suppress errors in vision/fair/pytorch3d

Differential Revision: D30479084

fbshipit-source-id: 6b22dd0afe4dfb1be6249e43a56657519f11dcf1

pytorch3d/datasets/r2n2/utils.py

@@ -144,7 +144,10 @@ def compute_extrinsic_matrix(azimuth, elevation, distance):  # pragma: no cover
 
 
 def read_binvox_coords(
-    f, integer_division: bool = True, dtype: torch.dtype = torch.float32
+    f,
+    integer_division: bool = True,
+    # pyre-fixme[9]: dtype has type `dtype`; used as `Type[torch.float32]`.
+    dtype: torch.dtype = torch.float32,
 ):  # pragma: no cover
     """
     Copied from meshrcnn codebase:

pytorch3d/io/obj_io.py

@@ -576,12 +576,21 @@ def _load_obj(
         mtl_path,
     ) = _parse_obj(f_obj, data_dir)
 
+    # pyre-fixme[6]: Expected `dtype` for 3rd param but got `Type[torch.float32]`.
     verts = _make_tensor(verts, cols=3, dtype=torch.float32, device=device)  # (V, 3)
     normals = _make_tensor(
-        normals, cols=3, dtype=torch.float32, device=device
+        normals,
+        cols=3,
+        # pyre-fixme[6]: Expected `dtype` for 3rd param but got `Type[torch.float32]`.
+        dtype=torch.float32,
+        device=device,
     )  # (N, 3)
     verts_uvs = _make_tensor(
-        verts_uvs, cols=2, dtype=torch.float32, device=device
+        verts_uvs,
+        cols=2,
+        # pyre-fixme[6]: Expected `dtype` for 3rd param but got `Type[torch.float32]`.
+        dtype=torch.float32,
+        device=device,
     )  # (T, 2)
 
     faces_verts_idx = _format_faces_indices(

pytorch3d/io/ply_io.py

@@ -884,6 +884,7 @@ def _get_verts(
         and vertex[0].ndim == 2
         and vertex[0].shape[1] == 3
     ):
+        # pyre-fixme[6]: Expected `dtype` for 3rd param but got `Type[torch.float32]`.
         return _make_tensor(vertex[0], cols=3, dtype=torch.float32), None, None
 
     vertex_colors = None

pytorch3d/ops/utils.py

@@ -58,6 +58,7 @@ def eyes(
     dim: int,
     N: int,
     device: Optional[torch.device] = None,
+    # pyre-fixme[9]: dtype has type `dtype`; used as `Type[torch.float32]`.
     dtype: torch.dtype = torch.float32,
 ) -> torch.Tensor:
     """

pytorch3d/renderer/cameras.py

@@ -253,6 +253,8 @@ class CamerasBase(TensorProperties):
         input points to the renderer to be in NDC space.
         """
         if self.in_ndc():
+            # pyre-fixme[6]: Expected `dtype` for 2nd param but got
+            #  `Type[torch.float32]`.
             return Transform3d(device=self.device, dtype=torch.float32)
         else:
             # For custom cameras which can be defined in screen space,
@@ -1031,6 +1033,8 @@ class PerspectiveCameras(CamerasBase):
         i.e. +X left, +Y up.
         """
         if self.in_ndc():
+            # pyre-fixme[6]: Expected `dtype` for 2nd param but got
+            #  `Type[torch.float32]`.
             ndc_transform = Transform3d(device=self.device, dtype=torch.float32)
         else:
             # when cameras are defined in screen/image space, the principal point is
@@ -1229,6 +1233,8 @@ class OrthographicCameras(CamerasBase):
         i.e. +X left, +Y up.
         """
         if self.in_ndc():
+            # pyre-fixme[6]: Expected `dtype` for 2nd param but got
+            #  `Type[torch.float32]`.
             ndc_transform = Transform3d(device=self.device, dtype=torch.float32)
         else:
             # when cameras are defined in screen/image space, the principal point is

pytorch3d/renderer/utils.py

@@ -95,7 +95,11 @@ class TensorProperties(nn.Module):
     """
 
     def __init__(
-        self, dtype: torch.dtype = torch.float32, device: Device = "cpu", **kwargs
+        self,
+        # pyre-fixme[9]: dtype has type `dtype`; used as `Type[torch.float32]`.
+        dtype: torch.dtype = torch.float32,
+        device: Device = "cpu",
+        **kwargs,
     ) -> None:
         """
         Args:
@@ -273,7 +277,10 @@ class TensorProperties(nn.Module):
 
 
 def format_tensor(
-    input, dtype: torch.dtype = torch.float32, device: Device = "cpu"
+    input,
+    # pyre-fixme[9]: dtype has type `dtype`; used as `Type[torch.float32]`.
+    dtype: torch.dtype = torch.float32,
+    device: Device = "cpu",
 ) -> torch.Tensor:
     """
     Helper function for converting a scalar value to a tensor.
@@ -301,7 +308,10 @@ def format_tensor(
 
 
 def convert_to_tensors_and_broadcast(
-    *args, dtype: torch.dtype = torch.float32, device: Device = "cpu"
+    *args,
+    # pyre-fixme[9]: dtype has type `dtype`; used as `Type[torch.float32]`.
+    dtype: torch.dtype = torch.float32,
+    device: Device = "cpu",
 ):
     """
     Helper function to handle parsing an arbitrary number of inputs (*args)

pytorch3d/transforms/transform3d.py

@@ -142,6 +142,7 @@ class Transform3d:
 
     def __init__(
         self,
+        # pyre-fixme[9]: dtype has type `dtype`; used as `Type[torch.float32]`.
         dtype: torch.dtype = torch.float32,
         device: Device = "cpu",
         matrix: Optional[torch.Tensor] = None,
@@ -461,6 +462,7 @@ class Translate(Transform3d):
         x,
         y=None,
         z=None,
+        # pyre-fixme[9]: dtype has type `dtype`; used as `Type[torch.float32]`.
         dtype: torch.dtype = torch.float32,
         device: Optional[Device] = None,
     ) -> None:
@@ -502,6 +504,7 @@ class Scale(Transform3d):
         x,
         y=None,
         z=None,
+        # pyre-fixme[9]: dtype has type `dtype`; used as `Type[torch.float32]`.
         dtype: torch.dtype = torch.float32,
         device: Optional[Device] = None,
     ) -> None:
@@ -547,6 +550,7 @@ class Rotate(Transform3d):
     def __init__(
         self,
         R: torch.Tensor,
+        # pyre-fixme[9]: dtype has type `dtype`; used as `Type[torch.float32]`.
         dtype: torch.dtype = torch.float32,
         device: Optional[Device] = None,
         orthogonal_tol: float = 1e-5,
@@ -588,6 +592,7 @@ class RotateAxisAngle(Rotate):
         angle,
         axis: str = "X",
         degrees: bool = True,
+        # pyre-fixme[9]: dtype has type `dtype`; used as `Type[torch.float64]`.
         dtype: torch.dtype = torch.float64,
         device: Optional[Device] = None,
     ) -> None: