423A35C7/pytorch3d
1
0
Fork 0
mirror of https://github.com/facebookresearch/pytorch3d.git synced 2026-10-17 19:55:43 +08:00
Code Issues Packages Projects Releases Wiki Activity

Suppress type errors for Pyre upgrade

Browse Source 
Summary:
This diff was automatically generated by the Pyre per-target upgrade tool.

It adds `# pyrefly: ignore` comments for type errors that an upcoming Pyrefly version will report. These suppressions keep existing type-checking tests passing while the upgrade rolls out. This diff changes comments only; it does not change Python runtime behavior or application logic.

pyre-upgrade-september-29

#pyreupgrade

Differential Revision: D122460195

fbshipit-source-id: 2ca62cd61e77d222c5b42ac89e73fc570a9781ae
This commit is contained in:
generatedunixname89002005307016
2026-09-29 23:00:50 -07:00
committed by meta-codesync[bot]
parent 978cd99221
commit 88e182f989
5 changed files with 14 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
pytorch3d/implicitron/tools/eval_video_trajectory.py
View File

@@ -182,10 +182,12 @@ def generate_eval_video_cameras(
) )
test_cameras = PerspectiveCameras( test_cameras = PerspectiveCameras(
# pyrefly: ignore [bad-argument-type]
focal_length=focal_length, focal_length=focal_length,
principal_point=principal_point, principal_point=principal_point,
R=R, R=R,
T=T, T=T,
# pyrefly: ignore [missing-attribute]
device=focal_length.device, device=focal_length.device,
) )

3
pytorch3d/ops/points_alignment.py
View File

@@ -340,8 +340,11 @@ def corresponding_points_alignment(
total_weight = torch.clamp(num_points, 1) total_weight = torch.clamp(num_points, 1)
# special handling for heterogeneous point clouds and/or input weights # special handling for heterogeneous point clouds and/or input weights
if weights is not None: if weights is not None:
# pyrefly: ignore [bad-index]
Xc *= weights[:, :, None] Xc *= weights[:, :, None]
# pyrefly: ignore [bad-index]
Yc *= weights[:, :, None] Yc *= weights[:, :, None]
# pyrefly: ignore [missing-attribute]
total_weight = torch.clamp(weights.sum(1), eps) total_weight = torch.clamp(weights.sum(1), eps)
if (num_points < (dim + 1)).any(): if (num_points < (dim + 1)).any():

4
pytorch3d/renderer/cameras.py
View File

@@ -427,9 +427,11 @@ class CamerasBase(TensorProperties):
if isinstance(index, tensor_types["bool"]): if isinstance(index, tensor_types["bool"]):
# LongTensor]` has no attribute `ndim`. # LongTensor]` has no attribute `ndim`.
# LongTensor]` has no attribute `shape`. # LongTensor]` has no attribute `shape`.
# pyrefly: ignore [missing-attribute]
if index.ndim != 1 or index.shape[0] != len(self): if index.ndim != 1 or index.shape[0] != len(self):
raise ValueError( raise ValueError(
# LongTensor]` has no attribute `shape`. # LongTensor]` has no attribute `shape`.
# pyrefly: ignore [missing-attribute]
f"Boolean index of shape {index.shape} does not match cameras" f"Boolean index of shape {index.shape} does not match cameras"
) )
elif max(index) >= len(self): elif max(index) >= len(self):
@@ -1790,11 +1792,13 @@ def get_ndc_to_screen_transform(
image_size = torch.tensor(image_size, device=cameras.device) image_size = torch.tensor(image_size, device=cameras.device)
# pyrefly: ignore [missing-attribute] # pyrefly: ignore [missing-attribute]
image_size = image_size.view(-1, 2) # of shape (1 or B)x2 image_size = image_size.view(-1, 2) # of shape (1 or B)x2
# pyrefly: ignore [missing-attribute]
height, width = image_size.unbind(1) height, width = image_size.unbind(1)
# For non square images, we scale the points such that smallest side # For non square images, we scale the points such that smallest side
# has range [-1, 1] and the largest side has range [-u, u], with u > 1. # has range [-1, 1] and the largest side has range [-u, u], with u > 1.
# This convention is consistent with the PyTorch3D renderer # This convention is consistent with the PyTorch3D renderer
# pyrefly: ignore [missing-attribute]
scale = (image_size.min(dim=1).values - 0.0) / 2.0 scale = (image_size.min(dim=1).values - 0.0) / 2.0
K[:, 0, 0] = scale K[:, 0, 0] = scale

2
pytorch3d/structures/meshes.py
View File

@@ -510,7 +510,9 @@ class Meshes:
index = index.squeeze(1) if index.numel() > 0 else index index = index.squeeze(1) if index.numel() > 0 else index
# pyrefly: ignore [missing-attribute] # pyrefly: ignore [missing-attribute]
index = index.tolist() index = index.tolist()
# pyrefly: ignore [not-iterable]
verts = [self.verts_list()[i] for i in index] verts = [self.verts_list()[i] for i in index]
# pyrefly: ignore [not-iterable]
faces = [self.faces_list()[i] for i in index] faces = [self.faces_list()[i] for i in index]
else: else:
raise IndexError(index) raise IndexError(index)

3
pytorch3d/structures/pointclouds.py
View File

@@ -411,10 +411,13 @@ class Pointclouds:
index = index.squeeze(1) if index.numel() > 0 else index index = index.squeeze(1) if index.numel() > 0 else index
# pyrefly: ignore [missing-attribute] # pyrefly: ignore [missing-attribute]
index = index.tolist() index = index.tolist()
# pyrefly: ignore [not-iterable]
points = [self.points_list()[i] for i in index] points = [self.points_list()[i] for i in index]
if normals_list is not None: if normals_list is not None:
# pyrefly: ignore [not-iterable]
normals = [normals_list[i] for i in index] normals = [normals_list[i] for i in index]
if features_list is not None: if features_list is not None:
# pyrefly: ignore [not-iterable]
features = [features_list[i] for i in index] features = [features_list[i] for i in index]
else: else:
raise IndexError(index) raise IndexError(index)