+from_vector(const phmap::flat_hash_map<key_t, std::vector<scalar_t>> &vec_dict,
             bool inplace = false) {
   c10::Dict<key_t, torch::Tensor> out_dict;
   for (const auto &kv : vec_dict)
@@ -91,7 +92,7 @@ template <bool replace>
 inline void
 uniform_choice(const int64_t population, const int64_t num_samples,
                const int64_t *idx_data, std::vector<int64_t> *samples,
-               std::unordered_map<int64_t, int64_t> *to_local_node) {
+               phmap::flat_hash_map<int64_t, int64_t> *to_local_node) {
 
   if (population == 0 || num_samples == 0)
     return;