suppress errors in `vision/fair/pytorch3d`

Differential Revision: D23521117

fbshipit-source-id: 8e11e91aaa2a91b7ca1fa4c00a3db86ab8648f7f

pytorch3d/ops/cameras_alignment.py

@@ -97,6 +97,7 @@ def corresponding_cameras_alignment(
         cameras_src_aligned: `cameras_src` after applying the alignment transform.
     """
 
+    # pyre-fixme[16]: `CamerasBase` has no attribute `R`.
     if cameras_src.R.shape[0] != cameras_tgt.R.shape[0]:
         raise ValueError(
             "cameras_src and cameras_tgt have to contain the same number of cameras!"
@@ -120,6 +121,7 @@ def corresponding_cameras_alignment(
         torch.bmm(
             align_t_T[:, None].repeat(cameras_src.R.shape[0], 1, 1), cameras_src.R
         )[:, 0]
+        # pyre-fixme[16]: `CamerasBase` has no attribute `T`.
         + cameras_src.T * align_t_s
     )
 
@@ -167,6 +169,7 @@ def _align_camera_extrinsics(
         R_A = (U V^T)^T
         ```
     """
+    # pyre-fixme[16]: `CamerasBase` has no attribute `R`.
     RRcov = torch.bmm(cameras_src.R, cameras_tgt.R.transpose(2, 1)).mean(0)
     U, _, V = torch.svd(RRcov)
     align_t_R = V @ U.t()
@@ -196,6 +199,7 @@ def _align_camera_extrinsics(
         T_A = mean(B) - mean(A) * s_A
         ```
     """
+    # pyre-fixme[16]: `CamerasBase` has no attribute `T`.
     A = torch.bmm(cameras_src.R, cameras_src.T[:, :, None])[:, :, 0]
     B = torch.bmm(cameras_src.R, cameras_tgt.T[:, :, None])[:, :, 0]
     Amu = A.mean(0, keepdim=True)