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TestSparseCompressedCPU.test_print_SparseBSR_cpu.expect
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3583 lines (2352 loc) · 72.7 KB
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########## torch.float32/torch.int32/size=(2, 3)+(2, 3)+() ##########
# sparse tensor
tensor(crow_indices=tensor([[[0, 3],
[0, 3],
[0, 3]],
[[0, 3],
[0, 3],
[0, 3]]]),
col_indices=tensor([[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]]]),
values=tensor([[[[[1.],
[3.]],
[[2.],
[0.]],
[[0.],
[4.]]],
[[[1.],
[4.]],
[[2.],
[0.]],
[[3.],
[0.]]],
[[[1.],
[2.]],
[[0.],
[3.]],
[[0.],
[4.]]]],
[[[[0.],
[2.]],
[[1.],
[3.]],
[[0.],
[4.]]],
[[[1.],
[3.]],
[[0.],
[4.]],
[[2.],
[0.]]],
[[[1.],
[0.]],
[[2.],
[4.]],
[[3.],
[0.]]]]]), size=(2, 3, 2, 3), nnz=3,
layout=torch.sparse_bsr)
# _crow_indices
tensor([[[0, 3],
[0, 3],
[0, 3]],
[[0, 3],
[0, 3],
[0, 3]]], dtype=torch.int32)
# _col_indices
tensor([[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]]], dtype=torch.int32)
# _values
tensor([[[[[1.],
[3.]],
[[2.],
[0.]],
[[0.],
[4.]]],
[[[1.],
[4.]],
[[2.],
[0.]],
[[3.],
[0.]]],
[[[1.],
[2.]],
[[0.],
[3.]],
[[0.],
[4.]]]],
[[[[0.],
[2.]],
[[1.],
[3.]],
[[0.],
[4.]]],
[[[1.],
[3.]],
[[0.],
[4.]],
[[2.],
[0.]]],
[[[1.],
[0.]],
[[2.],
[4.]],
[[3.],
[0.]]]]])
########## torch.float32/torch.int32/size=()+(8, 6)+() ##########
# sparse tensor
tensor(crow_indices=tensor([0, 2, 3, 5, 7]),
col_indices=tensor([0, 1, 0, 0, 1, 0, 1]),
values=tensor([[[ 0., 1., 0.],
[ 0., 4., 0.]],
[[ 2., 0., 3.],
[ 0., 5., 0.]],
[[ 6., 7., 8.],
[ 0., 0., 0.]],
[[ 0., 9., 0.],
[13., 0., 14.]],
[[10., 11., 12.],
[15., 16., 17.]],
[[ 0., 0., 0.],
[20., 21., 22.]],
[[ 0., 18., 19.],
[ 0., 23., 24.]]]), size=(8, 6), nnz=7,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 3, 5, 7], dtype=torch.int32)
# _col_indices
tensor([0, 1, 0, 0, 1, 0, 1], dtype=torch.int32)
# _values
tensor([[[ 0., 1., 0.],
[ 0., 4., 0.]],
[[ 2., 0., 3.],
[ 0., 5., 0.]],
[[ 6., 7., 8.],
[ 0., 0., 0.]],
[[ 0., 9., 0.],
[13., 0., 14.]],
[[10., 11., 12.],
[15., 16., 17.]],
[[ 0., 0., 0.],
[20., 21., 22.]],
[[ 0., 18., 19.],
[ 0., 23., 24.]]])
########## torch.float64/torch.int32/size=(2, 3)+(2, 3)+() ##########
# sparse tensor
tensor(crow_indices=tensor([[[0, 3],
[0, 3],
[0, 3]],
[[0, 3],
[0, 3],
[0, 3]]]),
col_indices=tensor([[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]]]),
values=tensor([[[[[1.],
[3.]],
[[2.],
[0.]],
[[0.],
[4.]]],
[[[1.],
[4.]],
[[2.],
[0.]],
[[3.],
[0.]]],
[[[1.],
[2.]],
[[0.],
[3.]],
[[0.],
[4.]]]],
[[[[0.],
[2.]],
[[1.],
[3.]],
[[0.],
[4.]]],
[[[1.],
[3.]],
[[0.],
[4.]],
[[2.],
[0.]]],
[[[1.],
[0.]],
[[2.],
[4.]],
[[3.],
[0.]]]]]), size=(2, 3, 2, 3), nnz=3,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([[[0, 3],
[0, 3],
[0, 3]],
[[0, 3],
[0, 3],
[0, 3]]], dtype=torch.int32)
# _col_indices
tensor([[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]]], dtype=torch.int32)
# _values
tensor([[[[[1.],
[3.]],
[[2.],
[0.]],
[[0.],
[4.]]],
[[[1.],
[4.]],
[[2.],
[0.]],
[[3.],
[0.]]],
[[[1.],
[2.]],
[[0.],
[3.]],
[[0.],
[4.]]]],
[[[[0.],
[2.]],
[[1.],
[3.]],
[[0.],
[4.]]],
[[[1.],
[3.]],
[[0.],
[4.]],
[[2.],
[0.]]],
[[[1.],
[0.]],
[[2.],
[4.]],
[[3.],
[0.]]]]], dtype=torch.float64)
########## torch.float64/torch.int32/size=()+(8, 6)+() ##########
# sparse tensor
tensor(crow_indices=tensor([0, 2, 3, 5, 7]),
col_indices=tensor([0, 1, 0, 0, 1, 0, 1]),
values=tensor([[[ 0., 1., 0.],
[ 0., 4., 0.]],
[[ 2., 0., 3.],
[ 0., 5., 0.]],
[[ 6., 7., 8.],
[ 0., 0., 0.]],
[[ 0., 9., 0.],
[13., 0., 14.]],
[[10., 11., 12.],
[15., 16., 17.]],
[[ 0., 0., 0.],
[20., 21., 22.]],
[[ 0., 18., 19.],
[ 0., 23., 24.]]]), size=(8, 6), nnz=7,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 3, 5, 7], dtype=torch.int32)
# _col_indices
tensor([0, 1, 0, 0, 1, 0, 1], dtype=torch.int32)
# _values
tensor([[[ 0., 1., 0.],
[ 0., 4., 0.]],
[[ 2., 0., 3.],
[ 0., 5., 0.]],
[[ 6., 7., 8.],
[ 0., 0., 0.]],
[[ 0., 9., 0.],
[13., 0., 14.]],
[[10., 11., 12.],
[15., 16., 17.]],
[[ 0., 0., 0.],
[20., 21., 22.]],
[[ 0., 18., 19.],
[ 0., 23., 24.]]], dtype=torch.float64)
########## torch.float32/torch.int64/size=(2, 3)+(2, 3)+() ##########
# sparse tensor
tensor(crow_indices=tensor([[[0, 3],
[0, 3],
[0, 3]],
[[0, 3],
[0, 3],
[0, 3]]]),
col_indices=tensor([[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]]]),
values=tensor([[[[[1.],
[3.]],
[[2.],
[0.]],
[[0.],
[4.]]],
[[[1.],
[4.]],
[[2.],
[0.]],
[[3.],
[0.]]],
[[[1.],
[2.]],
[[0.],
[3.]],
[[0.],
[4.]]]],
[[[[0.],
[2.]],
[[1.],
[3.]],
[[0.],
[4.]]],
[[[1.],
[3.]],
[[0.],
[4.]],
[[2.],
[0.]]],
[[[1.],
[0.]],
[[2.],
[4.]],
[[3.],
[0.]]]]]), size=(2, 3, 2, 3), nnz=3,
layout=torch.sparse_bsr)
# _crow_indices
tensor([[[0, 3],
[0, 3],
[0, 3]],
[[0, 3],
[0, 3],
[0, 3]]])
# _col_indices
tensor([[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]]])
# _values
tensor([[[[[1.],
[3.]],
[[2.],
[0.]],
[[0.],
[4.]]],
[[[1.],
[4.]],
[[2.],
[0.]],
[[3.],
[0.]]],
[[[1.],
[2.]],
[[0.],
[3.]],
[[0.],
[4.]]]],
[[[[0.],
[2.]],
[[1.],
[3.]],
[[0.],
[4.]]],
[[[1.],
[3.]],
[[0.],
[4.]],
[[2.],
[0.]]],
[[[1.],
[0.]],
[[2.],
[4.]],
[[3.],
[0.]]]]])
########## torch.float32/torch.int64/size=()+(8, 6)+() ##########
# sparse tensor
tensor(crow_indices=tensor([0, 2, 3, 5, 7]),
col_indices=tensor([0, 1, 0, 0, 1, 0, 1]),
values=tensor([[[ 0., 1., 0.],
[ 0., 4., 0.]],
[[ 2., 0., 3.],
[ 0., 5., 0.]],
[[ 6., 7., 8.],
[ 0., 0., 0.]],
[[ 0., 9., 0.],
[13., 0., 14.]],
[[10., 11., 12.],
[15., 16., 17.]],
[[ 0., 0., 0.],
[20., 21., 22.]],
[[ 0., 18., 19.],
[ 0., 23., 24.]]]), size=(8, 6), nnz=7,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 3, 5, 7])
# _col_indices
tensor([0, 1, 0, 0, 1, 0, 1])
# _values
tensor([[[ 0., 1., 0.],
[ 0., 4., 0.]],
[[ 2., 0., 3.],
[ 0., 5., 0.]],
[[ 6., 7., 8.],
[ 0., 0., 0.]],
[[ 0., 9., 0.],
[13., 0., 14.]],
[[10., 11., 12.],
[15., 16., 17.]],
[[ 0., 0., 0.],
[20., 21., 22.]],
[[ 0., 18., 19.],
[ 0., 23., 24.]]])
########## torch.float64/torch.int64/size=(2, 3)+(2, 3)+() ##########
# sparse tensor
tensor(crow_indices=tensor([[[0, 3],
[0, 3],
[0, 3]],
[[0, 3],
[0, 3],
[0, 3]]]),
col_indices=tensor([[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]]]),
values=tensor([[[[[1.],
[3.]],
[[2.],
[0.]],
[[0.],
[4.]]],
[[[1.],
[4.]],
[[2.],
[0.]],
[[3.],
[0.]]],
[[[1.],
[2.]],
[[0.],
[3.]],
[[0.],
[4.]]]],
[[[[0.],
[2.]],
[[1.],
[3.]],
[[0.],
[4.]]],
[[[1.],
[3.]],
[[0.],
[4.]],
[[2.],
[0.]]],
[[[1.],
[0.]],
[[2.],
[4.]],
[[3.],
[0.]]]]]), size=(2, 3, 2, 3), nnz=3,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([[[0, 3],
[0, 3],
[0, 3]],
[[0, 3],
[0, 3],
[0, 3]]])
# _col_indices
tensor([[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]]])
# _values
tensor([[[[[1.],
[3.]],
[[2.],
[0.]],
[[0.],
[4.]]],
[[[1.],
[4.]],
[[2.],
[0.]],
[[3.],
[0.]]],
[[[1.],
[2.]],
[[0.],
[3.]],
[[0.],
[4.]]]],
[[[[0.],
[2.]],
[[1.],
[3.]],
[[0.],
[4.]]],
[[[1.],
[3.]],
[[0.],
[4.]],
[[2.],
[0.]]],
[[[1.],
[0.]],
[[2.],
[4.]],
[[3.],
[0.]]]]], dtype=torch.float64)
########## torch.float64/torch.int64/size=()+(8, 6)+() ##########
# sparse tensor
tensor(crow_indices=tensor([0, 2, 3, 5, 7]),
col_indices=tensor([0, 1, 0, 0, 1, 0, 1]),
values=tensor([[[ 0., 1., 0.],
[ 0., 4., 0.]],
[[ 2., 0., 3.],
[ 0., 5., 0.]],
[[ 6., 7., 8.],
[ 0., 0., 0.]],
[[ 0., 9., 0.],
[13., 0., 14.]],
[[10., 11., 12.],
[15., 16., 17.]],
[[ 0., 0., 0.],
[20., 21., 22.]],
[[ 0., 18., 19.],
[ 0., 23., 24.]]]), size=(8, 6), nnz=7,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 3, 5, 7])
# _col_indices
tensor([0, 1, 0, 0, 1, 0, 1])
# _values
tensor([[[ 0., 1., 0.],
[ 0., 4., 0.]],
[[ 2., 0., 3.],
[ 0., 5., 0.]],
[[ 6., 7., 8.],
[ 0., 0., 0.]],
[[ 0., 9., 0.],
[13., 0., 14.]],
[[10., 11., 12.],
[15., 16., 17.]],
[[ 0., 0., 0.],
[20., 21., 22.]],
[[ 0., 18., 19.],
[ 0., 23., 24.]]], dtype=torch.float64)
########## torch.float32/torch.int32/size=(2, 3)+(2, 3)+(4,) ##########
# sparse tensor
tensor(crow_indices=tensor([[[0, 3],
[0, 3],
[0, 3]],
[[0, 3],
[0, 3],
[0, 3]]]),
col_indices=tensor([[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]]]),
values=tensor([[[[[[1., 2., 3., 4.]],
[[3., 4., 5., 6.]]],
[[[2., 3., 4., 5.]],
[[0., 0., 0., 0.]]],
[[[0., 0., 0., 0.]],
[[4., 5., 6., 7.]]]],
[[[[1., 2., 3., 4.]],
[[4., 5., 6., 7.]]],
[[[2., 3., 4., 5.]],
[[0., 0., 0., 0.]]],
[[[3., 4., 5., 6.]],
[[0., 0., 0., 0.]]]],
[[[[1., 2., 3., 4.]],
[[2., 3., 4., 5.]]],
[[[0., 0., 0., 0.]],
[[3., 4., 5., 6.]]],
[[[0., 0., 0., 0.]],
[[4., 5., 6., 7.]]]]],
[[[[[0., 0., 0., 0.]],
[[2., 3., 4., 5.]]],
[[[1., 2., 3., 4.]],
[[3., 4., 5., 6.]]],
[[[0., 0., 0., 0.]],
[[4., 5., 6., 7.]]]],
[[[[1., 2., 3., 4.]],
[[3., 4., 5., 6.]]],
[[[0., 0., 0., 0.]],
[[4., 5., 6., 7.]]],
[[[2., 3., 4., 5.]],
[[0., 0., 0., 0.]]]],
[[[[1., 2., 3., 4.]],
[[0., 0., 0., 0.]]],
[[[2., 3., 4., 5.]],
[[4., 5., 6., 7.]]],
[[[3., 4., 5., 6.]],
[[0., 0., 0., 0.]]]]]]), size=(2, 3, 2, 3, 4), nnz=3,
layout=torch.sparse_bsr)
# _crow_indices
tensor([[[0, 3],
[0, 3],
[0, 3]],
[[0, 3],
[0, 3],
[0, 3]]], dtype=torch.int32)
# _col_indices
tensor([[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2],
[0, 1, 2]]], dtype=torch.int32)
# _values
tensor([[[[[[1., 2., 3., 4.]],
[[3., 4., 5., 6.]]],
[[[2., 3., 4., 5.]],
[[0., 0., 0., 0.]]],
[[[0., 0., 0., 0.]],
[[4., 5., 6., 7.]]]],
[[[[1., 2., 3., 4.]],
[[4., 5., 6., 7.]]],
[[[2., 3., 4., 5.]],
[[0., 0., 0., 0.]]],
[[[3., 4., 5., 6.]],
[[0., 0., 0., 0.]]]],
[[[[1., 2., 3., 4.]],
[[2., 3., 4., 5.]]],
[[[0., 0., 0., 0.]],
[[3., 4., 5., 6.]]],
[[[0., 0., 0., 0.]],
[[4., 5., 6., 7.]]]]],
[[[[[0., 0., 0., 0.]],
[[2., 3., 4., 5.]]],