Add annotations to vision/fair/pytorch3d

Reviewed By: shannonzhu

Differential Revision: D33970393

fbshipit-source-id: 9b4dfaccfc3793fd37705a923d689cb14c9d26ba

pytorch3d/datasets/r2n2/utils.py

@@ -98,7 +98,9 @@ def collate_batched_R2N2(batch: List[Dict]):  # pragma: no cover
     return collated_dict
 
 
-def compute_extrinsic_matrix(azimuth, elevation, distance):  # pragma: no cover
+def compute_extrinsic_matrix(
+    azimuth: float, elevation: float, distance: float
+):  # pragma: no cover
     """
     Copied from meshrcnn codebase:
     https://github.com/facebookresearch/meshrcnn/blob/main/shapenet/utils/coords.py#L96
@@ -138,6 +140,7 @@ def compute_extrinsic_matrix(azimuth, elevation, distance):  # pragma: no cover
     # rotates the model 90 degrees about the x axis. To compensate for this quirk we
     # roll that rotation into the extrinsic matrix here
     rot = torch.tensor([[1, 0, 0, 0], [0, 0, -1, 0], [0, 1, 0, 0], [0, 0, 0, 1]])
+    # pyre-fixme[16]: `Tensor` has no attribute `mm`.
     RT = RT.mm(rot.to(RT))
 
     return RT
@@ -384,7 +387,7 @@ def voxelize(voxel_coords, P, V):  # pragma: no cover
     return voxels
 
 
-def project_verts(verts, P, eps=1e-1):  # pragma: no cover
+def project_verts(verts, P, eps: float = 1e-1):  # pragma: no cover
     """
     Copied from meshrcnn codebase:
     https://github.com/facebookresearch/meshrcnn/blob/main/shapenet/utils/coords.py#L159

pytorch3d/io/obj_io.py

@@ -32,7 +32,7 @@
 )
 
 
-def _format_faces_indices(faces_indices, max_index, device, pad_value=None):
+def _format_faces_indices(faces_indices, max_index: int, device, pad_value=None):
     """
     Format indices and check for invalid values. Indices can refer to
     values in one of the face properties: vertices, textures or normals.
@@ -57,6 +57,7 @@ def _format_faces_indices(faces_indices, max_index, device, pad_value=None):
     )
 
     if pad_value is not None:
+        # pyre-fixme[28]: Unexpected keyword argument `dim`.
         mask = faces_indices.eq(pad_value).all(dim=-1)
 
     # Change to 0 based indexing.
@@ -66,14 +67,15 @@ def _format_faces_indices(faces_indices, max_index, device, pad_value=None):
     faces_indices[(faces_indices < 0)] += max_index
 
     if pad_value is not None:
+        # pyre-fixme[61]: `mask` is undefined, or not always defined.
         faces_indices[mask] = pad_value
 
     return _check_faces_indices(faces_indices, max_index, pad_value)
 
 
 def load_obj(
     f,
-    load_textures=True,
+    load_textures: bool = True,
     create_texture_atlas: bool = False,
     texture_atlas_size: int = 4,
     texture_wrap: Optional[str] = "repeat",
@@ -351,7 +353,7 @@ def _parse_face(
     faces_normals_idx,
     faces_textures_idx,
     faces_materials_idx,
-):
+) -> None:
     face = tokens[1:]
     face_list = [f.split("/") for f in face]
     face_verts = []
@@ -546,7 +548,7 @@ def _load_materials(
 def _load_obj(
     f_obj,
     *,
-    data_dir,
+    data_dir: str,
     load_textures: bool = True,
     create_texture_atlas: bool = False,
     texture_atlas_size: int = 4,

pytorch3d/io/ply_io.py

@@ -463,7 +463,9 @@ def _read_ply_element_ascii(f, definition: _PlyElementType):
     return data
 
 
-def _read_raw_array(f, aim: str, length: int, dtype: type = np.uint8, dtype_size=1):
+def _read_raw_array(
+    f, aim: str, length: int, dtype: type = np.uint8, dtype_size: int = 1
+):
     """
     Read [length] elements from a file.
 

pytorch3d/io/utils.py

@@ -28,7 +28,7 @@ def nullcontext(x):
 PathOrStr = Union[pathlib.Path, str]
 
 
-def _open_file(f, path_manager: PathManager, mode="r") -> ContextManager[IO]:
+def _open_file(f, path_manager: PathManager, mode: str = "r") -> ContextManager[IO]:
     if isinstance(f, str):
         f = path_manager.open(f, mode)
         return contextlib.closing(f)

pytorch3d/loss/chamfer.py

@@ -14,7 +14,7 @@
 
 def _validate_chamfer_reduction_inputs(
     batch_reduction: Union[str, None], point_reduction: str
-):
+) -> None:
     """Check the requested reductions are valid.
 
     Args:

pytorch3d/ops/knn.py

@@ -106,7 +106,7 @@ def knn_points(
     version: int = -1,
     return_nn: bool = False,
     return_sorted: bool = True,
-):
+) -> _KNN:
     """
     K-Nearest neighbors on point clouds.
 

pytorch3d/ops/points_normals.py

@@ -166,7 +166,7 @@ def estimate_pointcloud_local_coord_frames(
     return curvatures, local_coord_frames
 
 
-def _disambiguate_vector_directions(pcl, knns, vecs):
+def _disambiguate_vector_directions(pcl, knns, vecs: float) -> float:
     """
     Disambiguates normal directions according to [1].
 
@@ -180,6 +180,7 @@ def _disambiguate_vector_directions(pcl, knns, vecs):
     # each element of the neighborhood
     df = knns - pcl[:, :, None]
     # projection of the difference on the principal direction
+    # pyre-fixme[16]: `float` has no attribute `__getitem__`.
     proj = (vecs[:, :, None] * df).sum(3)
     # check how many projections are positive
     n_pos = (proj > 0).type_as(knns).sum(2, keepdim=True)

pytorch3d/ops/points_to_volumes.py

@@ -479,7 +479,7 @@ def _check_points_to_volumes_inputs(
     volume_features: torch.Tensor,
     grid_sizes: torch.LongTensor,
     mask: Optional[torch.Tensor] = None,
-):
+) -> None:
 
     max_grid_size = grid_sizes.max(dim=0).values
     if torch.prod(max_grid_size) > volume_densities.shape[1]:

pytorch3d/ops/subdivide_meshes.py

@@ -400,7 +400,7 @@ def create_verts_index(verts_per_mesh, edges_per_mesh, device=None):
     return verts_idx
 
 
-def create_faces_index(faces_per_mesh, device=None):
+def create_faces_index(faces_per_mesh: int, 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
@@ -417,7 +417,9 @@ def create_faces_index(faces_per_mesh, device=None):
     """
     # e.g. faces_per_mesh = [2, 5, 3]
 
+    # pyre-fixme[16]: `int` has no attribute `sum`.
     F = faces_per_mesh.sum()  # e.g. 10
+    # pyre-fixme[16]: `int` has no attribute `cumsum`.
     faces_per_mesh_cumsum = faces_per_mesh.cumsum(dim=0)  # (N,) e.g. (2, 7, 10)
 
     switch1_idx = faces_per_mesh_cumsum.clone()

pytorch3d/ops/utils.py

@@ -150,7 +150,7 @@ def convert_pointclouds_to_tensor(pcl: Union[torch.Tensor, "Pointclouds"]):
     return X, num_points
 
 
-def is_pointclouds(pcl: Union[torch.Tensor, "Pointclouds"]):
+def is_pointclouds(pcl: Union[torch.Tensor, "Pointclouds"]) -> bool:
     """Checks whether the input `pcl` is an instance of `Pointclouds`
     by checking the existence of `points_padded` and `num_points_per_cloud`
     functions.

pytorch3d/renderer/cameras.py

@@ -427,10 +427,10 @@ def __getitem__(
 
 
 def OpenGLPerspectiveCameras(
-    znear=1.0,
-    zfar=100.0,
-    aspect_ratio=1.0,
-    fov=60.0,
+    znear: float = 1.0,
+    zfar: float = 100.0,
+    aspect_ratio: float = 1.0,
+    fov: float = 60.0,
     degrees: bool = True,
     R: torch.Tensor = _R,
     T: torch.Tensor = _T,
@@ -709,12 +709,12 @@ def in_ndc(self):
 
 
 def OpenGLOrthographicCameras(
-    znear=1.0,
-    zfar=100.0,
-    top=1.0,
-    bottom=-1.0,
-    left=-1.0,
-    right=1.0,
+    znear: float = 1.0,
+    zfar: float = 100.0,
+    top: float = 1.0,
+    bottom: float = -1.0,
+    left: float = -1.0,
+    right: float = 1.0,
     scale_xyz=((1.0, 1.0, 1.0),),  # (1, 3)
     R: torch.Tensor = _R,
     T: torch.Tensor = _T,
@@ -956,7 +956,7 @@ def in_ndc(self):
 
 
 def SfMPerspectiveCameras(
-    focal_length=1.0,
+    focal_length: float = 1.0,
     principal_point=((0.0, 0.0),),
     R: torch.Tensor = _R,
     T: torch.Tensor = _T,
@@ -1194,7 +1194,7 @@ def in_ndc(self):
 
 
 def SfMOrthographicCameras(
-    focal_length=1.0,
+    focal_length: float = 1.0,
     principal_point=((0.0, 0.0),),
     R: torch.Tensor = _R,
     T: torch.Tensor = _T,
@@ -1645,9 +1645,9 @@ def look_at_rotation(
 
 
 def look_at_view_transform(
-    dist=1.0,
-    elev=0.0,
-    azim=0.0,
+    dist: float = 1.0,
+    elev: float = 0.0,
+    azim: float = 0.0,
     degrees: bool = True,
     eye: Optional[Sequence] = None,
     at=((0, 0, 0),),  # (1, 3)

pytorch3d/renderer/implicit/raymarching.py

@@ -162,7 +162,7 @@ def forward(
         return opacities
 
 
-def _shifted_cumprod(x, shift=1):
+def _shifted_cumprod(x, shift: int = 1):
     """
     Computes `torch.cumprod(x, dim=-1)` and prepends `shift` number of
     ones and removes `shift` trailing elements to/from the last dimension
@@ -177,7 +177,7 @@ def _shifted_cumprod(x, shift=1):
 
 def _check_density_bounds(
     rays_densities: torch.Tensor, bounds: Tuple[float, float] = (0.0, 1.0)
-):
+) -> None:
     """
     Checks whether the elements of `rays_densities` range within `bounds`.
     If not issues a warning.
@@ -197,7 +197,7 @@ def _check_raymarcher_inputs(
     features_can_be_none: bool = False,
     z_can_be_none: bool = False,
     density_1d: bool = True,
-):
+) -> None:
     """
     Checks the validity of the inputs to raymarching algorithms.
     """

pytorch3d/renderer/implicit/utils.py

@@ -98,7 +98,7 @@ def _validate_ray_bundle_variables(
     rays_origins: torch.Tensor,
     rays_directions: torch.Tensor,
     rays_lengths: torch.Tensor,
-):
+) -> None:
     """
     Validate the shapes of RayBundle variables
     `rays_origins`, `rays_directions`, and `rays_lengths`.

pytorch3d/renderer/lighting.py

@@ -323,7 +323,7 @@ def specular(self, normals, points, camera_position, shininess) -> torch.Tensor:
         return torch.zeros_like(points)
 
 
-def _validate_light_properties(obj):
+def _validate_light_properties(obj) -> None:
     props = ("ambient_color", "diffuse_color", "specular_color")
     for n in props:
         t = getattr(obj, n)

pytorch3d/renderer/mesh/shader.py

@@ -301,7 +301,7 @@ def TexturedSoftPhongShader(
     lights: Optional[TensorProperties] = None,
     materials: Optional[Materials] = None,
     blend_params: Optional[BlendParams] = None,
-):
+) -> SoftPhongShader:
     """
     TexturedSoftPhongShader class has been DEPRECATED. Use SoftPhongShader instead.
     Preserving TexturedSoftPhongShader as a function for backwards compatibility.

pytorch3d/structures/meshes.py

@@ -1557,7 +1557,7 @@ def sample_textures(self, fragments):
             raise ValueError("Meshes does not have textures")
 
 
-def join_meshes_as_batch(meshes: List[Meshes], include_textures: bool = True):
+def join_meshes_as_batch(meshes: List[Meshes], include_textures: bool = True) -> Meshes:
     """
     Merge multiple Meshes objects, i.e. concatenate the meshes objects. They
     must all be on the same device. If include_textures is true, they must all

pytorch3d/structures/pointclouds.py

@@ -1224,7 +1224,7 @@ def inside_box(self, box):
         return coord_inside.all(dim=-1)
 
 
-def join_pointclouds_as_batch(pointclouds: Sequence[Pointclouds]):
+def join_pointclouds_as_batch(pointclouds: Sequence[Pointclouds]) -> Pointclouds:
     """
     Merge a list of Pointclouds objects into a single batched Pointclouds
     object. All pointclouds must be on the same device.

pytorch3d/transforms/math.py

@@ -10,7 +10,7 @@
 import torch
 
 
-DEFAULT_ACOS_BOUND = 1.0 - 1e-4
+DEFAULT_ACOS_BOUND: float = 1.0 - 1e-4
 
 
 def acos_linear_extrapolation(

pytorch3d/transforms/transform3d.py

@@ -754,7 +754,7 @@ def _broadcast_bmm(a, b):
 
 
 @torch.no_grad()
-def _check_valid_rotation_matrix(R, tol: float = 1e-7):
+def _check_valid_rotation_matrix(R, tol: float = 1e-7) -> None:
     """
     Determine if R is a valid rotation matrix by checking it satisfies the
     following conditions: