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

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.