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TestSparseCompressedCUDA.test_print_SparseCSC_cuda.expect
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TestSparseCompressedCUDA.test_print_SparseCSC_cuda.expect
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########## torch.float32/torch.int32/size=()+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([1., 2., 3., 4.]), device='cuda:0', size=(3, 2), nnz=4,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0', dtype=torch.int32)
# _values
tensor([1., 2., 3., 4.], device='cuda:0')
########## torch.float32/torch.int32/size=()+(0, 0)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([0]),
row_indices=tensor([], size=(0,)),
values=tensor([], size=(0,)), device='cuda:0', size=(0, 0), nnz=0,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([], device='cuda:0', dtype=torch.int32)
# _values
tensor([], device='cuda:0')
########## torch.float32/torch.int32/size=(2,)+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([[0, 2, 4],
[0, 3, 4]]),
row_indices=tensor([[0, 1, 0, 1],
[0, 1, 2, 0]]),
values=tensor([[1., 2., 3., 4.],
[5., 6., 7., 8.]]), device='cuda:0', size=(2, 3, 2),
nnz=4, layout=torch.sparse_csc)
# _ccol_indices
tensor([[0, 2, 4],
[0, 3, 4]], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([[0, 1, 0, 1],
[0, 1, 2, 0]], device='cuda:0', dtype=torch.int32)
# _values
tensor([[1., 2., 3., 4.],
[5., 6., 7., 8.]], device='cuda:0')
########## torch.float32/torch.int32/size=(2, 3)+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]]),
row_indices=tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]]),
values=tensor([[[ 1., 2., 3., 4.],
[ 5., 6., 7., 8.],
[ 9., 10., 11., 12.]],
[[13., 14., 15., 16.],
[17., 18., 19., 20.],
[21., 22., 23., 24.]]]), device='cuda:0',
size=(2, 3, 3, 2), nnz=4, layout=torch.sparse_csc)
# _ccol_indices
tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]], device='cuda:0', dtype=torch.int32)
# _values
tensor([[[ 1., 2., 3., 4.],
[ 5., 6., 7., 8.],
[ 9., 10., 11., 12.]],
[[13., 14., 15., 16.],
[17., 18., 19., 20.],
[21., 22., 23., 24.]]], device='cuda:0')
########## torch.float64/torch.int32/size=()+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([1., 2., 3., 4.]), device='cuda:0', size=(3, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0', dtype=torch.int32)
# _values
tensor([1., 2., 3., 4.], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int32/size=()+(0, 0)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([0]),
row_indices=tensor([], size=(0,)),
values=tensor([], size=(0,)), device='cuda:0', size=(0, 0), nnz=0,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([0], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([], device='cuda:0', dtype=torch.int32)
# _values
tensor([], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int32/size=(2,)+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([[0, 2, 4],
[0, 3, 4]]),
row_indices=tensor([[0, 1, 0, 1],
[0, 1, 2, 0]]),
values=tensor([[1., 2., 3., 4.],
[5., 6., 7., 8.]]), device='cuda:0', size=(2, 3, 2),
nnz=4, dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([[0, 2, 4],
[0, 3, 4]], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([[0, 1, 0, 1],
[0, 1, 2, 0]], device='cuda:0', dtype=torch.int32)
# _values
tensor([[1., 2., 3., 4.],
[5., 6., 7., 8.]], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int32/size=(2, 3)+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]]),
row_indices=tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]]),
values=tensor([[[ 1., 2., 3., 4.],
[ 5., 6., 7., 8.],
[ 9., 10., 11., 12.]],
[[13., 14., 15., 16.],
[17., 18., 19., 20.],
[21., 22., 23., 24.]]]), device='cuda:0',
size=(2, 3, 3, 2), nnz=4, dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]], device='cuda:0', dtype=torch.int32)
# _values
tensor([[[ 1., 2., 3., 4.],
[ 5., 6., 7., 8.],
[ 9., 10., 11., 12.]],
[[13., 14., 15., 16.],
[17., 18., 19., 20.],
[21., 22., 23., 24.]]], device='cuda:0', dtype=torch.float64)
########## torch.float32/torch.int64/size=()+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([1., 2., 3., 4.]), device='cuda:0', size=(3, 2), nnz=4,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0')
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0')
# _values
tensor([1., 2., 3., 4.], device='cuda:0')
########## torch.float32/torch.int64/size=()+(0, 0)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([0]),
row_indices=tensor([], size=(0,)),
values=tensor([], size=(0,)), device='cuda:0', size=(0, 0), nnz=0,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0], device='cuda:0')
# _row_indices
tensor([], device='cuda:0', dtype=torch.int64)
# _values
tensor([], device='cuda:0')
########## torch.float32/torch.int64/size=(2,)+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([[0, 2, 4],
[0, 3, 4]]),
row_indices=tensor([[0, 1, 0, 1],
[0, 1, 2, 0]]),
values=tensor([[1., 2., 3., 4.],
[5., 6., 7., 8.]]), device='cuda:0', size=(2, 3, 2),
nnz=4, layout=torch.sparse_csc)
# _ccol_indices
tensor([[0, 2, 4],
[0, 3, 4]], device='cuda:0')
# _row_indices
tensor([[0, 1, 0, 1],
[0, 1, 2, 0]], device='cuda:0')
# _values
tensor([[1., 2., 3., 4.],
[5., 6., 7., 8.]], device='cuda:0')
########## torch.float32/torch.int64/size=(2, 3)+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]]),
row_indices=tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]]),
values=tensor([[[ 1., 2., 3., 4.],
[ 5., 6., 7., 8.],
[ 9., 10., 11., 12.]],
[[13., 14., 15., 16.],
[17., 18., 19., 20.],
[21., 22., 23., 24.]]]), device='cuda:0',
size=(2, 3, 3, 2), nnz=4, layout=torch.sparse_csc)
# _ccol_indices
tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]], device='cuda:0')
# _row_indices
tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]], device='cuda:0')
# _values
tensor([[[ 1., 2., 3., 4.],
[ 5., 6., 7., 8.],
[ 9., 10., 11., 12.]],
[[13., 14., 15., 16.],
[17., 18., 19., 20.],
[21., 22., 23., 24.]]], device='cuda:0')
########## torch.float64/torch.int64/size=()+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([1., 2., 3., 4.]), device='cuda:0', size=(3, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0')
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0')
# _values
tensor([1., 2., 3., 4.], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int64/size=()+(0, 0)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([0]),
row_indices=tensor([], size=(0,)),
values=tensor([], size=(0,)), device='cuda:0', size=(0, 0), nnz=0,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([0], device='cuda:0')
# _row_indices
tensor([], device='cuda:0', dtype=torch.int64)
# _values
tensor([], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int64/size=(2,)+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([[0, 2, 4],
[0, 3, 4]]),
row_indices=tensor([[0, 1, 0, 1],
[0, 1, 2, 0]]),
values=tensor([[1., 2., 3., 4.],
[5., 6., 7., 8.]]), device='cuda:0', size=(2, 3, 2),
nnz=4, dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([[0, 2, 4],
[0, 3, 4]], device='cuda:0')
# _row_indices
tensor([[0, 1, 0, 1],
[0, 1, 2, 0]], device='cuda:0')
# _values
tensor([[1., 2., 3., 4.],
[5., 6., 7., 8.]], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int64/size=(2, 3)+(3, 2)+() ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]]),
row_indices=tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]]),
values=tensor([[[ 1., 2., 3., 4.],
[ 5., 6., 7., 8.],
[ 9., 10., 11., 12.]],
[[13., 14., 15., 16.],
[17., 18., 19., 20.],
[21., 22., 23., 24.]]]), device='cuda:0',
size=(2, 3, 3, 2), nnz=4, dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]], device='cuda:0')
# _row_indices
tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]], device='cuda:0')
# _values
tensor([[[ 1., 2., 3., 4.],
[ 5., 6., 7., 8.],
[ 9., 10., 11., 12.]],
[[13., 14., 15., 16.],
[17., 18., 19., 20.],
[21., 22., 23., 24.]]], device='cuda:0', dtype=torch.float64)
########## torch.float32/torch.int32/size=()+(3, 2)+(2,) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[1., 2.],
[2., 3.],
[3., 4.],
[4., 5.]]), device='cuda:0', size=(3, 2, 2), nnz=4,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0', dtype=torch.int32)
# _values
tensor([[1., 2.],
[2., 3.],
[3., 4.],
[4., 5.]], device='cuda:0')
########## torch.float32/torch.int32/size=()+(3, 2)+(4, 2) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[ 1., 11.],
[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.],
[ 6., 16.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.],
[ 7., 17.]]]), device='cuda:0', size=(3, 2, 4, 2),
nnz=4, layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0', dtype=torch.int32)
# _values
tensor([[[ 1., 11.],
[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.],
[ 6., 16.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.],
[ 7., 17.]]], device='cuda:0')
########## torch.float32/torch.int32/size=(2, 3)+(3, 2)+(2, 1) ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]]),
row_indices=tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]]),
values=tensor([[[[[ 1.],
[ 2.]],
[[ 2.],
[ 3.]],
[[ 3.],
[ 4.]],
[[ 4.],
[ 5.]]],
[[[ 5.],
[ 6.]],
[[ 6.],
[ 7.]],
[[ 7.],
[ 8.]],
[[ 8.],
[ 9.]]],
[[[ 9.],
[10.]],
[[10.],
[11.]],
[[11.],
[12.]],
[[12.],
[13.]]]],
[[[[13.],
[14.]],
[[14.],
[15.]],
[[15.],
[16.]],
[[16.],
[17.]]],
[[[17.],
[18.]],
[[18.],
[19.]],
[[19.],
[20.]],
[[20.],
[21.]]],
[[[21.],
[22.]],
[[22.],
[23.]],
[[23.],
[24.]],
[[24.],
[25.]]]]]), device='cuda:0', size=(2, 3, 3, 2, 2, 1),
nnz=4, layout=torch.sparse_csc)
# _ccol_indices
tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]], device='cuda:0', dtype=torch.int32)
# _values
tensor([[[[[ 1.],
[ 2.]],
[[ 2.],
[ 3.]],
[[ 3.],
[ 4.]],
[[ 4.],
[ 5.]]],
[[[ 5.],
[ 6.]],
[[ 6.],
[ 7.]],
[[ 7.],
[ 8.]],
[[ 8.],
[ 9.]]],
[[[ 9.],
[10.]],
[[10.],
[11.]],
[[11.],
[12.]],
[[12.],
[13.]]]],
[[[[13.],
[14.]],
[[14.],
[15.]],
[[15.],
[16.]],
[[16.],
[17.]]],
[[[17.],
[18.]],
[[18.],
[19.]],
[[19.],
[20.]],
[[20.],
[21.]]],
[[[21.],
[22.]],
[[22.],
[23.]],
[[23.],
[24.]],
[[24.],
[25.]]]]], device='cuda:0')
########## torch.float64/torch.int32/size=()+(3, 2)+(2,) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[1., 2.],
[2., 3.],
[3., 4.],
[4., 5.]]), device='cuda:0', size=(3, 2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0', dtype=torch.int32)
# _values
tensor([[1., 2.],
[2., 3.],
[3., 4.],
[4., 5.]], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int32/size=()+(3, 2)+(4, 2) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[ 1., 11.],
[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.],
[ 6., 16.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.],
[ 7., 17.]]]), device='cuda:0', size=(3, 2, 4, 2),
nnz=4, dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0', dtype=torch.int32)
# _values
tensor([[[ 1., 11.],
[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.],
[ 6., 16.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.],
[ 7., 17.]]], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int32/size=(2, 3)+(3, 2)+(2, 1) ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]]),
row_indices=tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]]),
values=tensor([[[[[ 1.],
[ 2.]],
[[ 2.],
[ 3.]],
[[ 3.],
[ 4.]],
[[ 4.],
[ 5.]]],
[[[ 5.],
[ 6.]],
[[ 6.],
[ 7.]],
[[ 7.],
[ 8.]],
[[ 8.],
[ 9.]]],
[[[ 9.],
[10.]],
[[10.],
[11.]],
[[11.],
[12.]],
[[12.],
[13.]]]],
[[[[13.],
[14.]],
[[14.],
[15.]],
[[15.],
[16.]],
[[16.],
[17.]]],
[[[17.],
[18.]],
[[18.],
[19.]],
[[19.],
[20.]],
[[20.],
[21.]]],
[[[21.],
[22.]],
[[22.],
[23.]],
[[23.],
[24.]],
[[24.],
[25.]]]]]), device='cuda:0', size=(2, 3, 3, 2, 2, 1),
nnz=4, dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]], device='cuda:0', dtype=torch.int32)
# _values
tensor([[[[[ 1.],
[ 2.]],
[[ 2.],
[ 3.]],
[[ 3.],
[ 4.]],
[[ 4.],
[ 5.]]],
[[[ 5.],
[ 6.]],
[[ 6.],
[ 7.]],
[[ 7.],
[ 8.]],
[[ 8.],
[ 9.]]],
[[[ 9.],
[10.]],
[[10.],
[11.]],
[[11.],
[12.]],
[[12.],
[13.]]]],
[[[[13.],
[14.]],
[[14.],
[15.]],
[[15.],
[16.]],
[[16.],
[17.]]],
[[[17.],
[18.]],
[[18.],
[19.]],
[[19.],
[20.]],
[[20.],
[21.]]],
[[[21.],
[22.]],
[[22.],
[23.]],
[[23.],
[24.]],
[[24.],
[25.]]]]], device='cuda:0', dtype=torch.float64)
########## torch.float32/torch.int64/size=()+(3, 2)+(2,) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[1., 2.],
[2., 3.],
[3., 4.],
[4., 5.]]), device='cuda:0', size=(3, 2, 2), nnz=4,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0')
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0')
# _values
tensor([[1., 2.],
[2., 3.],
[3., 4.],
[4., 5.]], device='cuda:0')
########## torch.float32/torch.int64/size=()+(3, 2)+(4, 2) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[ 1., 11.],
[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.],
[ 6., 16.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.],
[ 7., 17.]]]), device='cuda:0', size=(3, 2, 4, 2),
nnz=4, layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0')
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0')
# _values
tensor([[[ 1., 11.],
[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.],
[ 6., 16.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.],
[ 7., 17.]]], device='cuda:0')
########## torch.float32/torch.int64/size=(2, 3)+(3, 2)+(2, 1) ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 3, 4],
[0, 1, 4]],
[[0, 1, 4],
[0, 2, 4],
[0, 3, 4]]]),
row_indices=tensor([[[0, 1, 0, 1],
[0, 1, 2, 0],
[0, 0, 1, 2]],
[[1, 0, 1, 2],
[0, 2, 0, 1],
[0, 1, 2, 1]]]),
values=tensor([[[[[ 1.],
[ 2.]],
[[ 2.],
[ 3.]],
[[ 3.],
[ 4.]],
[[ 4.],
[ 5.]]],
[[[ 5.],
[ 6.]],
[[ 6.],
[ 7.]],
[[ 7.],