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/llvm-project/mlir/test/Dialect/SparseTensor/
H A Droundtrip.mlir3 #SparseVector = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed)}>
7 // CHECK: %[[T:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr to tensor<128xf64, #{{.*}}>
10 %0 = sparse_tensor.new %arg0 : !llvm.ptr to tensor<128xf64, #SparseVector>
16 #SparseVector = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed), posWidth=32, crdWidth=32}>
22 // CHECK: %[[R:.*]] = sparse_tensor.assemble (%[[P]], %[[I]]), %[[D]]
26 %0 = sparse_tensor.assemble (%pos, %index), %data: (tensor<2xi32>, tensor<6x1xi32>), tensor<6xf64>
33 #SparseVector = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed), crdWidth=32}>
39 // CHECK: %[[P:.*]]:2, %[[D:.*]], %[[PL:.*]]:2, %[[DL:.*]] = sparse_tensor.disassemble %[[T]]
46 %rp, %ri, %d, %rpl, %ril, %dl = sparse_tensor.disassemble %sp : tensor<100xf64, #SparseVector>
55 #SparseVector = #sparse_tensor
[all...]
H A Dinvalid.mlir4 // expected-error@+1 {{'sparse_tensor.new' op result #0 must be sparse tensor of any type values, but got 'tensor<32xf32>'}}
5 %0 = sparse_tensor.new %arg0 : !llvm.ptr to tensor<32xf32>
11 #SparseVector = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed), posWidth=32, crdWidth=32}>
16 %0 = sparse_tensor.assemble (%pos, %coordinates), %values
23 #SparseVector = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed), posWidth=32, crdWidth=32}>
28 %0 = sparse_tensor.assemble (%pos, %coordinates), %values
35 #SparseVector = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton), posWidth=32, crdWidth=32}>
40 %0 = sparse_tensor.assemble (%pos, %coordinates), %values
47 #CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed), posWidth=32, crdWidth=32}>
52 %0 = sparse_tensor
[all...]
H A Dconvert_dense2sparse.mlir3 #SparseVector = #sparse_tensor.encoding<{
7 #CSR = #sparse_tensor.encoding<{
11 #CSC = #sparse_tensor.encoding<{
15 #SparseTensor = #sparse_tensor.encoding<{
20 // CHECK: sparse_tensor.foreach
23 // CHECK-NOT: sparse_tensor.reorder_coo
24 // CHECK: sparse_tensor.load
26 %0 = sparse_tensor.convert %arg0 : tensor<?xi32> to tensor<?xi32, #SparseVector>
31 // CHECK: sparse_tensor.foreach
34 // CHECK-NOT: sparse_tensor.reorder_coo
[all …]
H A Dfold.mlir3 #SparseVector = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed)}>
7 // CHECK-NOT: sparse_tensor.convert
10 %0 = sparse_tensor.convert %arg0 : tensor<64xf32> to tensor<64xf32>
16 // CHECK-NOT: sparse_tensor.convert
19 %0 = sparse_tensor.convert %arg0 : tensor<64xf32> to tensor<64xf32, #SparseVector>
25 // CHECK-NOT: sparse_tensor.positions
26 // CHECK-NOT: sparse_tensor.coordinates
27 // CHECK-NOT: sparse_tensor.values
30 …%0 = sparse_tensor.positions %arg0 { level = 0 : index } : tensor<64xf32, #SparseVector> to memref…
31 …%1 = sparse_tensor.coordinates %arg0 { level = 0 : index } : tensor<64xf32, #SparseVector> to memr…
[all …]
H A Dconvert_sparse2sparse.mlir3 #SparseVector64 = #sparse_tensor.encoding<{
9 #SparseVector32 = #sparse_tensor.encoding<{
15 #SparseVector = #sparse_tensor.encoding<{
19 #SortedCOO2D = #sparse_tensor.encoding<{
23 #SortedCOO3D = #sparse_tensor.encoding<{
28 #TsssPermuted = #sparse_tensor.encoding<{
32 #COOSlice = #sparse_tensor.encoding<{
33 …map = (d0 : #sparse_tensor<slice(2, 2, 1)>, d1 : #sparse_tensor<slice(12, 13, 1)>) -> (d0 : compre…
39 %0 = sparse_tensor.convert %arg0 : tensor<64xf32, #SparseVector> to tensor<64xf32, #SparseVector>
44 // CHECK-NEXT: sparse_tensor.convert
[all …]
H A Droundtrip_encoding.mlir3 #SV = #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>
5 // CHECK: #[[$SV:.*]] = #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>
12 #CSR = #sparse_tensor.encoding<{
18 // CHECK: #[[$CSR:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed),…
25 #CSR_OnlyOnes = #sparse_tensor.encoding<{
33 // CHECK: #[[$CSR_OnlyOnes:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : com…
40 #CSR_OnlyOnes = #sparse_tensor.encoding<{
46 // CHECK: #[[$CSR_OnlyOnes:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : com…
53 #CSR_OnlyOnes = #sparse_tensor.encoding<{
61 // CHECK: #[[$CSR_OnlyOnes:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : com…
[all …]
H A Dconvert_sparse2dense.mlir3 #SparseVector = #sparse_tensor.encoding<{
7 #SparseMatrix = #sparse_tensor.encoding<{
11 #SparseTensor = #sparse_tensor.encoding<{
16 // CHECK-NOT: sparse_tensor.reorder_coo
19 // CHECK: sparse_tensor.foreach
22 %0 = sparse_tensor.convert %arg0 : tensor<13xi32, #SparseVector> to tensor<13xi32>
27 // CHECK-NOT: sparse_tensor.reorder_coo
30 // CHECK: sparse_tensor.foreach
33 %0 = sparse_tensor.convert %arg0 : tensor<?xi32, #SparseVector> to tensor<?xi32>
38 // CHECK-NOT: sparse_tensor.reorder_coo
[all …]
H A Dcodegen.mlir3 #SV = #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>
5 #SparseVector = #sparse_tensor.encoding<{
11 #Dense2D = #sparse_tensor.encoding<{
17 #Row = #sparse_tensor.encoding<{
23 #CSR = #sparse_tensor.encoding<{
29 #UCSR = #sparse_tensor.encoding<{
33 #CSC = #sparse_tensor.encoding<{
37 #BCSR = #sparse_tensor.encoding<{
41 #DCSR = #sparse_tensor.encoding<{
47 #Dense3D = #sparse_tensor.encoding<{
[all …]
H A Dsparse_space_collapse.mlir3 #COO = #sparse_tensor.encoding<{
14 // CHECK: %[[VAL_3:.*]] = sparse_tensor.extract_iteration_space %[[VAL_0]] lvls = 0 to 2
15 // CHECK: %[[VAL_4:.*]] = sparse_tensor.iterate %[[VAL_5:.*]] in %[[VAL_3]] iter_args(%[[…
17 // CHECK: sparse_tensor.yield %[[VAL_7]] : index
24 %l1 = sparse_tensor.extract_iteration_space %sp lvls = 0
25 : tensor<4x8xf32, #COO> -> !sparse_tensor.iter_space<#COO, lvls = 0>
26 …%r1 = sparse_tensor.iterate %it1 in %l1 iter_args(%outer = %i): !sparse_tensor.iter_space<#COO, lv…
27 %l2 = sparse_tensor.extract_iteration_space %sp at %it1 lvls = 1
28 …: tensor<4x8xf32, #COO>, !sparse_tensor.iterator<#COO, lvls = 0 to 1> -> !sparse_tensor.iter_space…
29 …%r2 = sparse_tensor.iterate %it2 in %l2 iter_args(%inner = %outer): !sparse_tensor.iter_space<#COO…
[all …]
H A Dinvalid_encoding.mlir4 #a = #sparse_tensor.encoding<{map = []}>
10 #a = #sparse_tensor.encoding<{map = ()}>
16 #a = #sparse_tensor.encoding<{map = (d0 -> d0)}>
22 #a = #sparse_tensor.encoding<{map = d0 -> d0}>
28 #a = #sparse_tensor.encoding<{map = (d0) -> d0}>
34 #a = #sparse_tensor.encoding<{map = (d0) -> (d0)}>
40 #a = #sparse_tensor.encoding<{map = (d0) -> (d0:)}>
46 #a = #sparse_tensor.encoding<{map = (d0) -> (d0 : (compressed))}>
52 #a = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
58 #a = #sparse_tensor.encoding<{map = (d0, d1, d2) -> (d0 : batch, d1 : compressed, d2: batch)}>
[all …]
H A Dsparse_matmul_codegen.mlir5 #CSR = #sparse_tensor.encoding<{
16 // CHECK-SAME: %[[VAL_3:.*3]]: !sparse_tensor.storage_specifier
20 // CHECK-SAME: %[[VAL_7:.*7]]: !sparse_tensor.storage_specifier
33 // CHECK: %[[VAL_20:.*]] = sparse_tensor.storage_specifier.init : !sparse_tensor.storage_…
34 …: %[[VAL_21:.*]] = sparse_tensor.storage_specifier.set %[[VAL_20]] lvl_sz at 0 with %[[…
35 …: %[[VAL_22:.*]] = sparse_tensor.storage_specifier.set %[[VAL_21]] lvl_sz at 1 with %[[…
36 …/ CHECK: %[[VAL_23:.*]] = sparse_tensor.storage_specifier.get %[[VAL_22]] pos_mem_sz at…
37 // CHECK: %[[VAL_24:.*]], %[[VAL_25:.*]] = sparse_tensor.push_back %[[VAL_23]], %[[VAL_15…
38 … %[[VAL_26:.*]] = sparse_tensor.storage_specifier.set %[[VAL_22]] pos_mem_sz at 1 with %…
39 // CHECK: %[[VAL_27:.*]], %[[VAL_28:.*]] = sparse_tensor.push_back %[[VAL_25]], %[[VAL_24…
[all …]
H A Dsparse_itertion_licm.mlir3 #CSR = #sparse_tensor.encoding<{
12 // CHECK: sparse_tensor.values
13 // CHECK: sparse_tensor.positions
14 // CHECK: sparse_tensor.coordinate
15 // CHECK: sparse_tensor.iterate
17 %l1 = sparse_tensor.extract_iteration_space %sp lvls = 0 : tensor<?x?xf64, #CSR>
18 … -> !sparse_tensor.iter_space<#CSR, lvls = 0>
19 sparse_tensor.iterate %it1 in %l1 at (%crd) : !sparse_tensor.iter_space<#CSR, lvls = 0> {
20 %0 = sparse_tensor.values %sp : tensor<?x?xf64, #CSR> to memref<?xf64>
21 … %1 = sparse_tensor.positions %sp { level = 1 : index } : tensor<?x?xf64, #CSR> to memref<?xindex>
[all …]
H A Dcodegen_buffer_initialization.mlir3 #SV = #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>
6 …_0:.*]]: index) -> (memref<?xindex>, memref<?xindex>, memref<?xf64>, !sparse_tensor.storage_specif…
19 // CHECK: %[[VAL_10:.*]] = sparse_tensor.storage_specifier.init : !sparse_tensor.storage_…
20 … CHECK: %[[VAL_12:.*]] = sparse_tensor.storage_specifier.set %[[VAL_10]] lvl_sz at 0 with %[…
21 …/ CHECK: %[[VAL_14:.*]] = sparse_tensor.storage_specifier.get %[[VAL_12]] pos_mem_sz at…
22 // CHECK: %[[VAL_15:.*]], %[[VAL_17:.*]] = sparse_tensor.push_back %[[VAL_14]], %[[VAL_5]…
23 …HECK: %[[VAL_18:.*]] = sparse_tensor.storage_specifier.set %[[VAL_12]] pos_mem_sz at 0 with %…
24 // CHECK: %[[VAL_19:.*]], %[[VAL_21:.*]] = sparse_tensor.push_back %[[VAL_17]], %[[VAL_15…
25 …HECK: %[[VAL_22:.*]] = sparse_tensor.storage_specifier.set %[[VAL_18]] pos_mem_sz at 0 with %…
26 …_9]], %[[VAL_22]] : memref<?xindex>, memref<?xindex>, memref<?xf64>, !sparse_tensor.storage_specif…
[all …]
H A Dsparse_extract_slice.mlir3 #CSR = #sparse_tensor.encoding<{
7 #CSR_SLICE = #sparse_tensor.encoding<{
8 …map = (d0 : #sparse_tensor<slice(0, 4, 1)>, d1 : #sparse_tensor<slice(0, 8, 1)>) -> (d0 : dense, d…
15 // CHECK-SAME: %[[VAL_3:.*3]]: !sparse_tensor.storage_specifier<#sparse{…
16 // CHECK: %[[VAL_4:.*]] = sparse_tensor.storage_specifier.init with %[[VAL_3]]
20 // CHECK: %[[VAL_8:.*]] = sparse_tensor.storage_specifier.set %[[VAL_4]] dim_offset at 0…
21 // CHECK: %[[VAL_9:.*]] = sparse_tensor.storage_specifier.set %[[VAL_8]] lvl_sz at 0 wit…
22 // CHECK: %[[VAL_10:.*]] = sparse_tensor.storage_specifier.set %[[VAL_9]] dim_stride at …
24 // CHECK: %[[VAL_12:.*]] = sparse_tensor.storage_specifier.set %[[VAL_10]] dim_offset at…
25 // CHECK: %[[VAL_13:.*]] = sparse_tensor.storage_specifier.set %[[VAL_12]] lvl_sz at 1 w…
[all …]
H A Dexternal_direct.mlir9 // CHECK: %[[I:.*]] = sparse_tensor.assemble (%[[B]], %[[C]]), %[[A]]
14 #sparse = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
16 %0 = sparse_tensor.convert %arg0 : tensor<64x64xf32, #sparse> to tensor<64x64xf32>
25 // CHECK: %[[P:.*]] = sparse_tensor.positions %[[F]]
26 // CHECK: %[[C:.*]] = sparse_tensor.coordinates %[[F]]
27 // CHECK: %[[V:.*]] = sparse_tensor.values %[[F]]
31 #sparse = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
33 %0 = sparse_tensor.convert %arg0 : tensor<64x64xf32> to tensor<64x64xf32, #sparse>
42 // CHECK: %[[P:.*]] = sparse_tensor.positions %[[F]]#1
43 // CHECK: %[[C:.*]] = sparse_tensor.coordinates %[[F]]#1
[all …]
H A Dsparse_foreach.mlir20 sparse_tensor.foreach in %cst { order = affine_map<(d0, d1) -> (d1, d0)> } : tensor<8x7xf32> do {
24 sparse_tensor.foreach in %cst : tensor<8x7xf32> do {
31 #CSR_SLICE = #sparse_tensor.encoding<{
32 …map = (d0 : #sparse_tensor<slice(0, 4, 1)>, d1 : #sparse_tensor<slice(2, 4, 1)>) -> (d0 : compress…
35 #CSR_SLICE_DYN = #sparse_tensor.encoding<{
36 …map = (d0 : #sparse_tensor<slice(?, ?, ?)>, d1 : #sparse_tensor<slice(?, ?, ?)>) -> (d0 : compress…
45 // C_HECK-DAG: %[[VAL_3:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tenso…
46 // C_HECK-DAG: %[[VAL_4:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : ten…
47 // C_HECK-DAG: %[[VAL_5:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xf64,
48 // C_HECK-DAG: %[[VAL_6:.*]] = sparse_tensor.slice.offset %[[VAL_0]] at 0 : tensor<?x?xf64,
[all …]
H A Dsparse_iteration_to_scf.mlir5 #COO = #sparse_tensor.encoding<{
40 %l1 = sparse_tensor.extract_iteration_space %sp lvls = 0
41 : tensor<4x8xf32, #COO> -> !sparse_tensor.iter_space<#COO, lvls = 0>
42 …%r1 = sparse_tensor.iterate %it1 in %l1 iter_args(%outer = %i): !sparse_tensor.iter_space<#COO, lv…
43 %l2 = sparse_tensor.extract_iteration_space %sp at %it1 lvls = 1
44 …: tensor<4x8xf32, #COO>, !sparse_tensor.iterator<#COO, lvls = 0 to 1> -> !sparse_tensor.iter_space…
45 …%r2 = sparse_tensor.iterate %it2 in %l2 iter_args(%inner = %outer): !sparse_tensor.iter_space<#COO…
47 sparse_tensor.yield %k : index
49 sparse_tensor.yield %r2 : index
H A Dsparse_reinterpret_map.mlir13 #BSR = #sparse_tensor.encoding<{ // 2x4 blocks
29 // CHECK: %[[T0:.*]] = sparse_tensor.reinterpret_map %[[A2]]
31 // CHECK: %[[T2:.*]] = sparse_tensor.reinterpret_map %[[T1]]
49 #BSR = #sparse_tensor.encoding<{
58 // CHECK-DAG: #[[$remap:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 floordiv 2 : dense, …
59 // CHECK-DAG: #[[$demap:.*]] = #sparse_tensor.encoding<{ map = (d0, d1, d2, d3) -> (d0 : dense, d1 …
63 // CHECK: %[[VAL_2:.*]] = sparse_tensor.reinterpret_map %[[VAL_0]] : tensor<2x4xf64, #[[$…
64 // CHECK: %[[VAL_4:.*]] = sparse_tensor.foreach in %[[VAL_2]] init(%[[VAL_1]])
67 // CHECK: sparse_tensor.yield %[[VAL_11]] : tensor<1x2x2x2xf64, #sparse{{[0-9]*}}>
69 // CHECK: %[[VAL_12:.*]] = sparse_tensor.reinterpret_map %[[VAL_4]] : tensor<1x2x2x2xf64,…
[all …]
H A Dspecifier_to_llvm.mlir3 #CSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
13 func.func @sparse_metadata_init() -> !sparse_tensor.storage_specifier<#CSR> {
14 %0 = sparse_tensor.storage_specifier.init : !sparse_tensor.storage_specifier<#CSR>
15 return %0 : !sparse_tensor.storage_specifier<#CSR>
23 func.func @sparse_get_md(%arg0: !sparse_tensor.storage_specifier<#CSR>) -> index {
24 %0 = sparse_tensor.storage_specifier.get %arg0 lvl_sz at 0
25 : !sparse_tensor.storage_specifier<#CSR>
35 func.func @sparse_set_md(%arg0: !sparse_tensor.storage_specifier<#CSR>, %arg1: index)
36 -> !sparse_tensor.storage_specifier<#CSR> {
37 %0 = sparse_tensor.storage_specifier.set %arg0 lvl_sz at 0 with %arg1
[all …]
H A Dsparse_concat.mlir7 #DCSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed, d1 : compressed)}>
18 // CHECK-DAG: %[[TMP_1:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 0 : index} : tensor…
19 // CHECK-DAG: %[[TMP_2:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 0 : index} : tens…
20 // CHECK-DAG: %[[TMP_3:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 1 : index} : tensor…
21 // CHECK-DAG: %[[TMP_4:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 1 : index} : tens…
22 // CHECK-DAG: %[[TMP_5:.*]] = sparse_tensor.values %[[TMP_arg0]] : tensor<2x4xf64, #sparse>
38 // CHECK-DAG: %[[TMP_8:.*]] = sparse_tensor.positions %[[TMP_arg1]] {level = 0 : index} : tensor…
39 // CHECK-DAG: %[[TMP_9:.*]] = sparse_tensor.coordinates %[[TMP_arg1]] {level = 0 : index} : tens…
40 // CHECK-DAG: %[[TMP_10:.*]] = sparse_tensor.positions %[[TMP_arg1]] {level = 1 : index} : tenso…
41 // CHECK-DAG: %[[TMP_11:.*]] = sparse_tensor.coordinates %[[TMP_arg1]] {level = 1 : index} : ten…
[all …]
/llvm-project/mlir/lib/Dialect/SparseTensor/Transforms/
H A DBufferizableOpInterfaceImpl.cpp23 using namespace mlir::sparse_tensor;
26 namespace sparse_tensor { namespace
41 sparse_tensor::ConcatenateOp> {
66 ConvertOpInterface, sparse_tensor::ConvertOp> {
96 sparse_tensor::LoadOp> {
115 sparse_tensor::NewOp> {
127 AssembleOpInterface, sparse_tensor::AssembleOp> {
159 DisassembleOpInterface, sparse_tensor::DisassembleOp> {
191 ForeachOpInterface, sparse_tensor::ForeachOp> {
221 NumberOfEntriesOpInterface, sparse_tensor::NumberOfEntriesOp> {
[all …]
/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/
H A Dsparse_print.mlir28 #AllDense = #sparse_tensor.encoding<{
35 #AllDenseT = #sparse_tensor.encoding<{
42 #CSR = #sparse_tensor.encoding<{
49 #DCSR = #sparse_tensor.encoding<{
56 #CSC = #sparse_tensor.encoding<{
63 #DCSC = #sparse_tensor.encoding<{
70 #BSR = #sparse_tensor.encoding<{
79 #BSRC = #sparse_tensor.encoding<{
88 #BSC = #sparse_tensor.encoding<{
97 #BSCC = #sparse_tensor
[all...]
H A Dsparse_conversion_sparse2dense.mlir34 #Tensor1 = #sparse_tensor.encoding<{
38 #Tensor2 = #sparse_tensor.encoding<{
42 #Tensor3 = #sparse_tensor.encoding<{
46 #Tensor4 = #sparse_tensor.encoding<{
50 #Tensor5 = #sparse_tensor.encoding<{
54 #Tensor6 = #sparse_tensor.encoding<{
127 %s2341 = sparse_tensor.convert %src : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor1>
128 %s2342 = sparse_tensor.convert %src : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor2>
129 %s2343 = sparse_tensor.convert %src : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor3>
130 %s2344 = sparse_tensor
[all...]
H A Dsparse_matmul_slice.mlir26 #DCSR = #sparse_tensor.encoding<{
30 #DCSR_SLICE = #sparse_tensor.encoding<{
31 map = (d0 : #sparse_tensor<slice(0, 4, 1)>, d1 : #sparse_tensor<slice(0, 8, 1)>) -> (d0 : compressed, d1 : compressed)
34 #CSR = #sparse_tensor.encoding<{
38 #CSR_SLICE = #sparse_tensor.encoding<{
39 map = (d0 : #sparse_tensor<slice(0, 4, 1)>, d1 : #sparse_tensor<slice(0, 8, 1)>) -> (d0 : dense, d1 : compressed)
42 #COO = #sparse_tensor.encoding<{
46 #CSR_SLICE_1 = #sparse_tensor
[all...]
H A Dsparse_foreach_slices.mlir27 #CSR = #sparse_tensor.encoding<{
31 #CSR_SLICE = #sparse_tensor.encoding<{
32 map = (d0 : #sparse_tensor<slice(1, 4, 1)>, d1 : #sparse_tensor<slice(1, 4, 2)>) -> (d0 : dense, d1 : compressed)
35 #CSR_SLICE_DYN = #sparse_tensor.encoding<{
36 map = (d0 : #sparse_tensor<slice(?, ?, ?)>, d1 : #sparse_tensor<slice(?, ?, ?)>) -> (d0 : dense, d1 : compressed)
39 #COO = #sparse_tensor.encoding<{
43 #COO_SLICE = #sparse_tensor.encoding<{
44 map = (d0 : #sparse_tensor<slic
[all...]

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