Reshape for faces_packed_to_edges_packed

Summary:
As pointed out in #328, we had an indexing operation where a reshape would do and be faster. The resulting faces_packed_to_edges_packed is no longer contiguous.

Also fix a use of faces_packed_to_edges_packed which might modify the object unintentionally.

Reviewed By: theschnitz

Differential Revision: D24390292

fbshipit-source-id: 225677d8fcc1d6b76efad7706718ecdb5182ffe1

pytorch3d/ops/subdivide_meshes.py

@@ -103,8 +103,9 @@ class SubdivideMeshes(nn.Module):
         verts_packed = meshes.verts_packed()
         with torch.no_grad():
             faces_packed = meshes.faces_packed()
-            faces_packed_to_edges_packed = meshes.faces_packed_to_edges_packed()
-            faces_packed_to_edges_packed += verts_packed.shape[0]
+            faces_packed_to_edges_packed = (
+                meshes.faces_packed_to_edges_packed() + verts_packed.shape[0]
+            )
 
             f0 = torch.stack(
                 [

pytorch3d/structures/meshes.py

@@ -1035,9 +1035,7 @@ class Meshes(object):
         self._edges_packed = torch.stack([u // V, u % V], dim=1)
         self._edges_packed_to_mesh_idx = edge_to_mesh[unique_idx]
 
-        face_to_edge = torch.arange(3 * F).view(3, F).t()
-        face_to_edge = inverse_idxs[face_to_edge]
-        self._faces_packed_to_edges_packed = face_to_edge
+        self._faces_packed_to_edges_packed = inverse_idxs.reshape(3, F).t()
 
         # Compute number of edges per mesh
         num_edges_per_mesh = torch.zeros(self._N, dtype=torch.int32, device=self.device)