Annotate dunder functions

Summary: Annotate the (return type of the) following dunder functions across the codebase: `__init__()`, `__len__()`, `__getitem__()`

Reviewed By: nikhilaravi

Differential Revision: D29001801

fbshipit-source-id: 928d9e1c417ffe01ab8c0445311287786e997c7c

projects/nerf/nerf/dataset.py

@@ -36,7 +36,7 @@ class ListDataset(Dataset):
     A simple dataset made of a list of entries.
     """
 
-    def __init__(self, entries: List):
+    def __init__(self, entries: List) -> None:
         """
         Args:
             entries: The list of dataset entries.
@@ -45,7 +45,7 @@ class ListDataset(Dataset):
 
     def __len__(
         self,
-    ):
+    ) -> int:
         return len(self._entries)
 
     def __getitem__(self, index):

projects/nerf/nerf/stats.py

@@ -22,7 +22,7 @@ class AverageMeter:
     Tracks the exact history of the added values in every epoch.
     """
 
-    def __init__(self):
+    def __init__(self) -> None:
         """
         Initialize the structure with empty history and zero-ed moving average.
         """
@@ -110,7 +110,7 @@ class Stats:
         verbose: bool = False,
         epoch: int = -1,
         plot_file: Optional[str] = None,
-    ):
+    ) -> None:
         """
         Args:
             log_vars: The list of variable names to be logged.

pytorch3d/datasets/r2n2/r2n2.py

@@ -64,7 +64,7 @@ class R2N2(ShapeNetBase):  # pragma: no cover
         voxels_rel_path: str = "ShapeNetVoxels",
         load_textures: bool = True,
         texture_resolution: int = 4,
-    ):
+    ) -> None:
         """
         Store each object's synset id and models id the given directories.
 

pytorch3d/datasets/r2n2/utils.py

@@ -437,7 +437,7 @@ class BlenderCamera(CamerasBase):  # pragma: no cover
     (which uses Blender for rendering the views for each model).
     """
 
-    def __init__(self, R=r, T=t, K=k, device: Device = "cpu"):
+    def __init__(self, R=r, T=t, K=k, device: Device = "cpu") -> None:
         """
         Args:
             R: Rotation matrix of shape (N, 3, 3).

pytorch3d/datasets/shapenet/shapenet_core.py

@@ -31,7 +31,7 @@ class ShapeNetCore(ShapeNetBase):  # pragma: no cover
         version: int = 1,
         load_textures: bool = True,
         texture_resolution: int = 4,
-    ):
+    ) -> None:
         """
         Store each object's synset id and models id from data_dir.
 

pytorch3d/datasets/shapenet_base.py

@@ -30,7 +30,7 @@ class ShapeNetBase(torch.utils.data.Dataset):  # pragma: no cover
     and __getitem__ need to be implemented.
     """
 
-    def __init__(self):
+    def __init__(self) -> None:
         """
         Set up lists of synset_ids and model_ids.
         """
@@ -44,7 +44,7 @@ class ShapeNetBase(torch.utils.data.Dataset):  # pragma: no cover
         self.load_textures = True
         self.texture_resolution = 4
 
-    def __len__(self):
+    def __len__(self) -> int:
         """
         Return number of total models in the loaded dataset.
         """

pytorch3d/io/experimental_gltf_io.py

@@ -187,7 +187,7 @@ def _make_node_transform(node: Dict[str, Any]) -> Transform3d:
 
 
 class _GLTFLoader:
-    def __init__(self, stream: BinaryIO):
+    def __init__(self, stream: BinaryIO) -> None:
         self._json_data = None
         # Map from buffer index to (decoded) binary data
         self._binary_data = {}
@@ -539,7 +539,7 @@ class MeshGlbFormat(MeshFormatInterpreter):
         used which does not match the semantics of the standard.
     """
 
-    def __init__(self):
+    def __init__(self) -> None:
         self.known_suffixes = (".glb",)
 
     def read(

pytorch3d/io/obj_io.py

@@ -291,7 +291,7 @@ def load_objs_as_meshes(
 
 
 class MeshObjFormat(MeshFormatInterpreter):
-    def __init__(self):
+    def __init__(self) -> None:
         self.known_suffixes = (".obj",)
 
     def read(

pytorch3d/io/off_io.py

@@ -419,7 +419,7 @@ class MeshOffFormat(MeshFormatInterpreter):
 
     """
 
-    def __init__(self):
+    def __init__(self) -> None:
         self.known_suffixes = (".off",)
 
     def read(

pytorch3d/io/pluggable.py

@@ -63,7 +63,7 @@ class IO:
         self,
         include_default_formats: bool = True,
         path_manager: Optional[PathManager] = None,
-    ):
+    ) -> None:
         if path_manager is None:
             self.path_manager = PathManager()
         else:

pytorch3d/io/ply_io.py

@@ -66,7 +66,7 @@ class _PlyElementType:
         self.name:       (str) name of the element
     """
 
-    def __init__(self, name: str, count: int):
+    def __init__(self, name: str, count: int) -> None:
         self.name = name
         self.count = count
         self.properties: List[_Property] = []
@@ -130,7 +130,7 @@ class _PlyElementType:
 
 
 class _PlyHeader:
-    def __init__(self, f):
+    def __init__(self, f) -> None:
         """
         Load a header of a Ply file from a file-like object.
         Members:
@@ -1232,7 +1232,7 @@ def save_ply(
 
 
 class MeshPlyFormat(MeshFormatInterpreter):
-    def __init__(self):
+    def __init__(self) -> None:
         self.known_suffixes = (".ply",)
 
     def read(
@@ -1313,7 +1313,7 @@ class MeshPlyFormat(MeshFormatInterpreter):
 
 
 class PointcloudPlyFormat(PointcloudFormatInterpreter):
-    def __init__(self):
+    def __init__(self) -> None:
         self.known_suffixes = (".ply",)
 
     def read(

pytorch3d/ops/graph_conv.py

@@ -21,7 +21,7 @@ class GraphConv(nn.Module):
         output_dim: int,
         init: str = "normal",
         directed: bool = False,
-    ):
+    ) -> None:
         """
         Args:
             input_dim: Number of input features per vertex.

pytorch3d/ops/marching_cubes.py

@@ -15,7 +15,7 @@ EPS = 0.00001
 
 
 class Cube:
-    def __init__(self, bfl_vertex: Tuple[int, int, int], spacing: int = 1):
+    def __init__(self, bfl_vertex: Tuple[int, int, int], spacing: int = 1) -> None:
         """
         Initializes a cube given the bottom front left vertex coordinate
         and the cube spacing

pytorch3d/ops/subdivide_meshes.py

@@ -26,7 +26,7 @@ class SubdivideMeshes(nn.Module):
     but different vertex positions.
     """
 
-    def __init__(self, meshes=None):
+    def __init__(self, meshes=None) -> None:
         """
         Args:
             meshes: Meshes object or None. If a meshes object is provided,

pytorch3d/renderer/cameras.py

@@ -364,7 +364,7 @@ class FoVPerspectiveCameras(CamerasBase):
         T=_T,
         K=None,
         device: Device = "cpu",
-    ):
+    ) -> None:
         """
 
         Args:
@@ -848,7 +848,7 @@ class PerspectiveCameras(CamerasBase):
         K=None,
         device="cpu",
         image_size=((-1, -1),),
-    ):
+    ) -> None:
         """
 
         Args:
@@ -1013,7 +1013,7 @@ class OrthographicCameras(CamerasBase):
         K=None,
         device="cpu",
         image_size=((-1, -1),),
-    ):
+    ) -> None:
         """
 
         Args:

pytorch3d/renderer/implicit/raymarching.py

@@ -49,7 +49,7 @@ class EmissionAbsorptionRaymarcher(torch.nn.Module):
     elements along the ray direction.
     """
 
-    def __init__(self, surface_thickness: int = 1):
+    def __init__(self, surface_thickness: int = 1) -> None:
         """
         Args:
             surface_thickness: Denotes the overlap between the absorption
@@ -128,7 +128,7 @@ class AbsorptionOnlyRaymarcher(torch.nn.Module):
     It then returns `opacities = 1 - total_transmission`.
     """
 
-    def __init__(self):
+    def __init__(self) -> None:
         super().__init__()
 
     def forward(

pytorch3d/renderer/implicit/raysampling.py

@@ -66,7 +66,7 @@ class GridRaysampler(torch.nn.Module):
         n_pts_per_ray: int,
         min_depth: float,
         max_depth: float,
-    ):
+    ) -> None:
         """
         Args:
             min_x: The leftmost x-coordinate of each ray's source pixel's center.
@@ -150,7 +150,7 @@ class NDCGridRaysampler(GridRaysampler):
         n_pts_per_ray: int,
         min_depth: float,
         max_depth: float,
-    ):
+    ) -> None:
         """
         Args:
             image_width: The horizontal size of the image grid.
@@ -192,7 +192,7 @@ class MonteCarloRaysampler(torch.nn.Module):
         n_pts_per_ray: int,
         min_depth: float,
         max_depth: float,
-    ):
+    ) -> None:
         """
         Args:
             min_x: The smallest x-coordinate of each ray's source pixel.

pytorch3d/renderer/implicit/renderer.py

@@ -105,7 +105,7 @@ class ImplicitRenderer(torch.nn.Module):
         ```
     """
 
-    def __init__(self, raysampler: Callable, raymarcher: Callable):
+    def __init__(self, raysampler: Callable, raymarcher: Callable) -> None:
         """
         Args:
             raysampler: A `Callable` that takes as input scene cameras
@@ -206,7 +206,7 @@ class VolumeRenderer(torch.nn.Module):
 
     def __init__(
         self, raysampler: Callable, raymarcher: Callable, sample_mode: str = "bilinear"
-    ):
+    ) -> None:
         """
         Args:
             raysampler: A `Callable` that takes as input scene cameras
@@ -256,7 +256,7 @@ class VolumeSampler(torch.nn.Module):
     at 3D points sampled along projection rays.
     """
 
-    def __init__(self, volumes: Volumes, sample_mode: str = "bilinear"):
+    def __init__(self, volumes: Volumes, sample_mode: str = "bilinear") -> None:
         """
         Args:
             volumes: An instance of the `Volumes` class representing a

pytorch3d/renderer/lighting.py

@@ -164,7 +164,7 @@ class DirectionalLights(TensorProperties):
         specular_color=((0.2, 0.2, 0.2),),
         direction=((0, 1, 0),),
         device: Device = "cpu",
-    ):
+    ) -> None:
         """
         Args:
             ambient_color: RGB color of the ambient component.
@@ -225,7 +225,7 @@ class PointLights(TensorProperties):
         specular_color=((0.2, 0.2, 0.2),),
         location=((0, 1, 0),),
         device: Device = "cpu",
-    ):
+    ) -> None:
         """
         Args:
             ambient_color: RGB color of the ambient component
@@ -294,7 +294,7 @@ class AmbientLights(TensorProperties):
     not used in rendering.
     """
 
-    def __init__(self, *, ambient_color=None, device: Device = "cpu"):
+    def __init__(self, *, ambient_color=None, device: Device = "cpu") -> None:
         """
         If ambient_color is provided, it should be a sequence of
         triples of floats.

pytorch3d/renderer/materials.py

@@ -24,7 +24,7 @@ class Materials(TensorProperties):
         specular_color=((1, 1, 1),),
         shininess=64,
         device: Device = "cpu",
-    ):
+    ) -> None:
         """
         Args:
             ambient_color: RGB ambient reflectivity of the material

pytorch3d/renderer/mesh/clip.py

@@ -84,7 +84,7 @@ class ClippedFaces:
         barycentric_conversion: Optional[torch.Tensor] = None,
         faces_clipped_to_conversion_idx: Optional[torch.Tensor] = None,
         clipped_faces_neighbor_idx: Optional[torch.Tensor] = None,
-    ):
+    ) -> None:
         self.face_verts = face_verts
         self.mesh_to_face_first_idx = mesh_to_face_first_idx
         self.num_faces_per_mesh = num_faces_per_mesh
@@ -139,7 +139,7 @@ class ClipFrustum:
         perspective_correct: bool = False,
         cull: bool = True,
         z_clip_value: Optional[float] = None,
-    ):
+    ) -> None:
         self.left = left
         self.right = right
         self.top = top

pytorch3d/renderer/mesh/rasterizer.py

@@ -49,7 +49,7 @@ class RasterizationSettings:
         cull_backfaces: bool = False,
         z_clip_value: Optional[float] = None,
         cull_to_frustum: bool = False,
-    ):
+    ) -> None:
         self.image_size = image_size
         self.blur_radius = blur_radius
         self.faces_per_pixel = faces_per_pixel
@@ -68,7 +68,7 @@ class MeshRasterizer(nn.Module):
     Meshes.
     """
 
-    def __init__(self, cameras=None, raster_settings=None):
+    def __init__(self, cameras=None, raster_settings=None) -> None:
         """
         Args:
             cameras: A cameras object which has a  `transform_points` method

pytorch3d/renderer/mesh/renderer.py

@@ -32,7 +32,7 @@ class MeshRenderer(nn.Module):
     function.
     """
 
-    def __init__(self, rasterizer, shader):
+    def __init__(self, rasterizer, shader) -> None:
         super().__init__()
         self.rasterizer = rasterizer
         self.shader = shader
@@ -76,7 +76,7 @@ class MeshRendererWithFragments(nn.Module):
         depth = fragments.zbuf
     """
 
-    def __init__(self, rasterizer, shader):
+    def __init__(self, rasterizer, shader) -> None:
         super().__init__()
         self.rasterizer = rasterizer
         self.shader = shader

pytorch3d/renderer/mesh/shader.py

@@ -51,7 +51,7 @@ class HardPhongShader(nn.Module):
         lights=None,
         materials=None,
         blend_params=None,
-    ):
+    ) -> None:
         super().__init__()
         self.lights = lights if lights is not None else PointLights(device=device)
         self.materials = (
@@ -112,7 +112,7 @@ class SoftPhongShader(nn.Module):
         lights=None,
         materials=None,
         blend_params=None,
-    ):
+    ) -> None:
         super().__init__()
         self.lights = lights if lights is not None else PointLights(device=device)
         self.materials = (
@@ -178,7 +178,7 @@ class HardGouraudShader(nn.Module):
         lights=None,
         materials=None,
         blend_params=None,
-    ):
+    ) -> None:
         super().__init__()
         self.lights = lights if lights is not None else PointLights(device=device)
         self.materials = (
@@ -243,7 +243,7 @@ class SoftGouraudShader(nn.Module):
         lights=None,
         materials=None,
         blend_params=None,
-    ):
+    ) -> None:
         super().__init__()
         self.lights = lights if lights is not None else PointLights(device=device)
         self.materials = (
@@ -325,7 +325,7 @@ class HardFlatShader(nn.Module):
         lights=None,
         materials=None,
         blend_params=None,
-    ):
+    ) -> None:
         super().__init__()
         self.lights = lights if lights is not None else PointLights(device=device)
         self.materials = (
@@ -381,7 +381,7 @@ class SoftSilhouetteShader(nn.Module):
         3D Reasoning', ICCV 2019
     """
 
-    def __init__(self, blend_params=None):
+    def __init__(self, blend_params=None) -> None:
         super().__init__()
         self.blend_params = blend_params if blend_params is not None else BlendParams()
 

pytorch3d/renderer/mesh/textures.py

@@ -262,7 +262,7 @@ class TexturesBase:
         """
         raise NotImplementedError()
 
-    def __getitem__(self, index):
+    def __getitem__(self, index) -> "TexturesBase":
         """
         Each texture class should implement a method
         to get the texture properties for the
@@ -321,7 +321,7 @@ def Textures(
 
 
 class TexturesAtlas(TexturesBase):
-    def __init__(self, atlas: Union[torch.Tensor, List[torch.Tensor]]):
+    def __init__(self, atlas: Union[torch.Tensor, List[torch.Tensor]]) -> None:
         """
         A texture representation where each face has a square texture map.
         This is based on the implementation from SoftRasterizer [1].
@@ -420,7 +420,7 @@ class TexturesAtlas(TexturesBase):
         tex._num_faces_per_mesh = num_faces
         return tex
 
-    def __getitem__(self, index):
+    def __getitem__(self, index) -> "TexturesAtlas":
         props = ["atlas_list", "_num_faces_per_mesh"]
         new_props = self._getitem(index, props=props)
         atlas = new_props["atlas_list"]
@@ -596,7 +596,7 @@ class TexturesUV(TexturesBase):
         verts_uvs: Union[torch.Tensor, List[torch.Tensor], Tuple[torch.Tensor]],
         padding_mode: str = "border",
         align_corners: bool = True,
-    ):
+    ) -> None:
         """
         Textures are represented as a per mesh texture map and uv coordinates for each
         vertex in each face. NOTE: this class only supports one texture map per mesh.
@@ -786,7 +786,7 @@ class TexturesUV(TexturesBase):
         tex.valid = self.valid.detach()
         return tex
 
-    def __getitem__(self, index):
+    def __getitem__(self, index) -> "TexturesUV":
         props = ["verts_uvs_list", "faces_uvs_list", "maps_list", "_num_faces_per_mesh"]
         new_props = self._getitem(index, props)
         faces_uvs = new_props["faces_uvs_list"]
@@ -1257,7 +1257,7 @@ class TexturesVertex(TexturesBase):
     def __init__(
         self,
         verts_features: Union[torch.Tensor, List[torch.Tensor], Tuple[torch.Tensor]],
-    ):
+    ) -> None:
         """
         Batched texture representation where each vertex in a mesh
         has a C dimensional feature vector.

pytorch3d/renderer/points/compositor.py

@@ -25,7 +25,7 @@ class AlphaCompositor(nn.Module):
 
     def __init__(
         self, background_color: Optional[Union[Tuple, List, torch.Tensor]] = None
-    ):
+    ) -> None:
         super().__init__()
         self.background_color = background_color
 
@@ -47,7 +47,7 @@ class NormWeightedCompositor(nn.Module):
 
     def __init__(
         self, background_color: Optional[Union[Tuple, List, torch.Tensor]] = None
-    ):
+    ) -> None:
         super().__init__()
         self.background_color = background_color
 

pytorch3d/renderer/points/pulsar/renderer.py

@@ -326,7 +326,7 @@ class Renderer(torch.nn.Module):
         background_normalized_depth: float = _C.EPS,
         n_channels: int = 3,
         n_track: int = 5,
-    ):
+    ) -> None:
         super(Renderer, self).__init__()
         # pyre-fixme[16]: Module `pytorch3d` has no attribute `_C`.
         self._renderer = _C.PulsarRenderer(

pytorch3d/renderer/points/pulsar/unified.py

@@ -51,7 +51,7 @@ class PulsarPointsRenderer(nn.Module):
         n_channels: int = 3,
         max_num_spheres: int = int(1e6),  # noqa: B008
         **kwargs,
-    ):
+    ) -> None:
         """
         rasterizer (PointsRasterizer): An object encapsulating rasterization parameters.
         compositor (ignored): Only keeping this for interface consistency. Default: None.

pytorch3d/renderer/points/rasterizer.py

@@ -38,7 +38,7 @@ class PointsRasterizationSettings:
         points_per_pixel: int = 8,
         bin_size: Optional[int] = None,
         max_points_per_bin: Optional[int] = None,
-    ):
+    ) -> None:
         self.image_size = image_size
         self.radius = radius
         self.points_per_pixel = points_per_pixel
@@ -51,7 +51,7 @@ class PointsRasterizer(nn.Module):
     This class implements methods for rasterizing a batch of pointclouds.
     """
 
-    def __init__(self, cameras=None, raster_settings=None):
+    def __init__(self, cameras=None, raster_settings=None) -> None:
         """
         cameras: A cameras object which has a  `transform_points` method
                 which returns the transformed points after applying the

pytorch3d/renderer/points/renderer.py

@@ -32,7 +32,7 @@ class PointsRenderer(nn.Module):
     function.
     """
 
-    def __init__(self, rasterizer, compositor):
+    def __init__(self, rasterizer, compositor) -> None:
         super().__init__()
         self.rasterizer = rasterizer
         self.compositor = compositor

pytorch3d/renderer/utils.py

@@ -25,7 +25,7 @@ class TensorAccessor(nn.Module):
     and one element in the batch needs to be modified.
     """
 
-    def __init__(self, class_object, index: Union[int, slice]):
+    def __init__(self, class_object, index: Union[int, slice]) -> None:
         """
         Args:
             class_object: this should be an instance of a class which has
@@ -96,7 +96,7 @@ class TensorProperties(nn.Module):
 
     def __init__(
         self, dtype: torch.dtype = torch.float32, device: Device = "cpu", **kwargs
-    ):
+    ) -> None:
         """
         Args:
             dtype: data type to set for the inputs
@@ -143,7 +143,7 @@ class TensorProperties(nn.Module):
     def isempty(self) -> bool:
         return self._N == 0
 
-    def __getitem__(self, index: Union[int, slice]):
+    def __getitem__(self, index: Union[int, slice]) -> TensorAccessor:
         """
 
         Args:

pytorch3d/structures/meshes.py

@@ -219,7 +219,7 @@ class Meshes:
         textures=None,
         *,
         verts_normals=None,
-    ):
+    ) -> None:
         """
         Args:
             verts:
@@ -469,10 +469,10 @@ class Meshes:
         else:
             raise ValueError("verts_normals must be a list or tensor")
 
-    def __len__(self):
+    def __len__(self) -> int:
         return self._N
 
-    def __getitem__(self, index):
+    def __getitem__(self, index) -> "Meshes":
         """
         Args:
             index: Specifying the index of the mesh to retrieve.
@@ -493,7 +493,7 @@ class Meshes:
             # NOTE consider converting index to cpu for efficiency
             if index.dtype == torch.bool:
                 # advanced indexing on a single dimension
-                index = index.nonzero()
+                index = index.nonzero()  # pyre-ignore
                 index = index.squeeze(1) if index.numel() > 0 else index
                 index = index.tolist()
             verts = [self.verts_list()[i] for i in index]

pytorch3d/structures/pointclouds.py

@@ -108,7 +108,7 @@ class Pointclouds:
         "equisized",
     ]
 
-    def __init__(self, points, normals=None, features=None):
+    def __init__(self, points, normals=None, features=None) -> None:
         """
         Args:
             points:
@@ -306,10 +306,10 @@ class Pointclouds:
                     points in a cloud."
             )
 
-    def __len__(self):
+    def __len__(self) -> int:
         return self._N
 
-    def __getitem__(self, index):
+    def __getitem__(self, index) -> "Pointclouds":
         """
         Args:
             index: Specifying the index of the cloud to retrieve.
@@ -343,7 +343,7 @@ class Pointclouds:
             # NOTE consider converting index to cpu for efficiency
             if index.dtype == torch.bool:
                 # advanced indexing on a single dimension
-                index = index.nonzero()
+                index = index.nonzero()  # pyre-ignore
                 index = index.squeeze(1) if index.numel() > 0 else index
                 index = index.tolist()
             points = [self.points_list()[i] for i in index]

pytorch3d/structures/volumes.py

@@ -155,7 +155,7 @@ class Volumes:
         features: Optional[_TensorBatch] = None,
         voxel_size: _VoxelSize = 1.0,
         volume_translation: _Translation = (0.0, 0.0, 0.0),
-    ):
+    ) -> None:
         """
         Args:
             **densities**: Batch of input feature volume occupancies of shape

pytorch3d/transforms/transform3d.py

@@ -144,7 +144,7 @@ class Transform3d:
         dtype: torch.dtype = torch.float32,
         device: Device = "cpu",
         matrix: Optional[torch.Tensor] = None,
-    ):
+    ) -> None:
         """
         Args:
             dtype: The data type of the transformation matrix.
@@ -176,7 +176,7 @@ class Transform3d:
         self.device = make_device(device)
         self.dtype = dtype
 
-    def __len__(self):
+    def __len__(self) -> int:
         return self.get_matrix().shape[0]
 
     def __getitem__(
@@ -462,7 +462,7 @@ class Translate(Transform3d):
         z=None,
         dtype: torch.dtype = torch.float32,
         device: Optional[Device] = None,
-    ):
+    ) -> None:
         """
         Create a new Transform3d representing 3D translations.
 
@@ -503,7 +503,7 @@ class Scale(Transform3d):
         z=None,
         dtype: torch.dtype = torch.float32,
         device: Optional[Device] = None,
-    ):
+    ) -> None:
         """
         A Transform3d representing a scaling operation, with different scale
         factors along each coordinate axis.
@@ -549,7 +549,7 @@ class Rotate(Transform3d):
         dtype: torch.dtype = torch.float32,
         device: Optional[Device] = None,
         orthogonal_tol: float = 1e-5,
-    ):
+    ) -> None:
         """
         Create a new Transform3d representing 3D rotation using a rotation
         matrix as the input.
@@ -589,7 +589,7 @@ class RotateAxisAngle(Rotate):
         degrees: bool = True,
         dtype: torch.dtype = torch.float64,
         device: Optional[Device] = None,
-    ):
+    ) -> None:
         """
         Create a new Transform3d representing 3D rotation about an axis
         by an angle.