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torch.Tensor.sparse_mask
Tensor.sparse_mask(mask) → Tensor
-
Returns a new sparse tensor with values from a strided tensor
self
filtered by the indices of the sparse tensormask
. The values ofmask
sparse tensor are ignored.self
andmask
tensors must have the same shape.Note
The returned sparse tensor might contain duplicate values if
mask
is not coalesced. It is therefore advisable to passmask.coalesce()
if such behavior is not desired.Note
The returned sparse tensor has the same indices as the sparse tensor
mask
, even when the corresponding values inself
are zeros.- Parameters
-
mask (Tensor) – a sparse tensor whose indices are used as a filter
Example:
>>> nse = 5 >>> dims = (5, 5, 2, 2) >>> I = torch.cat([torch.randint(0, dims[0], size=(nse,)), ... torch.randint(0, dims[1], size=(nse,))], 0).reshape(2, nse) >>> V = torch.randn(nse, dims[2], dims[3]) >>> S = torch.sparse_coo_tensor(I, V, dims).coalesce() >>> D = torch.randn(dims) >>> D.sparse_mask(S) tensor(indices=tensor([[0, 0, 0, 2], [0, 1, 4, 3]]), values=tensor([[[ 1.6550, 0.2397], [-0.1611, -0.0779]], [[ 0.2326, -1.0558], [ 1.4711, 1.9678]], [[-0.5138, -0.0411], [ 1.9417, 0.5158]], [[ 0.0793, 0.0036], [-0.2569, -0.1055]]]), size=(5, 5, 2, 2), nnz=4, layout=torch.sparse_coo)
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https://pytorch.org/docs/2.1/generated/torch.Tensor.sparse_mask.html