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What does nnz in mean in the output of torch.sparse_coo_tensor(indices, values, size=None, dtype=None, device=None, requires_grad=False)?

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What does nnz mean in the output of below pytorch function

torch.sparse_coo_tensor(indices, values, size=None, dtype=None, device=None, requires_grad=False)

It can be found at this link https://pytorch.org/docs/stable/torch.html

i = torch.tensor([[0, 1, 1], [2, 0, 2]]) v = torch.tensor([3, 4, 5], dtype=torch.float32) torch.sparse_coo_tensor(i, v, [2, 4], dtype=torch.float64, device=torch.device('cuda:0')) tensor(indices=tensor([[0, 1, 1], [2, 0, 2]]), values=tensor([3., 4., 5.]), device='cuda:0', size=(2, 4), nnz=3, dtype=torch.float64, layout=torch.sparse_coo)

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