Increase code coverage of subdivide_meshes

Summary: Increase code coverage of subdivide_meshes and re-include it in code coverage test

Reviewed By: bottler

Differential Revision: D29097476

fbshipit-source-id: 3403ae38a90c4b53f24188eed11faae202a235b5

pytorch3d/ops/subdivide_meshes.py

@@ -6,7 +6,7 @@ import torch.nn as nn
 from pytorch3d.structures import Meshes
 
 
-class SubdivideMeshes(nn.Module):  # pragma: no cover
+class SubdivideMeshes(nn.Module):
     """
     Subdivide a triangle mesh by adding a new vertex at the center of each edge
     and dividing each face into four new faces. Vectors of vertex
@@ -396,7 +396,7 @@ def create_verts_index(verts_per_mesh, edges_per_mesh, device=None):
     return verts_idx
 
 
-def create_faces_index(faces_per_mesh, device=None):  # pragma: no cover
+def create_faces_index(faces_per_mesh, device=None):
     """
     Helper function to group the faces indices for each mesh. New faces are
     stacked at the end of the original faces tensor, so in order to have

tests/test_subdivide_meshes.py

@@ -11,7 +11,7 @@ from pytorch3d.utils.ico_sphere import ico_sphere
 
 
 class TestSubdivideMeshes(TestCaseMixin, unittest.TestCase):
-    def test_simple_subdivide(self):
+    def simple_subdivide(self, with_init=False):
         # Create a mesh with one face and check the subdivided mesh has
         # 4 faces with the correct vertex coordinates.
         device = torch.device("cuda:0")
@@ -23,7 +23,8 @@ class TestSubdivideMeshes(TestCaseMixin, unittest.TestCase):
         )
         faces = torch.tensor([[0, 1, 2]], dtype=torch.int64, device=device)
         mesh = Meshes(verts=[verts], faces=[faces])
-        subdivide = SubdivideMeshes()
+        mesh_init = mesh.clone() if with_init else None
+        subdivide = SubdivideMeshes(meshes=mesh_init)
         new_mesh = subdivide(mesh)
 
         # Subdivided face:
@@ -61,6 +62,12 @@ class TestSubdivideMeshes(TestCaseMixin, unittest.TestCase):
         self.assertClose(new_faces, gt_subdivide_faces)
         self.assertTrue(new_verts.requires_grad == verts.requires_grad)
 
+    def test_simple_subdivide(self):
+        self.simple_subdivide()
+
+    def test_simple_subdivide_with_init(self):
+        self.simple_subdivide(with_init=True)
+
     def test_heterogeneous_meshes(self):
         device = torch.device("cuda:0")
         verts1 = torch.tensor(