From 1706eb8216248e54f68cad86f7ea4125c79a3ca4 Mon Sep 17 00:00:00 2001
From: Jiali Duan <jialiduan@meta.com>
Date: Tue, 15 Nov 2022 19:42:04 -0800
Subject: [PATCH] Simplify MC C++ hashing logic

Summary: To be consistent with CUDA hashing, the diff replaces boost hasher with a simplified hasher for storing unique global edge_ids.

Reviewed By: kjchalup

Differential Revision: D41140382

fbshipit-source-id: 2ce598e5edcf6369fe13bd15d1f5e014b252027b
---
 .../marching_cubes/marching_cubes_cpu.cpp     |  9 +---
 .../marching_cubes/marching_cubes_utils.h     | 43 +++++--------------
 2 files changed, 12 insertions(+), 40 deletions(-)

diff --git a/pytorch3d/csrc/marching_cubes/marching_cubes_cpu.cpp b/pytorch3d/csrc/marching_cubes/marching_cubes_cpu.cpp
index 5b780dc0..5d68db50 100644
--- a/pytorch3d/csrc/marching_cubes/marching_cubes_cpu.cpp
+++ b/pytorch3d/csrc/marching_cubes/marching_cubes_cpu.cpp
@@ -36,8 +36,6 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCpu(
 
   // Create tensor accessors
   auto vol_a = vol.accessor<float, 3>();
-  // vpair_to_edge maps a pair of vertex ids to its corresponding edge id
-  std::unordered_map<std::pair<int, int>, int64_t> vpair_to_edge;
   // edge_id_to_v maps from an edge id to a vertex position
   std::unordered_map<int64_t, Vertex> edge_id_to_v;
   // uniq_edge_id: used to remove redundant edge ids
@@ -64,12 +62,7 @@ std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCpu(
           const int e = _FACE_TABLE[cube.cubeindex][j];
           interp_points[e] = cube.VertexInterp(isolevel, e, vol_a);
 
-          auto vpair = cube.GetVPairFromEdge(e, W, H);
-          if (!vpair_to_edge.count(vpair)) {
-            vpair_to_edge[vpair] = vpair_to_edge.size();
-          }
-
-          int64_t edge = vpair_to_edge[vpair];
+          int64_t edge = cube.HashVpair(e, W, H, D);
           tri.push_back(edge);
           ps.push_back(interp_points[e]);
 
diff --git a/pytorch3d/csrc/marching_cubes/marching_cubes_utils.h b/pytorch3d/csrc/marching_cubes/marching_cubes_utils.h
index 48d93d39..486e0339 100644
--- a/pytorch3d/csrc/marching_cubes/marching_cubes_utils.h
+++ b/pytorch3d/csrc/marching_cubes/marching_cubes_utils.h
@@ -122,45 +122,24 @@ struct Cube {
     return p1 * (1 - ratio) + p2 * ratio;
   }
 
-  // Get a tuple of global vertex ID from a local edge ID
-  // Global vertex ID is calculated as (x + dx) + (y + dy) * W + (z + dz) * W *
-  // H
-
+  // Hash an edge into a global edge_id. The function binds an
+  // edge with an integer to address floating point precision issue.
+  //
   // Args:
-  //     edge: local edge ID in the cube
-  //     W: width of x dimension
-  //     H: height of y dimension
+  //    v1_id: global id of vertex 1
+  //    v2_id: global id of vertex 2
+  //    W: width of the 3d grid
+  //    H: height of the 3d grid
+  //    D: depth of the 3d grid
   //
   // Returns:
-  //     a pair of global vertex ID
+  //    hashing for a pair of vertex ids
   //
-  std::pair<int, int> GetVPairFromEdge(const int edge, int W, int H) {
+  int64_t HashVpair(const int edge, int W, int H, int D) {
     const int v1 = _EDGE_TO_VERTICES[edge][0];
     const int v2 = _EDGE_TO_VERTICES[edge][1];
     const int v1_id = p[v1].x + p[v1].y * W + p[v1].z * W * H;
     const int v2_id = p[v2].x + p[v2].y * W + p[v2].z * W * H;
-    return std::make_pair(v1_id, v2_id);
+    return (int64_t)v1_id * (W + W * H + W * H * D) + (int64_t)v2_id;
   }
 };
-
-// helper functions for hashing
-namespace std {
-// Taken from boost library to combine several hash functions
-template <class T>
-inline void hash_combine(size_t& s, const T& v) {
-  std::hash<T> h;
-  s ^= h(v) + 0x9e3779b9 + (s << 6) + (s >> 2);
-}
-
-// Function for hashing a pair of vertices
-template <>
-struct hash<std::pair<int, int>> {
-  size_t operator()(const std::pair<int, int>& p) const {
-    size_t res = 0;
-    hash_combine(res, p.first);
-    hash_combine(res, p.second);
-    return res;
-  }
-};
-
-} // namespace std