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pytorch/test/expect/TestSparseCompressedCPU.test_print_SparseCSC_cpu.expect
Pearu Peterson ccc991ba29 Support str for Sparse Compressed tensors 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77530

Approved by: https://github.com/cpuhrsch
2022-05-18 12:58:54 +00:00

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########## torch.float32/torch.int32/batch_shape=()/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 1]),
values=tensor([1., 2., 3., 4.]), size=(2, 2), nnz=4,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], dtype=torch.int32)
# _row_indices
tensor([0, 1, 0, 1], dtype=torch.int32)
# _values
tensor([1., 2., 3., 4.])
########## torch.float32/torch.int32/batch_shape=()/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([0]),
row_indices=tensor([], size=(0,)),
values=tensor([], size=(0,)), size=(0, 0), nnz=0,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0], dtype=torch.int32)
# _row_indices
tensor([], dtype=torch.int32)
# _values
tensor([])
########## torch.float32/torch.int32/batch_shape=(2,)/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([[0, 2, 4],
[0, 2, 4]]),
row_indices=tensor([[0, 1, 0, 1],
[0, 1, 0, 1]]),
values=tensor([[1., 2., 3., 4.],
[1., 2., 3., 4.]]), size=(2, 2, 2), nnz=4,
layout=torch.sparse_csc)
# _ccol_indices
tensor([[0, 2, 4],
[0, 2, 4]], dtype=torch.int32)
# _row_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]], dtype=torch.int32)
# _values
tensor([[1., 2., 3., 4.],
[1., 2., 3., 4.]])
########## torch.float32/torch.int32/batch_shape=(2, 3)/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]]),
row_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., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]],
[[1., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]]]), size=(2, 3, 2, 2), nnz=4,
layout=torch.sparse_csc)
# _ccol_indices
tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]], dtype=torch.int32)
# _row_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., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]],
[[1., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]]])
########## torch.float64/torch.int32/batch_shape=()/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 1]),
values=tensor([1., 2., 3., 4.]), size=(2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4], dtype=torch.int32)
# _row_indices
tensor([0, 1, 0, 1], dtype=torch.int32)
# _values
tensor([1., 2., 3., 4.], dtype=torch.float64)
########## torch.float64/torch.int32/batch_shape=()/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([0]),
row_indices=tensor([], size=(0,)),
values=tensor([], size=(0,)), size=(0, 0), nnz=0, dtype=torch.float64,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0], dtype=torch.int32)
# _row_indices
tensor([], dtype=torch.int32)
# _values
tensor([], dtype=torch.float64)
########## torch.float64/torch.int32/batch_shape=(2,)/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([[0, 2, 4],
[0, 2, 4]]),
row_indices=tensor([[0, 1, 0, 1],
[0, 1, 0, 1]]),
values=tensor([[1., 2., 3., 4.],
[1., 2., 3., 4.]]), size=(2, 2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([[0, 2, 4],
[0, 2, 4]], dtype=torch.int32)
# _row_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]], dtype=torch.int32)
# _values
tensor([[1., 2., 3., 4.],
[1., 2., 3., 4.]], dtype=torch.float64)
########## torch.float64/torch.int32/batch_shape=(2, 3)/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]]),
row_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., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]],
[[1., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]]]), size=(2, 3, 2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]], dtype=torch.int32)
# _row_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., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]],
[[1., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]]], dtype=torch.float64)
########## torch.float32/torch.int64/batch_shape=()/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 1]),
values=tensor([1., 2., 3., 4.]), size=(2, 2), nnz=4,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4])
# _row_indices
tensor([0, 1, 0, 1])
# _values
tensor([1., 2., 3., 4.])
########## torch.float32/torch.int64/batch_shape=()/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([0]),
row_indices=tensor([], size=(0,)),
values=tensor([], size=(0,)), size=(0, 0), nnz=0,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0])
# _row_indices
tensor([], dtype=torch.int64)
# _values
tensor([])
########## torch.float32/torch.int64/batch_shape=(2,)/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([[0, 2, 4],
[0, 2, 4]]),
row_indices=tensor([[0, 1, 0, 1],
[0, 1, 0, 1]]),
values=tensor([[1., 2., 3., 4.],
[1., 2., 3., 4.]]), size=(2, 2, 2), nnz=4,
layout=torch.sparse_csc)
# _ccol_indices
tensor([[0, 2, 4],
[0, 2, 4]])
# _row_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]])
# _values
tensor([[1., 2., 3., 4.],
[1., 2., 3., 4.]])
########## torch.float32/torch.int64/batch_shape=(2, 3)/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]]),
row_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., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]],
[[1., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]]]), size=(2, 3, 2, 2), nnz=4,
layout=torch.sparse_csc)
# _ccol_indices
tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]])
# _row_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., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]],
[[1., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]]])
########## torch.float64/torch.int64/batch_shape=()/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([0, 2, 4]),
row_indices=tensor([0, 1, 0, 1]),
values=tensor([1., 2., 3., 4.]), size=(2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([0, 2, 4])
# _row_indices
tensor([0, 1, 0, 1])
# _values
tensor([1., 2., 3., 4.], dtype=torch.float64)
########## torch.float64/torch.int64/batch_shape=()/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([0]),
row_indices=tensor([], size=(0,)),
values=tensor([], size=(0,)), size=(0, 0), nnz=0, dtype=torch.float64,
layout=torch.sparse_csc)
# _ccol_indices
tensor([0])
# _row_indices
tensor([], dtype=torch.int64)
# _values
tensor([], dtype=torch.float64)
########## torch.float64/torch.int64/batch_shape=(2,)/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([[0, 2, 4],
[0, 2, 4]]),
row_indices=tensor([[0, 1, 0, 1],
[0, 1, 0, 1]]),
values=tensor([[1., 2., 3., 4.],
[1., 2., 3., 4.]]), size=(2, 2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([[0, 2, 4],
[0, 2, 4]])
# _row_indices
tensor([[0, 1, 0, 1],
[0, 1, 0, 1]])
# _values
tensor([[1., 2., 3., 4.],
[1., 2., 3., 4.]], dtype=torch.float64)
########## torch.float64/torch.int64/batch_shape=(2, 3)/block_shape=() ##########
# sparse tensor
tensor(ccol_indices=tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]]),
row_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., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]],
[[1., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]]]), size=(2, 3, 2, 2), nnz=4,
dtype=torch.float64, layout=torch.sparse_csc)
# _ccol_indices
tensor([[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]],
[[0, 2, 4],
[0, 2, 4],
[0, 2, 4]]])
# _row_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., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]],
[[1., 2., 3., 4.],
[1., 2., 3., 4.],
[1., 2., 3., 4.]]], dtype=torch.float64)
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