diff --git a/pytorch3d/renderer/mesh/texturing.py b/pytorch3d/renderer/mesh/texturing.py
index fbcae3f8..1891e3fa 100644
--- a/pytorch3d/renderer/mesh/texturing.py
+++ b/pytorch3d/renderer/mesh/texturing.py
@@ -107,7 +107,9 @@ def interpolate_vertex_colors(fragments, meshes) -> torch.Tensor:
         There will be one C dimensional value for each element in
         fragments.pix_to_face.
     """
-    vertex_textures = meshes.textures.verts_rgb_padded().view(-1, 3)  # (V, C)
+    vertex_textures = meshes.textures.verts_rgb_padded().reshape(
+        -1, 3
+    )  # (V, C)
     vertex_textures = vertex_textures[meshes.verts_padded_to_packed_idx(), :]
     faces_packed = meshes.faces_packed()
     faces_textures = vertex_textures[faces_packed]  # (F, 3, C)
diff --git a/pytorch3d/renderer/utils.py b/pytorch3d/renderer/utils.py
index 7f0effca..20d3bfd2 100644
--- a/pytorch3d/renderer/utils.py
+++ b/pytorch3d/renderer/utils.py
@@ -223,27 +223,32 @@ class TensorProperties(object):
             self with all properties reshaped. e.g. a property with shape (N, 3)
             is transformed to shape (B, 3).
         """
+        # Iterate through the attributes of the class which are tensors.
         for k in dir(self):
             v = getattr(self, k)
             if torch.is_tensor(v):
                 if v.shape[0] > 1:
                     # There are different values for each batch element
-                    # so gather these using the batch_idx
-                    idx_dims = batch_idx.shape
+                    # so gather these using the batch_idx.
+                    # First clone the input batch_idx tensor before
+                    # modifying it.
+                    _batch_idx = batch_idx.clone()
+                    idx_dims = _batch_idx.shape
                     tensor_dims = v.shape
                     if len(idx_dims) > len(tensor_dims):
                         msg = "batch_idx cannot have more dimensions than %s. "
                         msg += "got shape %r and %s has shape %r"
                         raise ValueError(msg % (k, idx_dims, k, tensor_dims))
                     if idx_dims != tensor_dims:
-                        # To use torch.gather the index tensor (batch_idx) has
+                        # To use torch.gather the index tensor (_batch_idx) has
                         # to have the same shape as the input tensor.
                         new_dims = len(tensor_dims) - len(idx_dims)
                         new_shape = idx_dims + (1,) * new_dims
                         expand_dims = (-1,) + tensor_dims[1:]
-                        batch_idx = batch_idx.view(*new_shape)
-                        batch_idx = batch_idx.expand(*expand_dims)
-                    v = v.gather(0, batch_idx)
+                        _batch_idx = _batch_idx.view(*new_shape)
+                        _batch_idx = _batch_idx.expand(*expand_dims)
+
+                    v = v.gather(0, _batch_idx)
                     setattr(self, k, v)
         return self
 
diff --git a/pytorch3d/structures/meshes.py b/pytorch3d/structures/meshes.py
index 82741e5a..0060deb4 100644
--- a/pytorch3d/structures/meshes.py
+++ b/pytorch3d/structures/meshes.py
@@ -324,14 +324,14 @@ class Meshes(object):
             )
             if self._N > 0:
                 self.device = self._verts_list[0].device
-                num_verts_per_mesh = torch.tensor(
+                self._num_verts_per_mesh = torch.tensor(
                     [len(v) for v in self._verts_list], device=self.device
                 )
-                self._V = num_verts_per_mesh.max()
-                num_faces_per_mesh = torch.tensor(
+                self._V = self._num_verts_per_mesh.max()
+                self._num_faces_per_mesh = torch.tensor(
                     [len(f) for f in self._faces_list], device=self.device
                 )
-                self._F = num_faces_per_mesh.max()
+                self._F = self._num_faces_per_mesh.max()
                 self.valid = torch.tensor(
                     [
                         len(v) > 0 and len(f) > 0
@@ -341,8 +341,8 @@ class Meshes(object):
                     device=self.device,
                 )
 
-                if (len(num_verts_per_mesh.unique()) == 1) and (
-                    len(num_faces_per_mesh.unique()) == 1
+                if (len(self._num_verts_per_mesh.unique()) == 1) and (
+                    len(self._num_faces_per_mesh.unique()) == 1
                 ):
                     self.equisized = True
 
@@ -355,6 +355,7 @@ class Meshes(object):
             self._faces_padded = faces.to(torch.int64)
             self._N = self._verts_padded.shape[0]
             self._V = self._verts_padded.shape[1]
+
             self.device = self._verts_padded.device
             self.valid = torch.zeros(
                 (self._N,), dtype=torch.bool, device=self.device
@@ -363,18 +364,25 @@ class Meshes(object):
                 # Check that padded faces - which have value -1 - are at the
                 # end of the tensors
                 faces_not_padded = self._faces_padded.gt(-1).all(2)
-                num_faces = faces_not_padded.sum(1)
+                self._num_faces_per_mesh = faces_not_padded.sum(1)
                 if (faces_not_padded[:, :-1] < faces_not_padded[:, 1:]).any():
                     raise ValueError("Padding of faces must be at the end")
 
                 # NOTE that we don't check for the ordering of padded verts
                 # as long as the faces index correspond to the right vertices.
 
-                self.valid = num_faces > 0
-                self._F = num_faces.max()
-                if len(num_faces.unique()) == 1:
+                self.valid = self._num_faces_per_mesh > 0
+                self._F = self._num_faces_per_mesh.max()
+                if len(self._num_faces_per_mesh.unique()) == 1:
                     self.equisized = True
 
+                self._num_verts_per_mesh = torch.full(
+                    size=(self._N,),
+                    fill_value=self._V,
+                    dtype=torch.int64,
+                    device=self.device,
+                )
+
         else:
             raise ValueError(
                 "Verts and Faces must be either a list or a tensor with \
@@ -382,6 +390,23 @@ class Meshes(object):
                        number of verts or faces respectively."
             )
 
+        if self.isempty():
+            self._num_verts_per_mesh = torch.zeros(
+                (0,), dtype=torch.int64, device=self.device
+            )
+            self._num_faces_per_mesh = torch.zeros(
+                (0,), dtype=torch.int64, device=self.device
+            )
+
+        # Set the num verts/faces on the textures if present.
+        if self.textures is not None:
+            self.textures._num_faces_per_mesh = (
+                self._num_faces_per_mesh.tolist()
+            )
+            self.textures._num_verts_per_mesh = (
+                self._num_verts_per_mesh.tolist()
+            )
+
     def __len__(self):
         return self._N
 
@@ -893,11 +918,9 @@ class Meshes(object):
                     self._verts_packed,
                     self._verts_packed_to_mesh_idx,
                     self._mesh_to_verts_packed_first_idx,
-                    self._num_verts_per_mesh,
                     self._faces_packed,
                     self._faces_packed_to_mesh_idx,
                     self._mesh_to_faces_packed_first_idx,
-                    self._num_faces_per_mesh,
                 ]
             )
         ):
@@ -920,7 +943,6 @@ class Meshes(object):
             self._num_verts_per_mesh = torch.zeros(
                 (0,), dtype=torch.int64, device=self.device
             )
-
             self._faces_packed = -torch.ones(
                 (0, 3), dtype=torch.int64, device=self.device
             )
@@ -1354,6 +1376,7 @@ class Meshes(object):
         tex = None
         if self.textures is not None:
             tex = self.textures.extend(N)
+
         return Meshes(verts=new_verts_list, faces=new_faces_list, textures=tex)
 
 
diff --git a/pytorch3d/structures/textures.py b/pytorch3d/structures/textures.py
index 3ed0a1bd..94102ce3 100644
--- a/pytorch3d/structures/textures.py
+++ b/pytorch3d/structures/textures.py
@@ -4,7 +4,7 @@ from typing import List, Optional, Union
 import torch
 import torchvision.transforms as T
 
-from .utils import list_to_packed, padded_to_list
+from .utils import padded_to_list, padded_to_packed
 
 
 """
@@ -92,14 +92,19 @@ class Textures(object):
             faces_uvs: (N, F, 3) tensor giving the index into verts_uvs for each
                 vertex in the face. Padding value is assumed to be -1.
             verts_uvs: (N, V, 2) tensor giving the uv coordinate per vertex.
-            verts_rgb: (N, V, 3) tensor giving the rgb color per vertex.
+            verts_rgb: (N, V, 3) tensor giving the rgb color per vertex. Padding
+                value is assumed to be -1.
+
+        Note: only the padded representation of the textures is stored
+        and the packed/list representations are computed on the fly and
+        not cached.
         """
         if faces_uvs is not None and faces_uvs.ndim != 3:
             msg = "Expected faces_uvs to be of shape (N, F, 3); got %r"
             raise ValueError(msg % repr(faces_uvs.shape))
         if verts_uvs is not None and verts_uvs.ndim != 3:
             msg = "Expected verts_uvs to be of shape (N, V, 2); got %r"
-            raise ValueError(msg % repr(faces_uvs.shape))
+            raise ValueError(msg % repr(verts_uvs.shape))
         if verts_rgb is not None and verts_rgb.ndim != 3:
             msg = "Expected verts_rgb to be of shape (N, V, 3); got %r"
             raise ValueError(msg % repr(verts_rgb.shape))
@@ -109,20 +114,20 @@ class Textures(object):
                 raise ValueError(msg % repr(maps.shape))
             elif isinstance(maps, list):
                 maps = _pad_texture_maps(maps)
+            if faces_uvs is None or verts_uvs is None:
+                msg = "To use maps, faces_uvs and verts_uvs are required"
+                raise ValueError(msg)
+
         self._faces_uvs_padded = faces_uvs
         self._verts_uvs_padded = verts_uvs
         self._verts_rgb_padded = verts_rgb
         self._maps_padded = maps
-        self._num_faces_per_mesh = None
-        self._set_num_faces_per_mesh()
 
-    def _set_num_faces_per_mesh(self) -> None:
-        """
-        Determines and sets the number of textured faces for each mesh.
-        """
-        if self._faces_uvs_padded is not None:
-            faces_uvs = self._faces_uvs_padded
-            self._num_faces_per_mesh = faces_uvs.gt(-1).all(-1).sum(-1).tolist()
+        # The number of faces/verts for each mesh is
+        # set inside the Meshes object when textures is
+        # passed into the Meshes constructor.
+        self._num_faces_per_mesh = None
+        self._num_verts_per_mesh = None
 
     def clone(self):
         other = Textures()
@@ -148,41 +153,67 @@ class Textures(object):
                     setattr(other, key, value[index][None])
                 else:
                     setattr(other, key, value[index])
-        other._set_num_faces_per_mesh()
         return other
 
     def faces_uvs_padded(self) -> torch.Tensor:
         return self._faces_uvs_padded
 
-    def faces_uvs_list(self) -> List[torch.Tensor]:
-        if self._faces_uvs_padded is not None:
-            return padded_to_list(
-                self._faces_uvs_padded, split_size=self._num_faces_per_mesh
-            )
+    def faces_uvs_list(self) -> Union[List[torch.Tensor], None]:
+        if self._faces_uvs_padded is None:
+            return None
+        return padded_to_list(
+            self._faces_uvs_padded, split_size=self._num_faces_per_mesh
+        )
 
-    def faces_uvs_packed(self) -> torch.Tensor:
-        return list_to_packed(self.faces_uvs_list())[0]
+    def faces_uvs_packed(self) -> Union[torch.Tensor, None]:
+        if self._faces_uvs_padded is None:
+            return None
+        return padded_to_packed(
+            self._faces_uvs_padded, split_size=self._num_faces_per_mesh
+        )
 
-    def verts_uvs_padded(self) -> torch.Tensor:
+    def verts_uvs_padded(self) -> Union[torch.Tensor, None]:
         return self._verts_uvs_padded
 
-    def verts_uvs_list(self) -> List[torch.Tensor]:
+    def verts_uvs_list(self) -> Union[List[torch.Tensor], None]:
+        if self._verts_uvs_padded is None:
+            return None
+        # Vertices shared between multiple faces
+        # may have a different uv coordinate for
+        # each face so the num_verts_uvs_per_mesh
+        # may be different from num_verts_per_mesh.
+        # Therefore don't use any split_size.
         return padded_to_list(self._verts_uvs_padded)
 
-    def verts_uvs_packed(self) -> torch.Tensor:
-        return list_to_packed(self.verts_uvs_list())[0]
+    def verts_uvs_packed(self) -> Union[torch.Tensor, None]:
+        if self._verts_uvs_padded is None:
+            return None
+        # Vertices shared between multiple faces
+        # may have a different uv coordinate for
+        # each face so the num_verts_uvs_per_mesh
+        # may be different from num_verts_per_mesh.
+        # Therefore don't use any split_size.
+        return padded_to_packed(self._verts_uvs_padded)
 
-    def verts_rgb_padded(self) -> torch.Tensor:
+    def verts_rgb_padded(self) -> Union[torch.Tensor, None]:
         return self._verts_rgb_padded
 
-    def verts_rgb_list(self) -> List[torch.Tensor]:
-        return padded_to_list(self._verts_rgb_padded)
+    def verts_rgb_list(self) -> Union[List[torch.Tensor], None]:
+        if self._verts_rgb_padded is None:
+            return None
+        return padded_to_list(
+            self._verts_rgb_padded, split_size=self._num_verts_per_mesh
+        )
 
-    def verts_rgb_packed(self) -> torch.Tensor:
-        return list_to_packed(self.verts_rgb_list())[0]
+    def verts_rgb_packed(self) -> Union[torch.Tensor, None]:
+        if self._verts_rgb_padded is None:
+            return None
+        return padded_to_packed(
+            self._verts_rgb_padded, split_size=self._num_verts_per_mesh
+        )
 
     # Currently only the padded maps are used.
-    def maps_padded(self) -> torch.Tensor:
+    def maps_padded(self) -> Union[torch.Tensor, None]:
         return self._maps_padded
 
     def extend(self, N: int) -> "Textures":
diff --git a/tests/data/test_simple_sphere_light.png b/tests/data/test_simple_sphere_light_phong.png
similarity index 100%
rename from tests/data/test_simple_sphere_light.png
rename to tests/data/test_simple_sphere_light_phong.png
diff --git a/tests/data/test_simple_sphere_light_elevated_camera.png b/tests/data/test_simple_sphere_light_phong_elevated_camera.png
similarity index 100%
rename from tests/data/test_simple_sphere_light_elevated_camera.png
rename to tests/data/test_simple_sphere_light_phong_elevated_camera.png
diff --git a/tests/test_meshes.py b/tests/test_meshes.py
index 57141e83..4d1b9338 100644
--- a/tests/test_meshes.py
+++ b/tests/test_meshes.py
@@ -135,6 +135,15 @@ class TestMeshes(TestCaseMixin, unittest.TestCase):
     def test_simple(self):
         mesh = TestMeshes.init_simple_mesh("cuda:0")
 
+        # Check that faces/verts per mesh are set in init:
+        self.assertClose(
+            mesh._num_faces_per_mesh.cpu(), torch.tensor([1, 2, 7])
+        )
+        self.assertClose(
+            mesh._num_verts_per_mesh.cpu(), torch.tensor([3, 4, 5])
+        )
+
+        # Check computed tensors
         self.assertClose(
             mesh.verts_packed_to_mesh_idx().cpu(),
             torch.tensor([0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 2]),
@@ -142,9 +151,6 @@ class TestMeshes(TestCaseMixin, unittest.TestCase):
         self.assertClose(
             mesh.mesh_to_verts_packed_first_idx().cpu(), torch.tensor([0, 3, 7])
         )
-        self.assertClose(
-            mesh.num_verts_per_mesh().cpu(), torch.tensor([3, 4, 5])
-        )
         self.assertClose(
             mesh.verts_padded_to_packed_idx().cpu(),
             torch.tensor([0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 14]),
@@ -156,9 +162,6 @@ class TestMeshes(TestCaseMixin, unittest.TestCase):
         self.assertClose(
             mesh.mesh_to_faces_packed_first_idx().cpu(), torch.tensor([0, 1, 3])
         )
-        self.assertClose(
-            mesh.num_faces_per_mesh().cpu(), torch.tensor([1, 2, 7])
-        )
         self.assertClose(
             mesh.num_edges_per_mesh().cpu(),
             torch.tensor([3, 5, 10], dtype=torch.int32),
@@ -249,6 +252,8 @@ class TestMeshes(TestCaseMixin, unittest.TestCase):
         self.assertEqual(mesh.faces_padded().shape[0], 0)
         self.assertEqual(mesh.verts_packed().shape[0], 0)
         self.assertEqual(mesh.faces_packed().shape[0], 0)
+        self.assertEqual(mesh.num_faces_per_mesh().shape[0], 0)
+        self.assertEqual(mesh.num_verts_per_mesh().shape[0], 0)
 
     def test_empty(self):
         N, V, F = 10, 100, 300
@@ -323,9 +328,11 @@ class TestMeshes(TestCaseMixin, unittest.TestCase):
 
         mesh = Meshes(verts=torch.stack(verts), faces=torch.stack(faces))
 
+        # Check verts/faces per mesh are set correctly in init.
         self.assertListEqual(
-            mesh.num_faces_per_mesh().tolist(), num_faces.tolist()
+            mesh._num_faces_per_mesh.tolist(), num_faces.tolist()
         )
+        self.assertListEqual(mesh._num_verts_per_mesh.tolist(), [V] * N)
 
         for n, (vv, ff) in enumerate(zip(mesh.verts_list(), mesh.faces_list())):
             self.assertClose(ff, faces[n][: num_faces[n]])
@@ -364,7 +371,6 @@ class TestMeshes(TestCaseMixin, unittest.TestCase):
             mesh._num_verts_per_mesh = torch.randint_like(
                 mesh.num_verts_per_mesh(), high=10
             )
-
             # Check cloned and original Meshes objects do not share tensors.
             self.assertFalse(
                 torch.allclose(new_mesh._verts_list[0], mesh._verts_list[0])
diff --git a/tests/test_rendering_meshes.py b/tests/test_rendering_meshes.py
index 0e5edf5b..853fc17e 100644
--- a/tests/test_rendering_meshes.py
+++ b/tests/test_rendering_meshes.py
@@ -34,7 +34,7 @@ from pytorch3d.renderer.mesh.texturing import Textures
 from pytorch3d.structures.meshes import Meshes
 from pytorch3d.utils.ico_sphere import ico_sphere
 
-# Save out images generated in the tests for debugging
+# If DEBUG=True, save out images generated in the tests for debugging.
 # All saved images have prefix DEBUG_
 DEBUG = False
 DATA_DIR = Path(__file__).resolve().parent / "data"
@@ -90,30 +90,31 @@ class TestRenderingMeshes(unittest.TestCase):
         raster_settings = RasterizationSettings(
             image_size=512, blur_radius=0.0, faces_per_pixel=1, bin_size=0
         )
-
-        # Init renderer
         rasterizer = MeshRasterizer(
             cameras=cameras, raster_settings=raster_settings
         )
-        renderer = MeshRenderer(
-            rasterizer=rasterizer,
-            shader=HardPhongShader(
-                lights=lights, cameras=cameras, materials=materials
-            ),
-        )
-        images = renderer(sphere_mesh)
-        rgb = images[0, ..., :3].squeeze().cpu()
-        if DEBUG:
-            filename = "DEBUG_simple_sphere_light%s.png" % postfix
-            Image.fromarray((rgb.numpy() * 255).astype(np.uint8)).save(
-                DATA_DIR / filename
-            )
 
-        # Load reference image
-        image_ref_phong = load_rgb_image(
-            "test_simple_sphere_light%s.png" % postfix
-        )
-        self.assertTrue(torch.allclose(rgb, image_ref_phong, atol=0.05))
+        # Test several shaders
+        shaders = {
+            "phong": HardPhongShader,
+            "gouraud": HardGouraudShader,
+            "flat": HardFlatShader,
+        }
+        for (name, shader_init) in shaders.items():
+            shader = shader_init(
+                lights=lights, cameras=cameras, materials=materials
+            )
+            renderer = MeshRenderer(rasterizer=rasterizer, shader=shader)
+            images = renderer(sphere_mesh)
+            filename = "simple_sphere_light_%s%s.png" % (name, postfix)
+            image_ref = load_rgb_image("test_%s" % filename)
+            rgb = images[0, ..., :3].squeeze().cpu()
+            if DEBUG:
+                filename = "DEBUG_" % filename
+                Image.fromarray((rgb.numpy() * 255).astype(np.uint8)).save(
+                    DATA_DIR / filename
+                )
+            self.assertTrue(torch.allclose(rgb, image_ref, atol=0.05))
 
         ########################################################
         # Move the light to the +z axis in world space so it is
@@ -121,7 +122,13 @@ class TestRenderingMeshes(unittest.TestCase):
         # +X left for both world and camera space.
         ########################################################
         lights.location[..., 2] = -2.0
-        images = renderer(sphere_mesh, lights=lights)
+        phong_shader = HardPhongShader(
+            lights=lights, cameras=cameras, materials=materials
+        )
+        phong_renderer = MeshRenderer(
+            rasterizer=rasterizer, shader=phong_shader
+        )
+        images = phong_renderer(sphere_mesh, lights=lights)
         rgb = images[0, ..., :3].squeeze().cpu()
         if DEBUG:
             filename = "DEBUG_simple_sphere_dark%s.png" % postfix
@@ -135,53 +142,6 @@ class TestRenderingMeshes(unittest.TestCase):
         )
         self.assertTrue(torch.allclose(rgb, image_ref_phong_dark, atol=0.05))
 
-        ######################################
-        # Change the shader to a GouraudShader
-        ######################################
-        lights.location = torch.tensor([0.0, 0.0, +2.0], device=device)[None]
-        renderer = MeshRenderer(
-            rasterizer=rasterizer,
-            shader=HardGouraudShader(
-                lights=lights, cameras=cameras, materials=materials
-            ),
-        )
-        images = renderer(sphere_mesh)
-        rgb = images[0, ..., :3].squeeze().cpu()
-        if DEBUG:
-            filename = "DEBUG_simple_sphere_light_gouraud%s.png" % postfix
-            Image.fromarray((rgb.numpy() * 255).astype(np.uint8)).save(
-                DATA_DIR / filename
-            )
-
-        # Load reference image
-        image_ref_gouraud = load_rgb_image(
-            "test_simple_sphere_light_gouraud%s.png" % postfix
-        )
-        self.assertTrue(torch.allclose(rgb, image_ref_gouraud, atol=0.005))
-
-        ######################################
-        # Change the shader to a HardFlatShader
-        ######################################
-        renderer = MeshRenderer(
-            rasterizer=rasterizer,
-            shader=HardFlatShader(
-                lights=lights, cameras=cameras, materials=materials
-            ),
-        )
-        images = renderer(sphere_mesh)
-        rgb = images[0, ..., :3].squeeze().cpu()
-        if DEBUG:
-            filename = "DEBUG_simple_sphere_light_flat%s.png" % postfix
-            Image.fromarray((rgb.numpy() * 255).astype(np.uint8)).save(
-                DATA_DIR / filename
-            )
-
-        # Load reference image
-        image_ref_flat = load_rgb_image(
-            "test_simple_sphere_light_flat%s.png" % postfix
-        )
-        self.assertTrue(torch.allclose(rgb, image_ref_flat, atol=0.005))
-
     def test_simple_sphere_elevated_camera(self):
         """
         Test output of phong and gouraud shading matches a reference image using
@@ -193,13 +153,13 @@ class TestRenderingMeshes(unittest.TestCase):
 
     def test_simple_sphere_batched(self):
         """
-        Test output of phong shading matches a reference image using
-        the default values for the light sources.
+        Test a mesh with vertex textures can be extended to form a batch, and
+        is rendered correctly with Phong, Gouraud and Flat Shaders.
         """
-        batch_size = 5
+        batch_size = 20
         device = torch.device("cuda:0")
 
-        # Init mesh
+        # Init mesh with vertex textures.
         sphere_meshes = ico_sphere(5, device).extend(batch_size)
         verts_padded = sphere_meshes.verts_padded()
         faces_padded = sphere_meshes.faces_padded()
@@ -224,26 +184,24 @@ class TestRenderingMeshes(unittest.TestCase):
         lights.location = torch.tensor([0.0, 0.0, +2.0], device=device)[None]
 
         # Init renderer
-        renderer = MeshRenderer(
-            rasterizer=MeshRasterizer(
-                cameras=cameras, raster_settings=raster_settings
-            ),
-            shader=HardPhongShader(
-                lights=lights, cameras=cameras, materials=materials
-            ),
+        rasterizer = MeshRasterizer(
+            cameras=cameras, raster_settings=raster_settings
         )
-        images = renderer(sphere_meshes)
-
-        # Load ref image
-        image_ref = load_rgb_image("test_simple_sphere_light.png")
-
-        for i in range(batch_size):
-            rgb = images[i, ..., :3].squeeze().cpu()
-            if DEBUG:
-                Image.fromarray((rgb.numpy() * 255).astype(np.uint8)).save(
-                    DATA_DIR / f"DEBUG_simple_sphere_{i}.png"
-                )
-            self.assertTrue(torch.allclose(rgb, image_ref, atol=0.05))
+        shaders = {
+            "phong": HardGouraudShader,
+            "gouraud": HardGouraudShader,
+            "flat": HardFlatShader,
+        }
+        for (name, shader_init) in shaders.items():
+            shader = shader_init(
+                lights=lights, cameras=cameras, materials=materials
+            )
+            renderer = MeshRenderer(rasterizer=rasterizer, shader=shader)
+            images = renderer(sphere_meshes)
+            image_ref = load_rgb_image("test_simple_sphere_light_%s.png" % name)
+            for i in range(batch_size):
+                rgb = images[i, ..., :3].squeeze().cpu()
+                self.assertTrue(torch.allclose(rgb, image_ref, atol=0.05))
 
     def test_silhouette_with_grad(self):
         """
diff --git a/tests/test_rendering_utils.py b/tests/test_rendering_utils.py
index 9f088d34..917d173d 100644
--- a/tests/test_rendering_utils.py
+++ b/tests/test_rendering_utils.py
@@ -1,6 +1,7 @@
 # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
 
 
+import numpy as np
 import unittest
 import torch
 
@@ -61,3 +62,28 @@ class TestTensorProperties(TestCaseMixin, unittest.TestCase):
         example = TensorPropertiesTestClass(x=(), y=())
         self.assertTrue(len(example) == 0)
         self.assertTrue(example.isempty())
+
+    def test_gather_props(self):
+        N = 4
+        x = torch.randn((N, 3, 4))
+        y = torch.randn((N, 5))
+        test_class = TensorPropertiesTestClass(x=x, y=y)
+
+        S = 15
+        idx = torch.tensor(np.random.choice(N, S))
+        test_class_gathered = test_class.gather_props(idx)
+
+        self.assertTrue(test_class_gathered.x.shape == (S, 3, 4))
+        self.assertTrue(test_class_gathered.y.shape == (S, 5))
+
+        for i in range(N):
+            inds = idx == i
+            if inds.sum() > 0:
+                # Check the gathered points in the output have the same value from
+                # the input.
+                self.assertClose(
+                    test_class_gathered.x[inds].mean(dim=0), x[i, ...]
+                )
+                self.assertClose(
+                    test_class_gathered.y[inds].mean(dim=0), y[i, ...]
+                )
diff --git a/tests/test_texturing.py b/tests/test_texturing.py
index f1cdc6d9..5e235c01 100644
--- a/tests/test_texturing.py
+++ b/tests/test_texturing.py
@@ -12,6 +12,7 @@ from pytorch3d.renderer.mesh.texturing import (
     interpolate_vertex_colors,
 )
 from pytorch3d.structures import Meshes, Textures
+from pytorch3d.structures.utils import list_to_padded
 
 from common_testing import TestCaseMixin
 from test_meshes import TestMeshes
@@ -154,6 +155,108 @@ class TestTexturing(TestCaseMixin, unittest.TestCase):
             torch.allclose(texels.squeeze(), expected_out.squeeze())
         )
 
+    def test_init_rgb_uv_fail(self):
+        V = 20
+        # Maps has wrong shape
+        with self.assertRaisesRegex(ValueError, "maps"):
+            Textures(
+                maps=torch.ones((5, 16, 16, 3, 4)),
+                faces_uvs=torch.randint(size=(5, 10, 3), low=0, high=V),
+                verts_uvs=torch.ones((5, V, 2)),
+            )
+        # faces_uvs has wrong shape
+        with self.assertRaisesRegex(ValueError, "faces_uvs"):
+            Textures(
+                maps=torch.ones((5, 16, 16, 3)),
+                faces_uvs=torch.randint(size=(5, 10, 3, 3), low=0, high=V),
+                verts_uvs=torch.ones((5, V, 2)),
+            )
+        # verts_uvs has wrong shape
+        with self.assertRaisesRegex(ValueError, "verts_uvs"):
+            Textures(
+                maps=torch.ones((5, 16, 16, 3)),
+                faces_uvs=torch.randint(size=(5, 10, 3), low=0, high=V),
+                verts_uvs=torch.ones((5, V, 2, 3)),
+            )
+        # verts_rgb has wrong shape
+        with self.assertRaisesRegex(ValueError, "verts_rgb"):
+            Textures(verts_rgb=torch.ones((5, 16, 16, 3)))
+
+        # maps provided without verts/faces uvs
+        with self.assertRaisesRegex(
+            ValueError, "faces_uvs and verts_uvs are required"
+        ):
+            Textures(maps=torch.ones((5, 16, 16, 3)))
+
+    def test_padded_to_packed(self):
+        N = 2
+        # Case where each face in the mesh has 3 unique uv vertex indices
+        # - i.e. even if a vertex is shared between multiple faces it will
+        # have a unique uv coordinate for each face.
+        faces_uvs_list = [
+            torch.tensor([[0, 1, 2], [3, 5, 4], [7, 6, 8]]),
+            torch.tensor([[0, 1, 2], [3, 4, 5]]),
+        ]  # (N, 3, 3)
+        verts_uvs_list = [torch.ones(9, 2), torch.ones(6, 2)]
+        faces_uvs_padded = list_to_padded(faces_uvs_list, pad_value=-1)
+        verts_uvs_padded = list_to_padded(verts_uvs_list)
+        tex = Textures(
+            maps=torch.ones((N, 16, 16, 3)),
+            faces_uvs=faces_uvs_padded,
+            verts_uvs=verts_uvs_padded,
+        )
+
+        # This is set inside Meshes when textures is passed as an input.
+        # Here we set _num_faces_per_mesh and _num_verts_per_mesh explicity.
+        tex1 = tex.clone()
+        tex1._num_faces_per_mesh = (
+            faces_uvs_padded.gt(-1).all(-1).sum(-1).tolist()
+        )
+        tex1._num_verts_per_mesh = torch.tensor([5, 4])
+        faces_packed = tex1.faces_uvs_packed()
+        verts_packed = tex1.verts_uvs_packed()
+        faces_list = tex1.faces_uvs_list()
+        verts_list = tex1.verts_uvs_list()
+
+        for f1, f2 in zip(faces_uvs_list, faces_list):
+            self.assertTrue((f1 == f2).all().item())
+
+        for f, v1, v2 in zip(faces_list, verts_list, verts_uvs_list):
+            idx = f.unique()
+            self.assertTrue((v1[idx] == v2).all().item())
+
+        self.assertTrue(faces_packed.shape == (3 + 2, 3))
+
+        # verts_packed is just flattened verts_padded.
+        # split sizes are not used for verts_uvs.
+        self.assertTrue(verts_packed.shape == (9 * 2, 2))
+
+        # Case where num_faces_per_mesh is not set
+        tex2 = tex.clone()
+        faces_packed = tex2.faces_uvs_packed()
+        verts_packed = tex2.verts_uvs_packed()
+        faces_list = tex2.faces_uvs_list()
+        verts_list = tex2.verts_uvs_list()
+
+        # Packed is just flattened padded as num_faces_per_mesh
+        # has not been provided.
+        self.assertTrue(verts_packed.shape == (9 * 2, 2))
+        self.assertTrue(faces_packed.shape == (3 * 2, 3))
+
+        for i in range(N):
+            self.assertTrue(
+                (faces_list[i] == faces_uvs_padded[i, ...].squeeze())
+                .all()
+                .item()
+            )
+
+        for i in range(N):
+            self.assertTrue(
+                (verts_list[i] == verts_uvs_padded[i, ...].squeeze())
+                .all()
+                .item()
+            )
+
     def test_clone(self):
         V = 20
         tex = Textures(
@@ -233,13 +336,17 @@ class TestTexturing(TestCaseMixin, unittest.TestCase):
         mesh = TestMeshes.init_mesh(B, 30, 50)
         V = mesh._V
         F = mesh._F
-        tex = Textures(
+
+        # 1. Texture uvs
+        tex_uv = Textures(
             maps=torch.randn((B, 16, 16, 3)),
             faces_uvs=torch.randint(size=(B, F, 3), low=0, high=V),
             verts_uvs=torch.randn((B, V, 2)),
         )
         tex_mesh = Meshes(
-            verts=mesh.verts_padded(), faces=mesh.faces_padded(), textures=tex
+            verts=mesh.verts_padded(),
+            faces=mesh.faces_padded(),
+            textures=tex_uv,
         )
         N = 20
         new_mesh = tex_mesh.extend(N)
@@ -269,5 +376,43 @@ class TestTexturing(TestCaseMixin, unittest.TestCase):
                 new_tex.maps_padded(),
             ]
         )
+
+        self.assertIsNone(new_tex.verts_rgb_list())
+        self.assertIsNone(new_tex.verts_rgb_padded())
+        self.assertIsNone(new_tex.verts_rgb_packed())
+
+        # 2. Texture vertex RGB
+        tex_rgb = Textures(verts_rgb=torch.randn((B, V, 3)))
+        tex_mesh_rgb = Meshes(
+            verts=mesh.verts_padded(),
+            faces=mesh.faces_padded(),
+            textures=tex_rgb,
+        )
+        N = 20
+        new_mesh_rgb = tex_mesh_rgb.extend(N)
+
+        self.assertEqual(len(tex_mesh_rgb) * N, len(new_mesh_rgb))
+
+        tex_init = tex_mesh_rgb.textures
+        new_tex = new_mesh_rgb.textures
+
+        for i in range(len(tex_mesh_rgb)):
+            for n in range(N):
+                self.assertClose(
+                    tex_init.verts_rgb_list()[i],
+                    new_tex.verts_rgb_list()[i * N + n],
+                )
+        self.assertAllSeparate(
+            [tex_init.verts_rgb_padded(), new_tex.verts_rgb_padded()]
+        )
+
+        self.assertIsNone(new_tex.verts_uvs_padded())
+        self.assertIsNone(new_tex.verts_uvs_list())
+        self.assertIsNone(new_tex.verts_uvs_packed())
+        self.assertIsNone(new_tex.faces_uvs_padded())
+        self.assertIsNone(new_tex.faces_uvs_list())
+        self.assertIsNone(new_tex.faces_uvs_packed())
+
+        # 3. Error
         with self.assertRaises(ValueError):
             tex_mesh.extend(N=-1)