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suppress errors in vision/fair/pytorch3d
Differential Revision: D49531589 fbshipit-source-id: 61c28ae33d2e5f75fd1695f35dc99931a3aaf7d3
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@ -45,6 +45,7 @@ def laplacian(verts: torch.Tensor, edges: torch.Tensor) -> torch.Tensor:
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# i.e. A[i, j] = 1 if (i,j) is an edge, or
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# A[e0, e1] = 1 & A[e1, e0] = 1
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ones = torch.ones(idx.shape[1], dtype=torch.float32, device=verts.device)
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# pyre-fixme[16]: Module `sparse` has no attribute `FloatTensor`.
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A = torch.sparse.FloatTensor(idx, ones, (V, V))
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# the sum of i-th row of A gives the degree of the i-th vertex
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@ -59,12 +60,14 @@ def laplacian(verts: torch.Tensor, edges: torch.Tensor) -> torch.Tensor:
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# pyre-fixme[58]: `/` is not supported for operand types `float` and `Tensor`.
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deg1 = torch.where(deg1 > 0.0, 1.0 / deg1, deg1)
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val = torch.cat([deg0, deg1])
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# pyre-fixme[16]: Module `sparse` has no attribute `FloatTensor`.
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L = torch.sparse.FloatTensor(idx, val, (V, V))
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# Then we add the diagonal values L[i, i] = -1.
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idx = torch.arange(V, device=verts.device)
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idx = torch.stack([idx, idx], dim=0)
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ones = torch.ones(idx.shape[1], dtype=torch.float32, device=verts.device)
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# pyre-fixme[16]: Module `sparse` has no attribute `FloatTensor`.
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L -= torch.sparse.FloatTensor(idx, ones, (V, V))
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return L
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@ -121,6 +124,7 @@ def cot_laplacian(
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ii = faces[:, [1, 2, 0]]
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jj = faces[:, [2, 0, 1]]
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idx = torch.stack([ii, jj], dim=0).view(2, F * 3)
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# pyre-fixme[16]: Module `sparse` has no attribute `FloatTensor`.
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L = torch.sparse.FloatTensor(idx, cot.view(-1), (V, V))
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# Make it symmetric; this means we are also setting
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@ -169,6 +173,7 @@ def norm_laplacian(
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e01 = edges.t() # (2, E)
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V = verts.shape[0]
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# pyre-fixme[16]: Module `sparse` has no attribute `FloatTensor`.
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L = torch.sparse.FloatTensor(e01, w01, (V, V))
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L = L + L.t()
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@ -401,7 +401,9 @@ class CamerasBase(TensorProperties):
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kwargs = {}
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tensor_types = {
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# pyre-fixme[16]: Module `cuda` has no attribute `BoolTensor`.
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"bool": (torch.BoolTensor, torch.cuda.BoolTensor),
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# pyre-fixme[16]: Module `cuda` has no attribute `LongTensor`.
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"long": (torch.LongTensor, torch.cuda.LongTensor),
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}
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if not isinstance(
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