blob: 46bdb44b2a983f6eb97279603bed57089d93cf09 [file] [log] [blame]
########## torch.float32/torch.int32/size=()+(3, 4)+() ##########
# 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.]]]), device='cuda:0', size=(3, 4), nnz=4,
layout=torch.sparse_bsc)
# _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.]]], 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, 1, 2)), device='cuda:0', size=(0, 0), nnz=0,
layout=torch.sparse_bsc)
# _ccol_indices
tensor([0], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([], device='cuda:0', dtype=torch.int32)
# _values
tensor([], device='cuda:0', size=(0, 1, 2))
########## torch.float32/torch.int32/size=(2,)+(6, 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.]],
[[2.],
[3.]],
[[3.],
[4.]],
[[4.],
[5.]]],
[[[5.],
[6.]],
[[6.],
[7.]],
[[7.],
[8.]],
[[8.],
[9.]]]]), device='cuda:0', size=(2, 6, 2), nnz=4,
layout=torch.sparse_bsc)
# _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.]],
[[2.],
[3.]],
[[3.],
[4.]],
[[4.],
[5.]]],
[[[5.],
[6.]],
[[6.],
[7.]],
[[7.],
[8.]],
[[8.],
[9.]]]], device='cuda:0')
########## torch.float32/torch.int32/size=(2, 3)+(9, 4)+() ##########
# 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., 11.],
[ 2., 12.],
[ 3., 13.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.]]],
[[[ 5., 15.],
[ 6., 16.],
[ 7., 17.]],
[[ 6., 16.],
[ 7., 17.],
[ 8., 18.]],
[[ 7., 17.],
[ 8., 18.],
[ 9., 19.]],
[[ 8., 18.],
[ 9., 19.],
[10., 20.]]],
[[[ 9., 19.],
[10., 20.],
[11., 21.]],
[[10., 20.],
[11., 21.],
[12., 22.]],
[[11., 21.],
[12., 22.],
[13., 23.]],
[[12., 22.],
[13., 23.],
[14., 24.]]]],
[[[[13., 23.],
[14., 24.],
[15., 25.]],
[[14., 24.],
[15., 25.],
[16., 26.]],
[[15., 25.],
[16., 26.],
[17., 27.]],
[[16., 26.],
[17., 27.],
[18., 28.]]],
[[[17., 27.],
[18., 28.],
[19., 29.]],
[[18., 28.],
[19., 29.],
[20., 30.]],
[[19., 29.],
[20., 30.],
[21., 31.]],
[[20., 30.],
[21., 31.],
[22., 32.]]],
[[[21., 31.],
[22., 32.],
[23., 33.]],
[[22., 32.],
[23., 33.],
[24., 34.]],
[[23., 33.],
[24., 34.],
[25., 35.]],
[[24., 34.],
[25., 35.],
[26., 36.]]]]]), device='cuda:0', size=(2, 3, 9, 4),
nnz=4, layout=torch.sparse_bsc)
# _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., 11.],
[ 2., 12.],
[ 3., 13.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.]]],
[[[ 5., 15.],
[ 6., 16.],
[ 7., 17.]],
[[ 6., 16.],
[ 7., 17.],
[ 8., 18.]],
[[ 7., 17.],
[ 8., 18.],
[ 9., 19.]],
[[ 8., 18.],
[ 9., 19.],
[10., 20.]]],
[[[ 9., 19.],
[10., 20.],
[11., 21.]],
[[10., 20.],
[11., 21.],
[12., 22.]],
[[11., 21.],
[12., 22.],
[13., 23.]],
[[12., 22.],
[13., 23.],
[14., 24.]]]],
[[[[13., 23.],
[14., 24.],
[15., 25.]],
[[14., 24.],
[15., 25.],
[16., 26.]],
[[15., 25.],
[16., 26.],
[17., 27.]],
[[16., 26.],
[17., 27.],
[18., 28.]]],
[[[17., 27.],
[18., 28.],
[19., 29.]],
[[18., 28.],
[19., 29.],
[20., 30.]],
[[19., 29.],
[20., 30.],
[21., 31.]],
[[20., 30.],
[21., 31.],
[22., 32.]]],
[[[21., 31.],
[22., 32.],
[23., 33.]],
[[22., 32.],
[23., 33.],
[24., 34.]],
[[23., 33.],
[24., 34.],
[25., 35.]],
[[24., 34.],
[25., 35.],
[26., 36.]]]]], device='cuda:0')
########## torch.float64/torch.int32/size=()+(3, 4)+() ##########
# 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.]]]), device='cuda:0', size=(3, 4), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsc)
# _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.]]], 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, 1, 2)), device='cuda:0', size=(0, 0), nnz=0,
dtype=torch.float64, layout=torch.sparse_bsc)
# _ccol_indices
tensor([0], device='cuda:0', dtype=torch.int32)
# _row_indices
tensor([], device='cuda:0', dtype=torch.int32)
# _values
tensor([], device='cuda:0', size=(0, 1, 2), dtype=torch.float64)
########## torch.float64/torch.int32/size=(2,)+(6, 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.]],
[[2.],
[3.]],
[[3.],
[4.]],
[[4.],
[5.]]],
[[[5.],
[6.]],
[[6.],
[7.]],
[[7.],
[8.]],
[[8.],
[9.]]]]), device='cuda:0', size=(2, 6, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsc)
# _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.]],
[[2.],
[3.]],
[[3.],
[4.]],
[[4.],
[5.]]],
[[[5.],
[6.]],
[[6.],
[7.]],
[[7.],
[8.]],
[[8.],
[9.]]]], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int32/size=(2, 3)+(9, 4)+() ##########
# 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., 11.],
[ 2., 12.],
[ 3., 13.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.]]],
[[[ 5., 15.],
[ 6., 16.],
[ 7., 17.]],
[[ 6., 16.],
[ 7., 17.],
[ 8., 18.]],
[[ 7., 17.],
[ 8., 18.],
[ 9., 19.]],
[[ 8., 18.],
[ 9., 19.],
[10., 20.]]],
[[[ 9., 19.],
[10., 20.],
[11., 21.]],
[[10., 20.],
[11., 21.],
[12., 22.]],
[[11., 21.],
[12., 22.],
[13., 23.]],
[[12., 22.],
[13., 23.],
[14., 24.]]]],
[[[[13., 23.],
[14., 24.],
[15., 25.]],
[[14., 24.],
[15., 25.],
[16., 26.]],
[[15., 25.],
[16., 26.],
[17., 27.]],
[[16., 26.],
[17., 27.],
[18., 28.]]],
[[[17., 27.],
[18., 28.],
[19., 29.]],
[[18., 28.],
[19., 29.],
[20., 30.]],
[[19., 29.],
[20., 30.],
[21., 31.]],
[[20., 30.],
[21., 31.],
[22., 32.]]],
[[[21., 31.],
[22., 32.],
[23., 33.]],
[[22., 32.],
[23., 33.],
[24., 34.]],
[[23., 33.],
[24., 34.],
[25., 35.]],
[[24., 34.],
[25., 35.],
[26., 36.]]]]]), device='cuda:0', size=(2, 3, 9, 4),
nnz=4, dtype=torch.float64, layout=torch.sparse_bsc)
# _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., 11.],
[ 2., 12.],
[ 3., 13.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.]]],
[[[ 5., 15.],
[ 6., 16.],
[ 7., 17.]],
[[ 6., 16.],
[ 7., 17.],
[ 8., 18.]],
[[ 7., 17.],
[ 8., 18.],
[ 9., 19.]],
[[ 8., 18.],
[ 9., 19.],
[10., 20.]]],
[[[ 9., 19.],
[10., 20.],
[11., 21.]],
[[10., 20.],
[11., 21.],
[12., 22.]],
[[11., 21.],
[12., 22.],
[13., 23.]],
[[12., 22.],
[13., 23.],
[14., 24.]]]],
[[[[13., 23.],
[14., 24.],
[15., 25.]],
[[14., 24.],
[15., 25.],
[16., 26.]],
[[15., 25.],
[16., 26.],
[17., 27.]],
[[16., 26.],
[17., 27.],
[18., 28.]]],
[[[17., 27.],
[18., 28.],
[19., 29.]],
[[18., 28.],
[19., 29.],
[20., 30.]],
[[19., 29.],
[20., 30.],
[21., 31.]],
[[20., 30.],
[21., 31.],
[22., 32.]]],
[[[21., 31.],
[22., 32.],
[23., 33.]],
[[22., 32.],
[23., 33.],
[24., 34.]],
[[23., 33.],
[24., 34.],
[25., 35.]],
[[24., 34.],
[25., 35.],
[26., 36.]]]]], device='cuda:0', dtype=torch.float64)
########## torch.float32/torch.int64/size=()+(3, 4)+() ##########
# 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.]]]), device='cuda:0', size=(3, 4), nnz=4,
layout=torch.sparse_bsc)
# _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.]]], 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, 1, 2)), device='cuda:0', size=(0, 0), nnz=0,
layout=torch.sparse_bsc)
# _ccol_indices
tensor([0], device='cuda:0')
# _row_indices
tensor([], device='cuda:0', dtype=torch.int64)
# _values
tensor([], device='cuda:0', size=(0, 1, 2))
########## torch.float32/torch.int64/size=(2,)+(6, 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.]],
[[2.],
[3.]],
[[3.],
[4.]],
[[4.],
[5.]]],
[[[5.],
[6.]],
[[6.],
[7.]],
[[7.],
[8.]],
[[8.],
[9.]]]]), device='cuda:0', size=(2, 6, 2), nnz=4,
layout=torch.sparse_bsc)
# _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.]],
[[2.],
[3.]],
[[3.],
[4.]],
[[4.],
[5.]]],
[[[5.],
[6.]],
[[6.],
[7.]],
[[7.],
[8.]],
[[8.],
[9.]]]], device='cuda:0')
########## torch.float32/torch.int64/size=(2, 3)+(9, 4)+() ##########
# 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., 11.],
[ 2., 12.],
[ 3., 13.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.]]],
[[[ 5., 15.],
[ 6., 16.],
[ 7., 17.]],
[[ 6., 16.],
[ 7., 17.],
[ 8., 18.]],
[[ 7., 17.],
[ 8., 18.],
[ 9., 19.]],
[[ 8., 18.],
[ 9., 19.],
[10., 20.]]],
[[[ 9., 19.],
[10., 20.],
[11., 21.]],
[[10., 20.],
[11., 21.],
[12., 22.]],
[[11., 21.],
[12., 22.],
[13., 23.]],
[[12., 22.],
[13., 23.],
[14., 24.]]]],
[[[[13., 23.],
[14., 24.],
[15., 25.]],
[[14., 24.],
[15., 25.],
[16., 26.]],
[[15., 25.],
[16., 26.],
[17., 27.]],
[[16., 26.],
[17., 27.],
[18., 28.]]],
[[[17., 27.],
[18., 28.],
[19., 29.]],
[[18., 28.],
[19., 29.],
[20., 30.]],
[[19., 29.],
[20., 30.],
[21., 31.]],
[[20., 30.],
[21., 31.],
[22., 32.]]],
[[[21., 31.],
[22., 32.],
[23., 33.]],
[[22., 32.],
[23., 33.],
[24., 34.]],
[[23., 33.],
[24., 34.],
[25., 35.]],
[[24., 34.],
[25., 35.],
[26., 36.]]]]]), device='cuda:0', size=(2, 3, 9, 4),
nnz=4, layout=torch.sparse_bsc)
# _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., 11.],
[ 2., 12.],
[ 3., 13.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.]]],
[[[ 5., 15.],
[ 6., 16.],
[ 7., 17.]],
[[ 6., 16.],
[ 7., 17.],
[ 8., 18.]],
[[ 7., 17.],
[ 8., 18.],
[ 9., 19.]],
[[ 8., 18.],
[ 9., 19.],
[10., 20.]]],
[[[ 9., 19.],
[10., 20.],
[11., 21.]],
[[10., 20.],
[11., 21.],
[12., 22.]],
[[11., 21.],
[12., 22.],
[13., 23.]],
[[12., 22.],
[13., 23.],
[14., 24.]]]],
[[[[13., 23.],
[14., 24.],
[15., 25.]],
[[14., 24.],
[15., 25.],
[16., 26.]],
[[15., 25.],
[16., 26.],
[17., 27.]],
[[16., 26.],
[17., 27.],
[18., 28.]]],
[[[17., 27.],
[18., 28.],
[19., 29.]],
[[18., 28.],
[19., 29.],
[20., 30.]],
[[19., 29.],
[20., 30.],
[21., 31.]],
[[20., 30.],
[21., 31.],
[22., 32.]]],
[[[21., 31.],
[22., 32.],
[23., 33.]],
[[22., 32.],
[23., 33.],
[24., 34.]],
[[23., 33.],
[24., 34.],
[25., 35.]],
[[24., 34.],
[25., 35.],
[26., 36.]]]]], device='cuda:0')
########## torch.float64/torch.int64/size=()+(3, 4)+() ##########
# 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.]]]), device='cuda:0', size=(3, 4), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsc)
# _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.]]], 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, 1, 2)), device='cuda:0', size=(0, 0), nnz=0,
dtype=torch.float64, layout=torch.sparse_bsc)
# _ccol_indices
tensor([0], device='cuda:0')
# _row_indices
tensor([], device='cuda:0', dtype=torch.int64)
# _values
tensor([], device='cuda:0', size=(0, 1, 2), dtype=torch.float64)
########## torch.float64/torch.int64/size=(2,)+(6, 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.]],
[[2.],
[3.]],
[[3.],
[4.]],
[[4.],
[5.]]],
[[[5.],
[6.]],
[[6.],
[7.]],
[[7.],
[8.]],
[[8.],
[9.]]]]), device='cuda:0', size=(2, 6, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsc)
# _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.]],
[[2.],
[3.]],
[[3.],
[4.]],
[[4.],
[5.]]],
[[[5.],
[6.]],
[[6.],
[7.]],
[[7.],
[8.]],
[[8.],
[9.]]]], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int64/size=(2, 3)+(9, 4)+() ##########
# 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., 11.],
[ 2., 12.],
[ 3., 13.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.]]],
[[[ 5., 15.],
[ 6., 16.],
[ 7., 17.]],
[[ 6., 16.],
[ 7., 17.],
[ 8., 18.]],
[[ 7., 17.],
[ 8., 18.],
[ 9., 19.]],
[[ 8., 18.],
[ 9., 19.],
[10., 20.]]],
[[[ 9., 19.],
[10., 20.],
[11., 21.]],
[[10., 20.],
[11., 21.],
[12., 22.]],
[[11., 21.],
[12., 22.],
[13., 23.]],
[[12., 22.],
[13., 23.],
[14., 24.]]]],
[[[[13., 23.],
[14., 24.],
[15., 25.]],
[[14., 24.],
[15., 25.],
[16., 26.]],
[[15., 25.],
[16., 26.],
[17., 27.]],
[[16., 26.],
[17., 27.],
[18., 28.]]],
[[[17., 27.],
[18., 28.],
[19., 29.]],
[[18., 28.],
[19., 29.],
[20., 30.]],
[[19., 29.],
[20., 30.],
[21., 31.]],
[[20., 30.],
[21., 31.],
[22., 32.]]],
[[[21., 31.],
[22., 32.],
[23., 33.]],
[[22., 32.],
[23., 33.],
[24., 34.]],
[[23., 33.],
[24., 34.],
[25., 35.]],
[[24., 34.],
[25., 35.],
[26., 36.]]]]]), device='cuda:0', size=(2, 3, 9, 4),
nnz=4, dtype=torch.float64, layout=torch.sparse_bsc)
# _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., 11.],
[ 2., 12.],
[ 3., 13.]],
[[ 2., 12.],
[ 3., 13.],
[ 4., 14.]],
[[ 3., 13.],
[ 4., 14.],
[ 5., 15.]],
[[ 4., 14.],
[ 5., 15.],
[ 6., 16.]]],
[[[ 5., 15.],
[ 6., 16.],
[ 7., 17.]],
[[ 6., 16.],
[ 7., 17.],
[ 8., 18.]],
[[ 7., 17.],
[ 8., 18.],
[ 9., 19.]],
[[ 8., 18.],
[ 9., 19.],
[10., 20.]]],
[[[ 9., 19.],
[10., 20.],
[11., 21.]],
[[10., 20.],
[11., 21.],
[12., 22.]],
[[11., 21.],
[12., 22.],
[13., 23.]],
[[12., 22.],
[13., 23.],
[14., 24.]]]],
[[[[13., 23.],
[14., 24.],
[15., 25.]],
[[14., 24.],
[15., 25.],
[16., 26.]],
[[15., 25.],
[16., 26.],
[17., 27.]],
[[16., 26.],
[17., 27.],
[18., 28.]]],
[[[17., 27.],
[18., 28.],
[19., 29.]],
[[18., 28.],
[19., 29.],
[20., 30.]],
[[19., 29.],
[20., 30.],
[21., 31.]],
[[20., 30.],
[21., 31.],
[22., 32.]]],
[[[21., 31.],
[22., 32.],
[23., 33.]],
[[22., 32.],
[23., 33.],
[24., 34.]],
[[23., 33.],
[24., 34.],
[25., 35.]],
[[24., 34.],
[25., 35.],
[26., 36.]]]]], device='cuda:0', dtype=torch.float64)
########## torch.float32/torch.int32/size=()+(6, 6)+(2,) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[[ 1., 101.],
[ 11., 111.],
[ 21., 121.]],
[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]]],
[[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]],
[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]]],
[[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]],
[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]]],
[[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]],
[[ 5., 105.],
[ 15., 115.],
[ 25., 125.]]]]), device='cuda:0', size=(6, 6, 2),
nnz=4, layout=torch.sparse_bsc)
# _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., 101.],
[ 11., 111.],
[ 21., 121.]],
[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]]],
[[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]],
[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]]],
[[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]],
[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]]],
[[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]],
[[ 5., 105.],
[ 15., 115.],
[ 25., 125.]]]], device='cuda:0')
########## torch.float32/torch.int32/size=()+(9, 4)+(4, 2) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[[[1.0000e+00, 1.0010e+03],
[1.0100e+02, 1.1010e+03],
[2.0100e+02, 1.2010e+03],
[3.0100e+02, 1.3010e+03]],
[[1.1000e+01, 1.0110e+03],
[1.1100e+02, 1.1110e+03],
[2.1100e+02, 1.2110e+03],
[3.1100e+02, 1.3110e+03]]],
[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]]],
[[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]]],
[[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]]],
[[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]],
[[[6.0000e+00, 1.0060e+03],
[1.0600e+02, 1.1060e+03],
[2.0600e+02, 1.2060e+03],
[3.0600e+02, 1.3060e+03]],
[[1.6000e+01, 1.0160e+03],
[1.1600e+02, 1.1160e+03],
[2.1600e+02, 1.2160e+03],
[3.1600e+02, 1.3160e+03]]]]]), device='cuda:0',
size=(9, 4, 4, 2), nnz=4, layout=torch.sparse_bsc)
# _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([[[[[1.0000e+00, 1.0010e+03],
[1.0100e+02, 1.1010e+03],
[2.0100e+02, 1.2010e+03],
[3.0100e+02, 1.3010e+03]],
[[1.1000e+01, 1.0110e+03],
[1.1100e+02, 1.1110e+03],
[2.1100e+02, 1.2110e+03],
[3.1100e+02, 1.3110e+03]]],
[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]]],
[[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]]],
[[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]]],
[[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]],
[[[6.0000e+00, 1.0060e+03],
[1.0600e+02, 1.1060e+03],
[2.0600e+02, 1.2060e+03],
[3.0600e+02, 1.3060e+03]],
[[1.6000e+01, 1.0160e+03],
[1.1600e+02, 1.1160e+03],
[2.1600e+02, 1.2160e+03],
[3.1600e+02, 1.3160e+03]]]]], device='cuda:0')
########## torch.float32/torch.int32/size=(2, 3)+(6, 6)+(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.],
[101.]],
[[ 11.],
[111.]],
[[ 21.],
[121.]]],
[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]]],
[[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]],
[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]]],
[[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]],
[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]]],
[[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]],
[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]]]],
[[[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]],
[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]]],
[[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]],
[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]]],
[[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]],
[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]]],
[[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]],
[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]]]],
[[[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]],
[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]]],
[[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]],
[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]]],
[[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]],
[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]]],
[[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]],
[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]]]]],
[[[[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]],
[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]]],
[[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]],
[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]]],
[[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]],
[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]]],
[[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]],
[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]]]],
[[[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]],
[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]]],
[[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]],
[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]]],
[[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]],
[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]]],
[[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]],
[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]]]],
[[[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]],
[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]]],
[[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]],
[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]]],
[[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]],
[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]]],
[[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]],
[[[ 25.],
[125.]],
[[ 35.],
[135.]],
[[ 45.],
[145.]]]]]]]), device='cuda:0',
size=(2, 3, 6, 6, 2, 1), nnz=4, layout=torch.sparse_bsc)
# _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.],
[101.]],
[[ 11.],
[111.]],
[[ 21.],
[121.]]],
[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]]],
[[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]],
[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]]],
[[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]],
[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]]],
[[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]],
[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]]]],
[[[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]],
[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]]],
[[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]],
[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]]],
[[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]],
[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]]],
[[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]],
[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]]]],
[[[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]],
[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]]],
[[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]],
[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]]],
[[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]],
[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]]],
[[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]],
[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]]]]],
[[[[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]],
[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]]],
[[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]],
[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]]],
[[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]],
[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]]],
[[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]],
[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]]]],
[[[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]],
[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]]],
[[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]],
[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]]],
[[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]],
[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]]],
[[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]],
[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]]]],
[[[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]],
[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]]],
[[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]],
[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]]],
[[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]],
[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]]],
[[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]],
[[[ 25.],
[125.]],
[[ 35.],
[135.]],
[[ 45.],
[145.]]]]]]], device='cuda:0')
########## torch.float64/torch.int32/size=()+(6, 6)+(2,) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[[ 1., 101.],
[ 11., 111.],
[ 21., 121.]],
[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]]],
[[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]],
[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]]],
[[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]],
[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]]],
[[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]],
[[ 5., 105.],
[ 15., 115.],
[ 25., 125.]]]]), device='cuda:0', size=(6, 6, 2),
nnz=4, dtype=torch.float64, layout=torch.sparse_bsc)
# _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., 101.],
[ 11., 111.],
[ 21., 121.]],
[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]]],
[[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]],
[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]]],
[[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]],
[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]]],
[[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]],
[[ 5., 105.],
[ 15., 115.],
[ 25., 125.]]]], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int32/size=()+(9, 4)+(4, 2) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[[[1.0000e+00, 1.0010e+03],
[1.0100e+02, 1.1010e+03],
[2.0100e+02, 1.2010e+03],
[3.0100e+02, 1.3010e+03]],
[[1.1000e+01, 1.0110e+03],
[1.1100e+02, 1.1110e+03],
[2.1100e+02, 1.2110e+03],
[3.1100e+02, 1.3110e+03]]],
[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]]],
[[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]]],
[[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]]],
[[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]],
[[[6.0000e+00, 1.0060e+03],
[1.0600e+02, 1.1060e+03],
[2.0600e+02, 1.2060e+03],
[3.0600e+02, 1.3060e+03]],
[[1.6000e+01, 1.0160e+03],
[1.1600e+02, 1.1160e+03],
[2.1600e+02, 1.2160e+03],
[3.1600e+02, 1.3160e+03]]]]]), device='cuda:0',
size=(9, 4, 4, 2), nnz=4, dtype=torch.float64, layout=torch.sparse_bsc)
# _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([[[[[1.0000e+00, 1.0010e+03],
[1.0100e+02, 1.1010e+03],
[2.0100e+02, 1.2010e+03],
[3.0100e+02, 1.3010e+03]],
[[1.1000e+01, 1.0110e+03],
[1.1100e+02, 1.1110e+03],
[2.1100e+02, 1.2110e+03],
[3.1100e+02, 1.3110e+03]]],
[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]]],
[[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]]],
[[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]]],
[[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]],
[[[6.0000e+00, 1.0060e+03],
[1.0600e+02, 1.1060e+03],
[2.0600e+02, 1.2060e+03],
[3.0600e+02, 1.3060e+03]],
[[1.6000e+01, 1.0160e+03],
[1.1600e+02, 1.1160e+03],
[2.1600e+02, 1.2160e+03],
[3.1600e+02, 1.3160e+03]]]]], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int32/size=(2, 3)+(6, 6)+(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.],
[101.]],
[[ 11.],
[111.]],
[[ 21.],
[121.]]],
[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]]],
[[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]],
[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]]],
[[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]],
[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]]],
[[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]],
[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]]]],
[[[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]],
[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]]],
[[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]],
[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]]],
[[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]],
[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]]],
[[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]],
[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]]]],
[[[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]],
[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]]],
[[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]],
[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]]],
[[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]],
[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]]],
[[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]],
[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]]]]],
[[[[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]],
[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]]],
[[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]],
[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]]],
[[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]],
[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]]],
[[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]],
[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]]]],
[[[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]],
[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]]],
[[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]],
[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]]],
[[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]],
[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]]],
[[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]],
[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]]]],
[[[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]],
[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]]],
[[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]],
[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]]],
[[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]],
[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]]],
[[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]],
[[[ 25.],
[125.]],
[[ 35.],
[135.]],
[[ 45.],
[145.]]]]]]]), device='cuda:0',
size=(2, 3, 6, 6, 2, 1), nnz=4, dtype=torch.float64,
layout=torch.sparse_bsc)
# _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.],
[101.]],
[[ 11.],
[111.]],
[[ 21.],
[121.]]],
[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]]],
[[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]],
[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]]],
[[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]],
[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]]],
[[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]],
[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]]]],
[[[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]],
[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]]],
[[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]],
[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]]],
[[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]],
[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]]],
[[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]],
[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]]]],
[[[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]],
[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]]],
[[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]],
[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]]],
[[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]],
[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]]],
[[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]],
[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]]]]],
[[[[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]],
[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]]],
[[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]],
[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]]],
[[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]],
[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]]],
[[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]],
[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]]]],
[[[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]],
[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]]],
[[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]],
[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]]],
[[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]],
[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]]],
[[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]],
[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]]]],
[[[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]],
[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]]],
[[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]],
[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]]],
[[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]],
[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]]],
[[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]],
[[[ 25.],
[125.]],
[[ 35.],
[135.]],
[[ 45.],
[145.]]]]]]], device='cuda:0', dtype=torch.float64)
########## torch.float32/torch.int64/size=()+(6, 6)+(2,) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[[ 1., 101.],
[ 11., 111.],
[ 21., 121.]],
[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]]],
[[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]],
[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]]],
[[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]],
[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]]],
[[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]],
[[ 5., 105.],
[ 15., 115.],
[ 25., 125.]]]]), device='cuda:0', size=(6, 6, 2),
nnz=4, layout=torch.sparse_bsc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0')
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0')
# _values
tensor([[[[ 1., 101.],
[ 11., 111.],
[ 21., 121.]],
[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]]],
[[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]],
[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]]],
[[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]],
[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]]],
[[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]],
[[ 5., 105.],
[ 15., 115.],
[ 25., 125.]]]], device='cuda:0')
########## torch.float32/torch.int64/size=()+(9, 4)+(4, 2) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[[[1.0000e+00, 1.0010e+03],
[1.0100e+02, 1.1010e+03],
[2.0100e+02, 1.2010e+03],
[3.0100e+02, 1.3010e+03]],
[[1.1000e+01, 1.0110e+03],
[1.1100e+02, 1.1110e+03],
[2.1100e+02, 1.2110e+03],
[3.1100e+02, 1.3110e+03]]],
[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]]],
[[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]]],
[[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]]],
[[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]],
[[[6.0000e+00, 1.0060e+03],
[1.0600e+02, 1.1060e+03],
[2.0600e+02, 1.2060e+03],
[3.0600e+02, 1.3060e+03]],
[[1.6000e+01, 1.0160e+03],
[1.1600e+02, 1.1160e+03],
[2.1600e+02, 1.2160e+03],
[3.1600e+02, 1.3160e+03]]]]]), device='cuda:0',
size=(9, 4, 4, 2), nnz=4, layout=torch.sparse_bsc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0')
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0')
# _values
tensor([[[[[1.0000e+00, 1.0010e+03],
[1.0100e+02, 1.1010e+03],
[2.0100e+02, 1.2010e+03],
[3.0100e+02, 1.3010e+03]],
[[1.1000e+01, 1.0110e+03],
[1.1100e+02, 1.1110e+03],
[2.1100e+02, 1.2110e+03],
[3.1100e+02, 1.3110e+03]]],
[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]]],
[[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]]],
[[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]]],
[[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]],
[[[6.0000e+00, 1.0060e+03],
[1.0600e+02, 1.1060e+03],
[2.0600e+02, 1.2060e+03],
[3.0600e+02, 1.3060e+03]],
[[1.6000e+01, 1.0160e+03],
[1.1600e+02, 1.1160e+03],
[2.1600e+02, 1.2160e+03],
[3.1600e+02, 1.3160e+03]]]]], device='cuda:0')
########## torch.float32/torch.int64/size=(2, 3)+(6, 6)+(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.],
[101.]],
[[ 11.],
[111.]],
[[ 21.],
[121.]]],
[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]]],
[[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]],
[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]]],
[[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]],
[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]]],
[[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]],
[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]]]],
[[[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]],
[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]]],
[[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]],
[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]]],
[[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]],
[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]]],
[[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]],
[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]]]],
[[[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]],
[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]]],
[[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]],
[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]]],
[[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]],
[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]]],
[[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]],
[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]]]]],
[[[[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]],
[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]]],
[[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]],
[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]]],
[[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]],
[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]]],
[[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]],
[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]]]],
[[[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]],
[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]]],
[[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]],
[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]]],
[[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]],
[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]]],
[[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]],
[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]]]],
[[[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]],
[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]]],
[[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]],
[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]]],
[[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]],
[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]]],
[[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]],
[[[ 25.],
[125.]],
[[ 35.],
[135.]],
[[ 45.],
[145.]]]]]]]), device='cuda:0',
size=(2, 3, 6, 6, 2, 1), nnz=4, layout=torch.sparse_bsc)
# _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.],
[101.]],
[[ 11.],
[111.]],
[[ 21.],
[121.]]],
[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]]],
[[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]],
[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]]],
[[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]],
[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]]],
[[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]],
[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]]]],
[[[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]],
[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]]],
[[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]],
[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]]],
[[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]],
[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]]],
[[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]],
[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]]]],
[[[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]],
[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]]],
[[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]],
[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]]],
[[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]],
[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]]],
[[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]],
[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]]]]],
[[[[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]],
[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]]],
[[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]],
[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]]],
[[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]],
[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]]],
[[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]],
[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]]]],
[[[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]],
[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]]],
[[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]],
[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]]],
[[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]],
[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]]],
[[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]],
[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]]]],
[[[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]],
[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]]],
[[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]],
[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]]],
[[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]],
[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]]],
[[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]],
[[[ 25.],
[125.]],
[[ 35.],
[135.]],
[[ 45.],
[145.]]]]]]], device='cuda:0')
########## torch.float64/torch.int64/size=()+(6, 6)+(2,) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[[ 1., 101.],
[ 11., 111.],
[ 21., 121.]],
[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]]],
[[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]],
[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]]],
[[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]],
[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]]],
[[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]],
[[ 5., 105.],
[ 15., 115.],
[ 25., 125.]]]]), device='cuda:0', size=(6, 6, 2),
nnz=4, dtype=torch.float64, layout=torch.sparse_bsc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0')
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0')
# _values
tensor([[[[ 1., 101.],
[ 11., 111.],
[ 21., 121.]],
[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]]],
[[[ 2., 102.],
[ 12., 112.],
[ 22., 122.]],
[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]]],
[[[ 3., 103.],
[ 13., 113.],
[ 23., 123.]],
[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]]],
[[[ 4., 104.],
[ 14., 114.],
[ 24., 124.]],
[[ 5., 105.],
[ 15., 115.],
[ 25., 125.]]]], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int64/size=()+(9, 4)+(4, 2) ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 2]),
values=tensor([[[[[1.0000e+00, 1.0010e+03],
[1.0100e+02, 1.1010e+03],
[2.0100e+02, 1.2010e+03],
[3.0100e+02, 1.3010e+03]],
[[1.1000e+01, 1.0110e+03],
[1.1100e+02, 1.1110e+03],
[2.1100e+02, 1.2110e+03],
[3.1100e+02, 1.3110e+03]]],
[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]]],
[[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]]],
[[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]]],
[[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]],
[[[6.0000e+00, 1.0060e+03],
[1.0600e+02, 1.1060e+03],
[2.0600e+02, 1.2060e+03],
[3.0600e+02, 1.3060e+03]],
[[1.6000e+01, 1.0160e+03],
[1.1600e+02, 1.1160e+03],
[2.1600e+02, 1.2160e+03],
[3.1600e+02, 1.3160e+03]]]]]), device='cuda:0',
size=(9, 4, 4, 2), nnz=4, dtype=torch.float64, layout=torch.sparse_bsc)
# _ccol_indices
tensor([0, 2, 4], device='cuda:0')
# _row_indices
tensor([0, 1, 0, 2], device='cuda:0')
# _values
tensor([[[[[1.0000e+00, 1.0010e+03],
[1.0100e+02, 1.1010e+03],
[2.0100e+02, 1.2010e+03],
[3.0100e+02, 1.3010e+03]],
[[1.1000e+01, 1.0110e+03],
[1.1100e+02, 1.1110e+03],
[2.1100e+02, 1.2110e+03],
[3.1100e+02, 1.3110e+03]]],
[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]]],
[[[[2.0000e+00, 1.0020e+03],
[1.0200e+02, 1.1020e+03],
[2.0200e+02, 1.2020e+03],
[3.0200e+02, 1.3020e+03]],
[[1.2000e+01, 1.0120e+03],
[1.1200e+02, 1.1120e+03],
[2.1200e+02, 1.2120e+03],
[3.1200e+02, 1.3120e+03]]],
[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]]],
[[[[3.0000e+00, 1.0030e+03],
[1.0300e+02, 1.1030e+03],
[2.0300e+02, 1.2030e+03],
[3.0300e+02, 1.3030e+03]],
[[1.3000e+01, 1.0130e+03],
[1.1300e+02, 1.1130e+03],
[2.1300e+02, 1.2130e+03],
[3.1300e+02, 1.3130e+03]]],
[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]]],
[[[[4.0000e+00, 1.0040e+03],
[1.0400e+02, 1.1040e+03],
[2.0400e+02, 1.2040e+03],
[3.0400e+02, 1.3040e+03]],
[[1.4000e+01, 1.0140e+03],
[1.1400e+02, 1.1140e+03],
[2.1400e+02, 1.2140e+03],
[3.1400e+02, 1.3140e+03]]],
[[[5.0000e+00, 1.0050e+03],
[1.0500e+02, 1.1050e+03],
[2.0500e+02, 1.2050e+03],
[3.0500e+02, 1.3050e+03]],
[[1.5000e+01, 1.0150e+03],
[1.1500e+02, 1.1150e+03],
[2.1500e+02, 1.2150e+03],
[3.1500e+02, 1.3150e+03]]],
[[[6.0000e+00, 1.0060e+03],
[1.0600e+02, 1.1060e+03],
[2.0600e+02, 1.2060e+03],
[3.0600e+02, 1.3060e+03]],
[[1.6000e+01, 1.0160e+03],
[1.1600e+02, 1.1160e+03],
[2.1600e+02, 1.2160e+03],
[3.1600e+02, 1.3160e+03]]]]], device='cuda:0', dtype=torch.float64)
########## torch.float64/torch.int64/size=(2, 3)+(6, 6)+(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.],
[101.]],
[[ 11.],
[111.]],
[[ 21.],
[121.]]],
[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]]],
[[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]],
[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]]],
[[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]],
[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]]],
[[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]],
[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]]]],
[[[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]],
[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]]],
[[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]],
[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]]],
[[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]],
[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]]],
[[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]],
[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]]]],
[[[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]],
[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]]],
[[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]],
[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]]],
[[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]],
[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]]],
[[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]],
[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]]]]],
[[[[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]],
[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]]],
[[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]],
[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]]],
[[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]],
[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]]],
[[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]],
[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]]]],
[[[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]],
[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]]],
[[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]],
[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]]],
[[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]],
[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]]],
[[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]],
[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]]]],
[[[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]],
[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]]],
[[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]],
[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]]],
[[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]],
[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]]],
[[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]],
[[[ 25.],
[125.]],
[[ 35.],
[135.]],
[[ 45.],
[145.]]]]]]]), device='cuda:0',
size=(2, 3, 6, 6, 2, 1), nnz=4, dtype=torch.float64,
layout=torch.sparse_bsc)
# _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.],
[101.]],
[[ 11.],
[111.]],
[[ 21.],
[121.]]],
[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]]],
[[[[ 2.],
[102.]],
[[ 12.],
[112.]],
[[ 22.],
[122.]]],
[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]]],
[[[[ 3.],
[103.]],
[[ 13.],
[113.]],
[[ 23.],
[123.]]],
[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]]],
[[[[ 4.],
[104.]],
[[ 14.],
[114.]],
[[ 24.],
[124.]]],
[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]]]],
[[[[[ 5.],
[105.]],
[[ 15.],
[115.]],
[[ 25.],
[125.]]],
[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]]],
[[[[ 6.],
[106.]],
[[ 16.],
[116.]],
[[ 26.],
[126.]]],
[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]]],
[[[[ 7.],
[107.]],
[[ 17.],
[117.]],
[[ 27.],
[127.]]],
[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]]],
[[[[ 8.],
[108.]],
[[ 18.],
[118.]],
[[ 28.],
[128.]]],
[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]]]],
[[[[[ 9.],
[109.]],
[[ 19.],
[119.]],
[[ 29.],
[129.]]],
[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]]],
[[[[ 10.],
[110.]],
[[ 20.],
[120.]],
[[ 30.],
[130.]]],
[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]]],
[[[[ 11.],
[111.]],
[[ 21.],
[121.]],
[[ 31.],
[131.]]],
[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]]],
[[[[ 12.],
[112.]],
[[ 22.],
[122.]],
[[ 32.],
[132.]]],
[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]]]]],
[[[[[[ 13.],
[113.]],
[[ 23.],
[123.]],
[[ 33.],
[133.]]],
[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]]],
[[[[ 14.],
[114.]],
[[ 24.],
[124.]],
[[ 34.],
[134.]]],
[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]]],
[[[[ 15.],
[115.]],
[[ 25.],
[125.]],
[[ 35.],
[135.]]],
[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]]],
[[[[ 16.],
[116.]],
[[ 26.],
[126.]],
[[ 36.],
[136.]]],
[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]]]],
[[[[[ 17.],
[117.]],
[[ 27.],
[127.]],
[[ 37.],
[137.]]],
[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]]],
[[[[ 18.],
[118.]],
[[ 28.],
[128.]],
[[ 38.],
[138.]]],
[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]]],
[[[[ 19.],
[119.]],
[[ 29.],
[129.]],
[[ 39.],
[139.]]],
[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]]],
[[[[ 20.],
[120.]],
[[ 30.],
[130.]],
[[ 40.],
[140.]]],
[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]]]],
[[[[[ 21.],
[121.]],
[[ 31.],
[131.]],
[[ 41.],
[141.]]],
[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]]],
[[[[ 22.],
[122.]],
[[ 32.],
[132.]],
[[ 42.],
[142.]]],
[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]]],
[[[[ 23.],
[123.]],
[[ 33.],
[133.]],
[[ 43.],
[143.]]],
[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]]],
[[[[ 24.],
[124.]],
[[ 34.],
[134.]],
[[ 44.],
[144.]]],
[[[ 25.],
[125.]],
[[ 35.],
[135.]],
[[ 45.],
[145.]]]]]]], device='cuda:0', dtype=torch.float64)