423A35C7/pytorch3d
1
0
Fork 0
mirror of https://github.com/facebookresearch/pytorch3d.git synced 2026-03-07 04:36:00 +08:00
Code Issues Packages Projects Releases Wiki Activity

suppress errors in vision/fair/pytorch3d

Browse Source 
Differential Revision: D37172764

fbshipit-source-id: a2ec367e56de2781a17f5e708eb5832ec9d7e6b4
This commit is contained in:
Pyre Bot Jr
2022-06-15 06:27:35 -07:00
committed by Facebook GitHub Bot
parent ea4f3260e4
commit 7978ffd1e4
61 changed files with 188 additions and 80 deletions
Download Patch File Download Diff File Expand all files Collapse all files

13
pytorch3d/common/workaround/symeig3x3.py
View File

@@ -75,12 +75,14 @@ class _SymEig3x3(nn.Module):
if inputs.shape[-2:] != (3, 3):
raise ValueError("Only inputs of shape (..., 3, 3) are supported.")
inputs_diag = inputs.diagonal(dim1=-2, dim2=-1) # pyre-ignore[16]
inputs_diag = inputs.diagonal(dim1=-2, dim2=-1)
inputs_trace = inputs_diag.sum(-1)
q = inputs_trace / 3.0
# Calculate squared sum of elements outside the main diagonal / 2
# pyre-fixme[58]: `**` is not supported for operand types `Tensor` and `int`.
p1 = ((inputs**2).sum(dim=(-1, -2)) - (inputs_diag**2).sum(-1)) / 2
# pyre-fixme[58]: `**` is not supported for operand types `Tensor` and `int`.
p2 = ((inputs_diag - q[..., None]) ** 2).sum(dim=-1) + 2.0 * p1.clamp(self._eps)
p = torch.sqrt(p2 / 6.0)
@@ -195,8 +197,9 @@ class _SymEig3x3(nn.Module):
cross_products[..., :1, :]
)
# pyre-fixme[58]: `**` is not supported for operand types `Tensor` and `int`.
norms_sq = (cross_products**2).sum(dim=-1)
max_norms_index = norms_sq.argmax(dim=-1) # pyre-ignore[16]
max_norms_index = norms_sq.argmax(dim=-1)
# Pick only the cross-product with highest squared norm for each input
max_cross_products = self._gather_by_index(
@@ -227,9 +230,7 @@ class _SymEig3x3(nn.Module):
index_shape = list(source.shape)
index_shape[dim] = 1
return source.gather(dim, index.expand(index_shape)).squeeze( # pyre-ignore[16]
dim
)
return source.gather(dim, index.expand(index_shape)).squeeze(dim)
def _get_uv(self, w: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]:
"""
@@ -243,7 +244,7 @@ class _SymEig3x3(nn.Module):
Tuple of U and V unit-length vector tensors of shape (..., 3)
"""
min_idx = w.abs().argmin(dim=-1) # pyre-ignore[16]
min_idx = w.abs().argmin(dim=-1)
rotation_2d = self._rotations_3d[min_idx].to(w)
u = F.normalize((rotation_2d @ w[..., None])[..., 0], dim=-1)