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TestSparseCompressedCPU.test_print_SparseBSR_cpu.expect
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TestSparseCompressedCPU.test_print_SparseBSR_cpu.expect
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########## torch.float32/torch.int32/batch_shape=()/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([0, 2, 4]),
col_indices=tensor([0, 1, 0, 1]),
values=tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]), size=(2, 2), nnz=4,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 4], dtype=torch.int32)
# _col_indices
tensor([0, 1, 0, 1], dtype=torch.int32)
# _values
tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]])
########## torch.float32/torch.int32/batch_shape=()/block_shape=(0, 0) ##########
# sparse tensor
tensor(crow_indices=tensor([0]),
col_indices=tensor([], size=(0,)),
values=tensor([], size=(1, 0, 0)), size=(0, 0), nnz=0,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0], dtype=torch.int32)
# _col_indices
tensor([], dtype=torch.int32)
# _values
tensor([], size=(1, 0, 0))
########## torch.float32/torch.int32/batch_shape=(2,)/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([[0, 2, 4],
[0, 2, 4]]),
col_indices=tensor([[0, 1, 0, 1],
[0, 1, 0, 1]]),
values=tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]), size=(2, 2, 2), nnz=4,
layout=torch.sparse_bsr)
# _crow_indices
tensor([[0, 2, 4],
[0, 2, 4]], dtype=torch.int32)
# _col_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]], dtype=torch.int32)
# _values
tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]])
########## torch.float32/torch.int32/batch_shape=(2, 3)/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]]),
col_indices=tensor([[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]],
[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]]]),
values=tensor([[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]],
[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]]), size=(2, 3, 2, 2), nnz=4,
layout=torch.sparse_bsr)
# _crow_indices
tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]], dtype=torch.int32)
# _col_indices
tensor([[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]],
[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]]], dtype=torch.int32)
# _values
tensor([[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]],
[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]])
########## torch.float64/torch.int32/batch_shape=()/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([0, 2, 4]),
col_indices=tensor([0, 1, 0, 1]),
values=tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]), size=(2, 2), nnz=4, dtype=torch.float64,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 4], dtype=torch.int32)
# _col_indices
tensor([0, 1, 0, 1], dtype=torch.int32)
# _values
tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]], dtype=torch.float64)
########## torch.float64/torch.int32/batch_shape=()/block_shape=(0, 0) ##########
# sparse tensor
tensor(crow_indices=tensor([0]),
col_indices=tensor([], size=(0,)),
values=tensor([], size=(1, 0, 0)), size=(0, 0), nnz=0,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([0], dtype=torch.int32)
# _col_indices
tensor([], dtype=torch.int32)
# _values
tensor([], size=(1, 0, 0), dtype=torch.float64)
########## torch.float64/torch.int32/batch_shape=(2,)/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([[0, 2, 4],
[0, 2, 4]]),
col_indices=tensor([[0, 1, 0, 1],
[0, 1, 0, 1]]),
values=tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]), size=(2, 2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([[0, 2, 4],
[0, 2, 4]], dtype=torch.int32)
# _col_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]], dtype=torch.int32)
# _values
tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]], dtype=torch.float64)
########## torch.float64/torch.int32/batch_shape=(2, 3)/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]]),
col_indices=tensor([[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]],
[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]]]),
values=tensor([[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]],
[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]]), size=(2, 3, 2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]], dtype=torch.int32)
# _col_indices
tensor([[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]],
[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]]], dtype=torch.int32)
# _values
tensor([[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]],
[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]], dtype=torch.float64)
########## torch.float32/torch.int64/batch_shape=()/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([0, 2, 4]),
col_indices=tensor([0, 1, 0, 1]),
values=tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]), size=(2, 2), nnz=4,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 4])
# _col_indices
tensor([0, 1, 0, 1])
# _values
tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]])
########## torch.float32/torch.int64/batch_shape=()/block_shape=(0, 0) ##########
# sparse tensor
tensor(crow_indices=tensor([0]),
col_indices=tensor([], size=(0,)),
values=tensor([], size=(1, 0, 0)), size=(0, 0), nnz=0,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0])
# _col_indices
tensor([], dtype=torch.int64)
# _values
tensor([], size=(1, 0, 0))
########## torch.float32/torch.int64/batch_shape=(2,)/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([[0, 2, 4],
[0, 2, 4]]),
col_indices=tensor([[0, 1, 0, 1],
[0, 1, 0, 1]]),
values=tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]), size=(2, 2, 2), nnz=4,
layout=torch.sparse_bsr)
# _crow_indices
tensor([[0, 2, 4],
[0, 2, 4]])
# _col_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]])
# _values
tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]])
########## torch.float32/torch.int64/batch_shape=(2, 3)/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]]),
col_indices=tensor([[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]],
[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]]]),
values=tensor([[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]],
[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]]), size=(2, 3, 2, 2), nnz=4,
layout=torch.sparse_bsr)
# _crow_indices
tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]])
# _col_indices
tensor([[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]],
[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]]])
# _values
tensor([[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]],
[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]])
########## torch.float64/torch.int64/batch_shape=()/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([0, 2, 4]),
col_indices=tensor([0, 1, 0, 1]),
values=tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]), size=(2, 2), nnz=4, dtype=torch.float64,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 4])
# _col_indices
tensor([0, 1, 0, 1])
# _values
tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]], dtype=torch.float64)
########## torch.float64/torch.int64/batch_shape=()/block_shape=(0, 0) ##########
# sparse tensor
tensor(crow_indices=tensor([0]),
col_indices=tensor([], size=(0,)),
values=tensor([], size=(1, 0, 0)), size=(0, 0), nnz=0,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([0])
# _col_indices
tensor([], dtype=torch.int64)
# _values
tensor([], size=(1, 0, 0), dtype=torch.float64)
########## torch.float64/torch.int64/batch_shape=(2,)/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([[0, 2, 4],
[0, 2, 4]]),
col_indices=tensor([[0, 1, 0, 1],
[0, 1, 0, 1]]),
values=tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]), size=(2, 2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([[0, 2, 4],
[0, 2, 4]])
# _col_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]])
# _values
tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]], dtype=torch.float64)
########## torch.float64/torch.int64/batch_shape=(2, 3)/block_shape=(1, 2) ##########
# sparse tensor
tensor(crow_indices=tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]]),
col_indices=tensor([[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]],
[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]]]),
values=tensor([[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]],
[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]]), size=(2, 3, 2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]])
# _col_indices
tensor([[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]],
[[0, 1, 0, 1],
[0, 1, 0, 1],
[0, 1, 0, 1]]])
# _values
tensor([[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]],
[[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]]], dtype=torch.float64)