for CPU tensor types and the current CUDA device for CUDA
        tensor types.
  * **requires_grad** (*bool**, **optional*) -- If autograd should
    record operations on the returned tensor. Default: "False".

  * **check_invariants** (*bool**, **optional*) -- If sparse
    tensor invariants are checked. Default: as returned by
    "torch.sparse.check_sparse_tensor_invariants.is_enabled()",
    initially False.

Example::
      >>> compressed_indices = [0, 2, 4]
      >>> plain_indices = [0, 1, 0, 1]
      >>> values = [1, 2, 3, 4]
      >>> torch.sparse_compressed_tensor(torch.tensor(compressed_indices, dtype=torch.int64),
      ...                                torch.tensor(plain_indices, dtype=torch.int64),
      ...                                torch.tensor(values), dtype=torch.double, layout=torch.sparse_csr)
      tensor(crow_indices=tensor([0, 2, 4]),
             col_indices=tensor([0, 1, 0, 1]),
             values=tensor([1., 2., 3., 4.]), size=(2, 2), nnz=4,