1// RUN: mlir-opt %s \ 2// RUN: --sparsification --sparse-tensor-conversion \ 3// RUN: --convert-vector-to-scf --convert-scf-to-std \ 4// RUN: --func-bufferize --tensor-constant-bufferize --tensor-bufferize \ 5// RUN: --std-bufferize --finalizing-bufferize \ 6// RUN: --convert-vector-to-llvm --convert-memref-to-llvm --convert-std-to-llvm | \ 7// RUN: mlir-cpu-runner \ 8// RUN: -e entry -entry-point-result=void \ 9// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ 10// RUN: FileCheck %s 11 12// 13// Several common sparse storage schemes. 14// 15 16#Dense = #sparse_tensor.encoding<{ 17 dimLevelType = [ "dense", "dense" ] 18}> 19 20#CSR = #sparse_tensor.encoding<{ 21 dimLevelType = [ "dense", "compressed" ] 22}> 23 24#DCSR = #sparse_tensor.encoding<{ 25 dimLevelType = [ "compressed", "compressed" ] 26}> 27 28#CSC = #sparse_tensor.encoding<{ 29 dimLevelType = [ "dense", "compressed" ], 30 dimOrdering = affine_map<(i,j) -> (j,i)> 31}> 32 33#DCSC = #sparse_tensor.encoding<{ 34 dimLevelType = [ "compressed", "compressed" ], 35 dimOrdering = affine_map<(i,j) -> (j,i)> 36}> 37 38// 39// Integration test that looks "under the hood" of sparse storage schemes. 40// 41module { 42 // 43 // Main driver that initializes a sparse tensor and inspects the sparse 44 // storage schemes in detail. Note that users of the MLIR sparse compiler 45 // are typically not concerned with such details, but the test ensures 46 // everything is working "under the hood". 47 // 48 func @entry() { 49 %c0 = constant 0 : index 50 %c1 = constant 1 : index 51 %d0 = constant 0.0 : f64 52 53 // 54 // Initialize a dense tensor. 55 // 56 %t = constant dense<[ 57 [ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 3.0], 58 [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 59 [ 0.0, 0.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0], 60 [ 0.0, 0.0, 0.0, 5.0, 0.0, 0.0, 0.0, 0.0], 61 [ 0.0, 0.0, 0.0, 0.0, 6.0, 0.0, 0.0, 0.0], 62 [ 0.0, 7.0, 8.0, 0.0, 0.0, 0.0, 0.0, 9.0], 63 [ 0.0, 0.0, 10.0, 0.0, 0.0, 0.0, 11.0, 12.0], 64 [ 0.0, 13.0, 14.0, 0.0, 0.0, 0.0, 15.0, 16.0], 65 [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 66 [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 17.0, 0.0] 67 ]> : tensor<10x8xf64> 68 69 // 70 // Convert dense tensor to various sparse tensors. 71 // 72 %0 = sparse_tensor.convert %t : tensor<10x8xf64> to tensor<10x8xf64, #Dense> 73 %1 = sparse_tensor.convert %t : tensor<10x8xf64> to tensor<10x8xf64, #CSR> 74 %2 = sparse_tensor.convert %t : tensor<10x8xf64> to tensor<10x8xf64, #DCSR> 75 %3 = sparse_tensor.convert %t : tensor<10x8xf64> to tensor<10x8xf64, #CSC> 76 %4 = sparse_tensor.convert %t : tensor<10x8xf64> to tensor<10x8xf64, #DCSC> 77 78 // 79 // Inspect storage scheme of Dense. 80 // 81 // CHECK: ( 1, 0, 2, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 82 // CHECK-SAME: 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 83 // CHECK-SAME: 0, 0, 0, 0, 6, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 9, 84 // CHECK-SAME: 0, 0, 10, 0, 0, 0, 11, 12, 0, 13, 14, 0, 0, 0, 15, 16, 85 // CHECK-SAME: 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 0 ) 86 // 87 %5 = sparse_tensor.values %0 : tensor<10x8xf64, #Dense> to memref<?xf64> 88 %6 = vector.transfer_read %5[%c0], %d0: memref<?xf64>, vector<80xf64> 89 vector.print %6 : vector<80xf64> 90 91 // 92 // Inspect storage scheme of CSR. 93 // 94 // pointers(1) 95 // indices(1) 96 // values 97 // 98 // CHECK: ( 0, 3, 3, 4, 5, 6, 9, 12, 16, 16, 17 ) 99 // CHECK: ( 0, 2, 7, 2, 3, 4, 1, 2, 7, 2, 6, 7, 1, 2, 6, 7, 6 ) 100 // CHECK: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 ) 101 // 102 %7 = sparse_tensor.pointers %1, %c1 : tensor<10x8xf64, #CSR> to memref<?xindex> 103 %8 = vector.transfer_read %7[%c0], %c0: memref<?xindex>, vector<11xindex> 104 vector.print %8 : vector<11xindex> 105 %9 = sparse_tensor.indices %1, %c1 : tensor<10x8xf64, #CSR> to memref<?xindex> 106 %10 = vector.transfer_read %9[%c0], %c0: memref<?xindex>, vector<17xindex> 107 vector.print %10 : vector<17xindex> 108 %11 = sparse_tensor.values %1 : tensor<10x8xf64, #CSR> to memref<?xf64> 109 %12 = vector.transfer_read %11[%c0], %d0: memref<?xf64>, vector<17xf64> 110 vector.print %12 : vector<17xf64> 111 112 // 113 // Inspect storage scheme of DCSR. 114 // 115 // pointers(0) 116 // indices(0) 117 // pointers(1) 118 // indices(1) 119 // values 120 // 121 // CHECK: ( 0, 8 ) 122 // CHECK: ( 0, 2, 3, 4, 5, 6, 7, 9 ) 123 // CHECK: ( 0, 3, 4, 5, 6, 9, 12, 16, 17 ) 124 // CHECK: ( 0, 2, 7, 2, 3, 4, 1, 2, 7, 2, 6, 7, 1, 2, 6, 7, 6 ) 125 // CHECK: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 ) 126 // 127 %13 = sparse_tensor.pointers %2, %c0 : tensor<10x8xf64, #DCSR> to memref<?xindex> 128 %14 = vector.transfer_read %13[%c0], %c0: memref<?xindex>, vector<2xindex> 129 vector.print %14 : vector<2xindex> 130 %15 = sparse_tensor.indices %2, %c0 : tensor<10x8xf64, #DCSR> to memref<?xindex> 131 %16 = vector.transfer_read %15[%c0], %c0: memref<?xindex>, vector<8xindex> 132 vector.print %16 : vector<8xindex> 133 %17 = sparse_tensor.pointers %2, %c1 : tensor<10x8xf64, #DCSR> to memref<?xindex> 134 %18 = vector.transfer_read %17[%c0], %c0: memref<?xindex>, vector<9xindex> 135 vector.print %18 : vector<9xindex> 136 %19 = sparse_tensor.indices %2, %c1 : tensor<10x8xf64, #DCSR> to memref<?xindex> 137 %20 = vector.transfer_read %19[%c0], %c0: memref<?xindex>, vector<17xindex> 138 vector.print %20 : vector<17xindex> 139 %21 = sparse_tensor.values %2 : tensor<10x8xf64, #DCSR> to memref<?xf64> 140 %22 = vector.transfer_read %21[%c0], %d0: memref<?xf64>, vector<17xf64> 141 vector.print %22 : vector<17xf64> 142 143 // 144 // Inspect storage scheme of CSC. 145 // 146 // pointers(1) 147 // indices(1) 148 // values 149 // 150 // CHECK: ( 0, 1, 3, 8, 9, 10, 10, 13, 17 ) 151 // CHECK: ( 0, 5, 7, 0, 2, 5, 6, 7, 3, 4, 6, 7, 9, 0, 5, 6, 7 ) 152 // CHECK: ( 1, 7, 13, 2, 4, 8, 10, 14, 5, 6, 11, 15, 17, 3, 9, 12, 16 ) 153 // 154 %23 = sparse_tensor.pointers %3, %c1 : tensor<10x8xf64, #CSC> to memref<?xindex> 155 %24 = vector.transfer_read %23[%c0], %c0: memref<?xindex>, vector<9xindex> 156 vector.print %24 : vector<9xindex> 157 %25 = sparse_tensor.indices %3, %c1 : tensor<10x8xf64, #CSC> to memref<?xindex> 158 %26 = vector.transfer_read %25[%c0], %c0: memref<?xindex>, vector<17xindex> 159 vector.print %26 : vector<17xindex> 160 %27 = sparse_tensor.values %3 : tensor<10x8xf64, #CSC> to memref<?xf64> 161 %28 = vector.transfer_read %27[%c0], %d0: memref<?xf64>, vector<17xf64> 162 vector.print %28 : vector<17xf64> 163 164 // 165 // Inspect storage scheme of DCSC. 166 // 167 // pointers(0) 168 // indices(0) 169 // pointers(1) 170 // indices(1) 171 // values 172 // 173 // CHECK: ( 0, 7 ) 174 // CHECK: ( 0, 1, 2, 3, 4, 6, 7 ) 175 // CHECK: ( 0, 1, 3, 8, 9, 10, 13, 17 ) 176 // CHECK: ( 0, 5, 7, 0, 2, 5, 6, 7, 3, 4, 6, 7, 9, 0, 5, 6, 7 ) 177 // CHECK: ( 1, 7, 13, 2, 4, 8, 10, 14, 5, 6, 11, 15, 17, 3, 9, 12, 16 ) 178 // 179 %29 = sparse_tensor.pointers %4, %c0 : tensor<10x8xf64, #DCSC> to memref<?xindex> 180 %30 = vector.transfer_read %29[%c0], %c0: memref<?xindex>, vector<2xindex> 181 vector.print %30 : vector<2xindex> 182 %31 = sparse_tensor.indices %4, %c0 : tensor<10x8xf64, #DCSC> to memref<?xindex> 183 %32 = vector.transfer_read %31[%c0], %c0: memref<?xindex>, vector<7xindex> 184 vector.print %32 : vector<7xindex> 185 %33 = sparse_tensor.pointers %4, %c1 : tensor<10x8xf64, #DCSC> to memref<?xindex> 186 %34 = vector.transfer_read %33[%c0], %c0: memref<?xindex>, vector<8xindex> 187 vector.print %34 : vector<8xindex> 188 %35 = sparse_tensor.indices %4, %c1 : tensor<10x8xf64, #DCSC> to memref<?xindex> 189 %36 = vector.transfer_read %35[%c0], %c0: memref<?xindex>, vector<17xindex> 190 vector.print %36 : vector<17xindex> 191 %37 = sparse_tensor.values %4 : tensor<10x8xf64, #DCSC> to memref<?xf64> 192 %38 = vector.transfer_read %37[%c0], %d0: memref<?xf64>, vector<17xf64> 193 vector.print %38 : vector<17xf64> 194 195 return 196 } 197} 198