Add pyre typeshed information for Tensor.ndim and nn.ConvTranspose2d

Summary: Adding some appropriate methods into pyre typeshed. Removing corresponding pyre-ignore and pyre-fixme messages.

Differential Revision: D22949138

fbshipit-source-id: add8acdd4611ab698954868832594d062cd58f88

pytorch3d/loss/chamfer.py

@@ -41,7 +41,6 @@ def _handle_pointcloud_input(
         lengths = points.num_points_per_cloud()
         normals = points.normals_padded()  # either a tensor or None
     elif torch.is_tensor(points):
-        # pyre-fixme[16]: `Tensor` has no attribute `ndim`.
         if points.ndim != 3:
             raise ValueError("Expected points to be of shape (N, P, D)")
         X = points

pytorch3d/renderer/mesh/textures.py

@@ -52,7 +52,6 @@ def _list_to_padded_wrapper(
       x_padded: tensor consisting of padded input tensors
     """
     N = len(x)
-    # pyre-fixme[16]: `Tensor` has no attribute `ndim`.
     dims = x[0].ndim
     reshape_dims = x[0].shape[1:]
     D = torch.prod(torch.tensor(reshape_dims)).item()
@@ -598,7 +597,6 @@ class TexturesUV(TexturesBase):
         self.align_corners = align_corners
         if isinstance(faces_uvs, (list, tuple)):
             for fv in faces_uvs:
-                # pyre-fixme[16]: `Tensor` has no attribute `ndim`.
                 if fv.ndim != 2 or fv.shape[-1] != 3:
                     msg = "Expected faces_uvs to be of shape (F, 3); got %r"
                     raise ValueError(msg % repr(fv.shape))
@@ -1129,9 +1127,7 @@ class TexturesVertex(TexturesBase):
         """
         if isinstance(verts_features, (tuple, list)):
             correct_shape = all(
-                # pyre-fixme[16]: `Tensor` has no attribute `ndim`.
-                (torch.is_tensor(v) and v.ndim == 2)
-                for v in verts_features
+                (torch.is_tensor(v) and v.ndim == 2) for v in verts_features
             )
             if not correct_shape:
                 raise ValueError(

pytorch3d/structures/utils.py

@@ -48,7 +48,6 @@ def list_to_padded(
     )
     for i, y in enumerate(x):
         if len(y) > 0:
-            # pyre-fixme[16]: `Tensor` has no attribute `ndim`.
             if y.ndim != 2:
                 raise ValueError("Supports only 2-dimensional tensor items")
             x_padded[i, : y.shape[0], : y.shape[1]] = y
@@ -70,7 +69,6 @@ def padded_to_list(x: torch.Tensor, split_size: Union[list, tuple, None] = None)
     Returns:
       x_list: a list of tensors
     """
-    # pyre-fixme[16]: `Tensor` has no attribute `ndim`.
     if x.ndim != 3:
         raise ValueError("Supports only 3-dimensional input tensors")
 
@@ -178,7 +176,6 @@ def padded_to_packed(
     Returns:
       x_packed: a packed tensor.
     """
-    # pyre-fixme[16]: `Tensor` has no attribute `ndim`.
     if x.ndim != 3:
         raise ValueError("Supports only 3-dimensional input tensors")
 

pytorch3d/transforms/transform3d.py

@@ -155,7 +155,6 @@ class Transform3d:
         if matrix is None:
             self._matrix = torch.eye(4, dtype=dtype, device=device).view(1, 4, 4)
         else:
-            # pyre-fixme[16]: `Tensor` has no attribute `ndim`.
             if matrix.ndim not in (2, 3):
                 raise ValueError('"matrix" has to be a 2- or a 3-dimensional tensor.')
             if matrix.shape[-2] != 4 or matrix.shape[-1] != 4: