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Showing content from https://docs.pytorch.org/docs/stable/generated/torch.Tensor.sparse_mask.html below:

torch.Tensor.sparse_mask — PyTorch 2.7 documentation

Returns a new sparse tensor with values from a strided tensor self filtered by the indices of the sparse tensor mask. The values of mask sparse tensor are ignored. self and mask tensors must have the same shape.

>>> 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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