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android / platform / external / pytorch / 8c88a55d44 / . / test / expect / TestSparseCompressedCUDA.test_print_SparseBSR_cuda.expect
blob: 90c158c8860d4e85aa9544052081944fbb9a8e8d [file] [log] [blame]
########## 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.]]]), device='cuda:0', size=(2, 4), nnz=4,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 4], device='cuda:0', dtype=torch.int32)
# _col_indices
tensor([0, 1, 0, 1], device='cuda:0', dtype=torch.int32)
# _values
tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]], device='cuda:0')
########## 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)), device='cuda:0', size=(0, 0), nnz=0,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0], device='cuda:0', dtype=torch.int32)
# _col_indices
tensor([], device='cuda:0', dtype=torch.int32)
# _values
tensor([], device='cuda:0', 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.]]]]), device='cuda:0', size=(2, 2, 4), nnz=4,
layout=torch.sparse_bsr)
# _crow_indices
tensor([[0, 2, 4],
[0, 2, 4]], device='cuda:0', dtype=torch.int32)
# _col_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]], device='cuda:0', dtype=torch.int32)
# _values
tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]], device='cuda:0')
########## 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.]]]]]), device='cuda:0', size=(2, 3, 2, 4),
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]]], device='cuda:0', 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]]], device='cuda:0', 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.]]]]], device='cuda:0')
########## 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.]]]), device='cuda:0', size=(2, 4), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 4], device='cuda:0', dtype=torch.int32)
# _col_indices
tensor([0, 1, 0, 1], device='cuda:0', dtype=torch.int32)
# _values
tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]], device='cuda:0', 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)), device='cuda:0', size=(0, 0), nnz=0,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([0], device='cuda:0', dtype=torch.int32)
# _col_indices
tensor([], device='cuda:0', dtype=torch.int32)
# _values
tensor([], device='cuda:0', 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.]]]]), device='cuda:0', size=(2, 2, 4), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([[0, 2, 4],
[0, 2, 4]], device='cuda:0', dtype=torch.int32)
# _col_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]], device='cuda:0', dtype=torch.int32)
# _values
tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]], device='cuda:0', 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.]]]]]), device='cuda:0', size=(2, 3, 2, 4),
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]]], device='cuda:0', 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]]], device='cuda:0', 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.]]]]], device='cuda:0', 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.]]]), device='cuda:0', size=(2, 4), nnz=4,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 4], device='cuda:0')
# _col_indices
tensor([0, 1, 0, 1], device='cuda:0')
# _values
tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]], device='cuda:0')
########## 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)), device='cuda:0', size=(0, 0), nnz=0,
layout=torch.sparse_bsr)
# _crow_indices
tensor([0], device='cuda:0')
# _col_indices
tensor([], device='cuda:0', dtype=torch.int64)
# _values
tensor([], device='cuda:0', 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.]]]]), device='cuda:0', size=(2, 2, 4), nnz=4,
layout=torch.sparse_bsr)
# _crow_indices
tensor([[0, 2, 4],
[0, 2, 4]], device='cuda:0')
# _col_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]], device='cuda:0')
# _values
tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]], device='cuda:0')
########## 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.]]]]]), device='cuda:0', size=(2, 3, 2, 4),
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]]], device='cuda:0')
# _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]]], device='cuda:0')
# _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.]]]]], device='cuda:0')
########## 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.]]]), device='cuda:0', size=(2, 4), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([0, 2, 4], device='cuda:0')
# _col_indices
tensor([0, 1, 0, 1], device='cuda:0')
# _values
tensor([[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]], device='cuda:0', 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)), device='cuda:0', size=(0, 0), nnz=0,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([0], device='cuda:0')
# _col_indices
tensor([], device='cuda:0', dtype=torch.int64)
# _values
tensor([], device='cuda:0', 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.]]]]), device='cuda:0', size=(2, 2, 4), nnz=4,
dtype=torch.float64, layout=torch.sparse_bsr)
# _crow_indices
tensor([[0, 2, 4],
[0, 2, 4]], device='cuda:0')
# _col_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]], device='cuda:0')
# _values
tensor([[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]],
[[[ 1., 11.]],
[[ 2., 22.]],
[[ 3., 33.]],
[[ 4., 44.]]]], device='cuda:0', 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.]]]]]), device='cuda:0', size=(2, 3, 2, 4),
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]]], device='cuda:0')
# _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]]], device='cuda:0')
# _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.]]]]], device='cuda:0', dtype=torch.float64)