361 lines · plain
1// RUN: mlir-opt %s \2// RUN: --linalg-generalize-named-ops --linalg-fuse-elementwise-ops \3// RUN: --sparse-reinterpret-map --sparsification | FileCheck %s4 5#SparseVector = #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>6 7#DCSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed, d1 : compressed) }>8 9// CHECK-LABEL: func.func @matmul1(10// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32, #sparse{{[0-9]*}}>,11// CHECK-SAME: %[[VAL_1:.*]]: tensor<20x30xf32>,12// CHECK-SAME: %[[VAL_2:.*]]: tensor<10x30xf32>) -> tensor<10x30xf32> {13// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 30 : index14// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index15// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index16// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>17// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>18// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>19// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>20// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xf32>21// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_buffer %[[VAL_1]] : tensor<20x30xf32> to memref<20x30xf32>22// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_buffer %[[VAL_2]] : tensor<10x30xf32> to memref<10x30xf32>23// CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>24// CHECK: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_5]]] : memref<?xindex>25// CHECK: scf.for %[[VAL_15:.*]] = %[[VAL_13]] to %[[VAL_14]] step %[[VAL_5]] {26// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_15]]] : memref<?xindex>27// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_15]]] : memref<?xindex>28// CHECK: %[[VAL_18:.*]] = arith.addi %[[VAL_15]], %[[VAL_5]] : index29// CHECK: %[[VAL_19:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_18]]] : memref<?xindex>30// CHECK: scf.for %[[VAL_20:.*]] = %[[VAL_17]] to %[[VAL_19]] step %[[VAL_5]] {31// CHECK: %[[VAL_21:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<?xindex>32// CHECK: %[[VAL_22:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_20]]] : memref<?xf32>33// CHECK: scf.for %[[VAL_23:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {34// CHECK: %[[VAL_24:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_16]], %[[VAL_23]]] : memref<10x30xf32>35// CHECK: %[[VAL_25:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_21]], %[[VAL_23]]] : memref<20x30xf32>36// CHECK: %[[VAL_26:.*]] = arith.mulf %[[VAL_22]], %[[VAL_25]] : f3237// CHECK: %[[VAL_27:.*]] = arith.addf %[[VAL_24]], %[[VAL_26]] : f3238// CHECK: memref.store %[[VAL_27]], %[[VAL_12]]{{\[}}%[[VAL_16]], %[[VAL_23]]] : memref<10x30xf32>39// CHECK: }40// CHECK: }41// CHECK: }42// CHECK: %[[VAL_28:.*]] = bufferization.to_tensor %[[VAL_12]] : memref<10x30xf32>43// CHECK: return %[[VAL_28]] : tensor<10x30xf32>44// CHECK: }45func.func @matmul1(%a: tensor<10x20xf32, #DCSR>,46 %b: tensor<20x30xf32>,47 %c: tensor<10x30xf32>) -> tensor<10x30xf32> {48 %0 = linalg.matmul49 ins(%a, %b: tensor<10x20xf32, #DCSR>, tensor<20x30xf32>)50 outs(%c: tensor<10x30xf32>) -> tensor<10x30xf32>51 return %0 : tensor<10x30xf32>52}53 54// CHECK-LABEL: func.func @matmul_sparse_rhs(55// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32>,56// CHECK-SAME: %[[VAL_1:.*]]: tensor<20x30xf32, #sparse{{[0-9]*}}>,57// CHECK-SAME: %[[VAL_2:.*]]: tensor<10x30xf32>) -> tensor<10x30xf32> {58// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 10 : index59// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index60// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index61// CHECK-DAG: %[[VAL_6:.*]] = bufferization.to_buffer %[[VAL_0]] : tensor<10x20xf32> to memref<10x20xf32>62// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index}63// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index}64// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index}65// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index}66// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]]67// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_buffer %[[VAL_2]] : tensor<10x30xf32> to memref<10x30xf32>68// CHECK: scf.for %[[VAL_13:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {69// CHECK: %[[VAL_14:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex>70// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_5]]] : memref<?xindex>71// CHECK: scf.for %[[VAL_16:.*]] = %[[VAL_14]] to %[[VAL_15]] step %[[VAL_5]] {72// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_16]]] : memref<?xindex>73// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_13]], %[[VAL_17]]] : memref<10x20xf32>74// CHECK: %[[VAL_19:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_16]]] : memref<?xindex>75// CHECK: %[[VAL_20:.*]] = arith.addi %[[VAL_16]], %[[VAL_5]] : index76// CHECK: %[[VAL_21:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<?xindex>77// CHECK: scf.for %[[VAL_22:.*]] = %[[VAL_19]] to %[[VAL_21]] step %[[VAL_5]] {78// CHECK: %[[VAL_23:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_22]]] : memref<?xindex>79// CHECK: %[[VAL_24:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_13]], %[[VAL_23]]] : memref<10x30xf32>80// CHECK: %[[VAL_25:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_22]]] : memref<?xf32>81// CHECK: %[[VAL_26:.*]] = arith.mulf %[[VAL_18]], %[[VAL_25]] : f3282// CHECK: %[[VAL_27:.*]] = arith.addf %[[VAL_24]], %[[VAL_26]] : f3283// CHECK: memref.store %[[VAL_27]], %[[VAL_12]]{{\[}}%[[VAL_13]], %[[VAL_23]]] : memref<10x30xf32>84// CHECK: } {"Emitted from" = "linalg.generic"}85// CHECK: } {"Emitted from" = "linalg.generic"}86// CHECK: } {"Emitted from" = "linalg.generic"}87// CHECK: %[[VAL_28:.*]] = bufferization.to_tensor %[[VAL_12]] : memref<10x30xf32>88// CHECK: return %[[VAL_28]] : tensor<10x30xf32>89// CHECK: }90// IMPORTANT! Ensures that dense input are visit in row-major order.91func.func @matmul_sparse_rhs(%a: tensor<10x20xf32>,92 %b: tensor<20x30xf32, #DCSR>,93 %c: tensor<10x30xf32>) -> tensor<10x30xf32> {94 %0 = linalg.matmul95 ins(%a, %b: tensor<10x20xf32>, tensor<20x30xf32,#DCSR>)96 outs(%c: tensor<10x30xf32>) -> tensor<10x30xf32>97 return %0 : tensor<10x30xf32>98}99 100 101//102// Computes C = A x B with all matrices sparse (SpMSpM) in DCSR.103//104// CHECK-LABEL: func.func @matmul2(105// CHECK-SAME: %[[VAL_0:.*]]: tensor<4x8xf64, #sparse{{[0-9]*}}>,106// CHECK-SAME: %[[VAL_1:.*]]: tensor<8x4xf64, #sparse{{[0-9]*}}>) -> tensor<4x4xf64, #sparse{{[0-9]*}}> {107// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index108// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index109// CHECK-DAG: %[[VAL_4:.*]] = arith.constant false110// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true111// CHECK-DAG: %[[VAL_6:.*]] = tensor.empty() : tensor<4x4xf64, #sparse{{[0-9]*}}>112// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<4x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>113// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<4x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>114// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<4x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>115// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<4x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>116// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<4x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>117// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<8x4xf64, #sparse{{[0-9]*}}> to memref<?xindex>118// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<8x4xf64, #sparse{{[0-9]*}}> to memref<?xindex>119// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<8x4xf64, #sparse{{[0-9]*}}> to memref<?xindex>120// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<8x4xf64, #sparse{{[0-9]*}}> to memref<?xindex>121// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<8x4xf64, #sparse{{[0-9]*}}> to memref<?xf64>122// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_2]]] : memref<?xindex>123// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_3]]] : memref<?xindex>124// CHECK: %[[VAL_19:.*]] = scf.for %[[VAL_20:.*]] = %[[VAL_17]] to %[[VAL_18]] step %[[VAL_3]] iter_args(%[[VAL_21:.*]] = %[[VAL_6]]) -> (tensor<4x4xf64, #sparse{{[0-9]*}}>) {125// CHECK: %[[VAL_22:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_20]]] : memref<?xindex>126// CHECK: %[[VAL_23:.*]], %[[VAL_24:.*]], %[[VAL_25:.*]], %[[VAL_26:.*]] = sparse_tensor.expand %[[VAL_6]] : tensor<4x4xf64, #sparse{{[0-9]*}}> to memref<?xf64>, memref<?xi1>, memref<?xindex>127// CHECK: %[[VAL_27:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<?xindex>128// CHECK: %[[VAL_28:.*]] = arith.addi %[[VAL_20]], %[[VAL_3]] : index129// CHECK: %[[VAL_29:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_28]]] : memref<?xindex>130// CHECK: %[[VAL_30:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_2]]] : memref<?xindex>131// CHECK: %[[VAL_31:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_3]]] : memref<?xindex>132// CHECK: %[[VAL_32:.*]]:4 = scf.while (%[[VAL_33:.*]] = %[[VAL_27]], %[[VAL_34:.*]] = %[[VAL_30]], %[[VAL_35:.*]] = %[[VAL_26]], %[[VAL_36:.*]] = %[[VAL_21]]) : (index, index, index, tensor<4x4xf64, #sparse{{[0-9]*}}>) -> (index, index, index, tensor<4x4xf64, #sparse{{[0-9]*}}>) {133// CHECK: %[[VAL_37:.*]] = arith.cmpi ult, %[[VAL_33]], %[[VAL_29]] : index134// CHECK: %[[VAL_38:.*]] = arith.cmpi ult, %[[VAL_34]], %[[VAL_31]] : index135// CHECK: %[[VAL_39:.*]] = arith.andi %[[VAL_37]], %[[VAL_38]] : i1136// CHECK: scf.condition(%[[VAL_39]]) %[[VAL_33]], %[[VAL_34]], %[[VAL_35]], %[[VAL_36]] : index, index, index, tensor<4x4xf64, #sparse{{[0-9]*}}>137// CHECK: } do {138// CHECK: ^bb0(%[[VAL_40:.*]]: index, %[[VAL_41:.*]]: index, %[[VAL_42:.*]]: index, %[[VAL_43:.*]]: tensor<4x4xf64, #sparse{{[0-9]*}}>):139// CHECK: %[[VAL_44:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_40]]] : memref<?xindex>140// CHECK: %[[VAL_45:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_41]]] : memref<?xindex>141// CHECK: %[[VAL_46:.*]] = arith.cmpi ult, %[[VAL_45]], %[[VAL_44]] : index142// CHECK: %[[VAL_47:.*]] = arith.select %[[VAL_46]], %[[VAL_45]], %[[VAL_44]] : index143// CHECK: %[[VAL_48:.*]] = arith.cmpi eq, %[[VAL_44]], %[[VAL_47]] : index144// CHECK: %[[VAL_49:.*]] = arith.cmpi eq, %[[VAL_45]], %[[VAL_47]] : index145// CHECK: %[[VAL_50:.*]] = arith.andi %[[VAL_48]], %[[VAL_49]] : i1146// CHECK: %[[VAL_51:.*]]:2 = scf.if %[[VAL_50]] -> (index, tensor<4x4xf64, #sparse{{[0-9]*}}>) {147// CHECK: %[[VAL_52:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_40]]] : memref<?xf64>148// CHECK: %[[VAL_53:.*]] = memref.load %[[VAL_14]]{{\[}}%[[VAL_41]]] : memref<?xindex>149// CHECK: %[[VAL_54:.*]] = arith.addi %[[VAL_41]], %[[VAL_3]] : index150// CHECK: %[[VAL_55:.*]] = memref.load %[[VAL_14]]{{\[}}%[[VAL_54]]] : memref<?xindex>151// CHECK: %[[VAL_56:.*]] = scf.for %[[VAL_57:.*]] = %[[VAL_53]] to %[[VAL_55]] step %[[VAL_3]] iter_args(%[[VAL_58:.*]] = %[[VAL_42]]) -> (index) {152// CHECK: %[[VAL_59:.*]] = memref.load %[[VAL_15]]{{\[}}%[[VAL_57]]] : memref<?xindex>153// CHECK: %[[VAL_60:.*]] = memref.load %[[VAL_23]]{{\[}}%[[VAL_59]]] : memref<?xf64>154// CHECK: %[[VAL_61:.*]] = memref.load %[[VAL_16]]{{\[}}%[[VAL_57]]] : memref<?xf64>155// CHECK: %[[VAL_62:.*]] = arith.mulf %[[VAL_52]], %[[VAL_61]] : f64156// CHECK: %[[VAL_63:.*]] = arith.addf %[[VAL_60]], %[[VAL_62]] : f64157// CHECK: %[[VAL_64:.*]] = memref.load %[[VAL_24]]{{\[}}%[[VAL_59]]] : memref<?xi1>158// CHECK: %[[VAL_65:.*]] = arith.cmpi eq, %[[VAL_64]], %[[VAL_4]] : i1159// CHECK: %[[VAL_66:.*]] = scf.if %[[VAL_65]] -> (index) {160// CHECK: memref.store %[[VAL_5]], %[[VAL_24]]{{\[}}%[[VAL_59]]] : memref<?xi1>161// CHECK: memref.store %[[VAL_59]], %[[VAL_25]]{{\[}}%[[VAL_58]]] : memref<?xindex>162// CHECK: %[[VAL_67:.*]] = arith.addi %[[VAL_58]], %[[VAL_3]] : index163// CHECK: scf.yield %[[VAL_67]] : index164// CHECK: } else {165// CHECK: scf.yield %[[VAL_58]] : index166// CHECK: }167// CHECK: memref.store %[[VAL_63]], %[[VAL_23]]{{\[}}%[[VAL_59]]] : memref<?xf64>168// CHECK: scf.yield %[[VAL_68:.*]] : index169// CHECK: }170// CHECK: scf.yield %[[VAL_69:.*]], %[[VAL_43]] : index, tensor<4x4xf64, #sparse{{[0-9]*}}>171// CHECK: } else {172// CHECK: scf.yield %[[VAL_42]], %[[VAL_43]] : index, tensor<4x4xf64, #sparse{{[0-9]*}}>173// CHECK: }174// CHECK: %[[VAL_70:.*]] = arith.cmpi eq, %[[VAL_44]], %[[VAL_47]] : index175// CHECK: %[[VAL_71:.*]] = arith.addi %[[VAL_40]], %[[VAL_3]] : index176// CHECK: %[[VAL_72:.*]] = arith.select %[[VAL_70]], %[[VAL_71]], %[[VAL_40]] : index177// CHECK: %[[VAL_73:.*]] = arith.cmpi eq, %[[VAL_45]], %[[VAL_47]] : index178// CHECK: %[[VAL_74:.*]] = arith.addi %[[VAL_41]], %[[VAL_3]] : index179// CHECK: %[[VAL_75:.*]] = arith.select %[[VAL_73]], %[[VAL_74]], %[[VAL_41]] : index180// CHECK: scf.yield %[[VAL_72]], %[[VAL_75]], %[[VAL_76:.*]]#0, %[[VAL_76]]#1 : index, index, index, tensor<4x4xf64, #sparse{{[0-9]*}}>181// CHECK: }182// CHECK: %[[VAL_77:.*]] = sparse_tensor.compress %[[VAL_23]], %[[VAL_24]], %[[VAL_25]], %[[VAL_78:.*]]#2 into %[[VAL_78]]#3{{\[}}%[[VAL_22]]] : memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<4x4xf64, #sparse{{[0-9]*}}>183// CHECK: scf.yield %[[VAL_77]] : tensor<4x4xf64, #sparse{{[0-9]*}}>184// CHECK: }185// CHECK: %[[VAL_79:.*]] = sparse_tensor.load %[[VAL_80:.*]] hasInserts : tensor<4x4xf64, #sparse{{[0-9]*}}>186// CHECK: return %[[VAL_79]] : tensor<4x4xf64, #sparse{{[0-9]*}}>187// CHECK: }188func.func @matmul2(%A: tensor<4x8xf64, #DCSR>,189 %B: tensor<8x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR> {190 %c4 = arith.constant 4 : index191 %C = tensor.empty() : tensor<4x4xf64, #DCSR>192 %D = linalg.matmul193 ins(%A, %B: tensor<4x8xf64, #DCSR>, tensor<8x4xf64, #DCSR>)194 outs(%C: tensor<4x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR>195 return %D: tensor<4x4xf64, #DCSR>196}197 198 199// CHECK-LABEL: func.func @conv2d(200// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xi32>,201// CHECK-SAME: %[[VAL_1:.*]]: tensor<3x3xi32, #sparse{{[0-9]*}}>,202// CHECK-SAME: %[[VAL_2:.*]]: tensor<6x6xi32>) -> tensor<6x6xi32> {203// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 6 : index204// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index205// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index206// CHECK-DAG: %[[VAL_6:.*]] = bufferization.to_buffer %[[VAL_0]] : tensor<8x8xi32> to memref<8x8xi32>207// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<3x3xi32, #sparse{{[0-9]*}}> to memref<?xindex>208// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<3x3xi32, #sparse{{[0-9]*}}> to memref<?xindex>209// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<3x3xi32, #sparse{{[0-9]*}}> to memref<?xindex>210// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<3x3xi32, #sparse{{[0-9]*}}> to memref<?xindex>211// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<3x3xi32, #sparse{{[0-9]*}}> to memref<?xi32>212// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_buffer %[[VAL_2]] : tensor<6x6xi32> to memref<6x6xi32>213// CHECK: scf.for %[[VAL_13:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {214// CHECK: scf.for %[[VAL_14:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {215// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_13]], %[[VAL_14]]] : memref<6x6xi32>216// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex>217// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_5]]] : memref<?xindex>218// CHECK: %[[VAL_18:.*]] = scf.for %[[VAL_19:.*]] = %[[VAL_16]] to %[[VAL_17]] step %[[VAL_5]] iter_args(%[[VAL_20:.*]] = %[[VAL_15]]) -> (i32) {219// CHECK: %[[VAL_21:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_19]]] : memref<?xindex>220// CHECK: %[[VAL_22:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_19]]] : memref<?xindex>221// CHECK: %[[VAL_23:.*]] = arith.addi %[[VAL_19]], %[[VAL_5]] : index222// CHECK: %[[VAL_24:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_23]]] : memref<?xindex>223// CHECK: %[[VAL_25:.*]] = scf.for %[[VAL_26:.*]] = %[[VAL_22]] to %[[VAL_24]] step %[[VAL_5]] iter_args(%[[VAL_27:.*]] = %[[VAL_20]]) -> (i32) {224// CHECK: %[[VAL_28:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_26]]] : memref<?xindex>225// CHECK: %[[VAL_29:.*]] = arith.addi %[[VAL_13]], %[[VAL_21]] : index226// CHECK: %[[VAL_30:.*]] = arith.addi %[[VAL_14]], %[[VAL_28]] : index227// CHECK: %[[VAL_31:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_29]], %[[VAL_30]]] : memref<8x8xi32>228// CHECK: %[[VAL_32:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_26]]] : memref<?xi32>229// CHECK: %[[VAL_33:.*]] = arith.muli %[[VAL_31]], %[[VAL_32]] : i32230// CHECK: %[[VAL_34:.*]] = arith.addi %[[VAL_27]], %[[VAL_33]] : i32231// CHECK: scf.yield %[[VAL_34]] : i32232// CHECK: } {"Emitted from" = "linalg.generic"}233// CHECK: scf.yield %[[VAL_25]] : i32234// CHECK: } {"Emitted from" = "linalg.generic"}235// CHECK: memref.store %[[VAL_18]], %[[VAL_12]]{{\[}}%[[VAL_13]], %[[VAL_14]]] : memref<6x6xi32>236// CHECK: } {"Emitted from" = "linalg.generic"}237// CHECK: } {"Emitted from" = "linalg.generic"}238// CHECK: %[[VAL_35:.*]] = bufferization.to_tensor %[[VAL_12]] : memref<6x6xi32>239// CHECK: return %[[VAL_35]] : tensor<6x6xi32>240// CHECK: }241func.func @conv2d(%input: tensor<8x8xi32>,242 %filter: tensor<3x3xi32, #DCSR>,243 %output: tensor<6x6xi32>) -> tensor<6x6xi32> {244 %0 = linalg.conv_2d245 ins (%input, %filter: tensor<8x8xi32>, tensor<3x3xi32, #DCSR>)246 outs (%output: tensor<6x6xi32>) -> tensor<6x6xi32>247 return %0 : tensor<6x6xi32>248}249 250// CHECK-LABEL: func.func @quantized_matmul(251// CHECK-SAME: %[[VAL_0:.*]]: tensor<5x3xi8>,252// CHECK-SAME: %[[VAL_1:.*]]: tensor<3x6xi8, #sparse{{[0-9]*}}>,253// CHECK-SAME: %[[VAL_2:.*]]: tensor<5x6xi64>) -> tensor<5x6xi64> {254// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 5 : index255// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index256// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index257// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 2 : i64258// CHECK-DAG: %[[VAL_7:.*]] = bufferization.to_buffer %[[VAL_0]] : tensor<5x3xi8> to memref<5x3xi8>259// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<3x6xi8, #sparse{{[0-9]*}}> to memref<?xindex>260// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<3x6xi8, #sparse{{[0-9]*}}> to memref<?xindex>261// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<3x6xi8, #sparse{{[0-9]*}}> to memref<?xindex>262// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<3x6xi8, #sparse{{[0-9]*}}> to memref<?xindex>263// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<3x6xi8, #sparse{{[0-9]*}}> to memref<?xi8>264// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_buffer %[[VAL_2]] : tensor<5x6xi64> to memref<5x6xi64>265// CHECK: scf.for %[[VAL_14:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {266// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_4]]] : memref<?xindex>267// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_5]]] : memref<?xindex>268// CHECK: scf.for %[[VAL_17:.*]] = %[[VAL_15]] to %[[VAL_16]] step %[[VAL_5]] {269// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_17]]] : memref<?xindex>270// CHECK: %[[VAL_19:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_14]], %[[VAL_18]]] : memref<5x3xi8>271// CHECK: %[[VAL_20:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_17]]] : memref<?xindex>272// CHECK: %[[VAL_21:.*]] = arith.addi %[[VAL_17]], %[[VAL_5]] : index273// CHECK: %[[VAL_22:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_21]]] : memref<?xindex>274// CHECK: scf.for %[[VAL_23:.*]] = %[[VAL_20]] to %[[VAL_22]] step %[[VAL_5]] {275// CHECK: %[[VAL_24:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_23]]] : memref<?xindex>276// CHECK: %[[VAL_25:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_14]], %[[VAL_24]]] : memref<5x6xi64>277// CHECK: %[[VAL_26:.*]] = arith.extsi %[[VAL_19]] : i8 to i64278// CHECK: %[[VAL_27:.*]] = arith.subi %[[VAL_26]], %[[VAL_6]] : i64279// CHECK: %[[VAL_28:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_23]]] : memref<?xi8>280// CHECK: %[[VAL_29:.*]] = arith.extsi %[[VAL_28]] : i8 to i64281// CHECK: %[[VAL_30:.*]] = arith.muli %[[VAL_27]], %[[VAL_29]] : i64282// CHECK: %[[VAL_31:.*]] = arith.addi %[[VAL_25]], %[[VAL_30]] : i64283// CHECK: memref.store %[[VAL_31]], %[[VAL_13]]{{\[}}%[[VAL_14]], %[[VAL_24]]] : memref<5x6xi64>284// CHECK: } {"Emitted from" = "linalg.generic"}285// CHECK: } {"Emitted from" = "linalg.generic"}286// CHECK: } {"Emitted from" = "linalg.generic"}287// CHECK: %[[VAL_32:.*]] = bufferization.to_tensor %[[VAL_13]] : memref<5x6xi64>288// CHECK: return %[[VAL_32]] : tensor<5x6xi64>289// CHECK: }290func.func @quantized_matmul(%input1: tensor<5x3xi8>,291 %input2: tensor<3x6xi8, #DCSR>,292 %output: tensor<5x6xi64>) -> tensor<5x6xi64> {293 %c0 = arith.constant 0 : i32294 %c2 = arith.constant 2 : i32295 %0 = linalg.quantized_matmul296 ins(%input1, %input2, %c2, %c0 : tensor<5x3xi8>, tensor<3x6xi8, #DCSR>, i32, i32)297 outs(%output : tensor<5x6xi64>) -> tensor<5x6xi64>298 return %0: tensor<5x6xi64>299}300 301// CHECK-LABEL: func.func @sparse_dot(302// CHECK-SAME: %[[VAL_0:.*0]]: tensor<1024xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<1024xf32, #sparse{{[0-9]*}}>,303// CHECK-SAME: %[[VAL_2:.*2]]: tensor<f32>) -> tensor<f32> {304// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index305// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index306// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xindex>307// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xindex>308// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xf32>309// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xindex>310// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xindex>311// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xf32>312// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_buffer %[[VAL_2]] : tensor<f32> to memref<f32>313// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_11]][] : memref<f32>314// CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>315// CHECK: %[[VAL_14:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_4]]] : memref<?xindex>316// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_3]]] : memref<?xindex>317// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_4]]] : memref<?xindex>318// CHECK: %[[VAL_17:.*]]:3 = scf.while (%[[VAL_18:.*]] = %[[VAL_13]], %[[VAL_19:.*]] = %[[VAL_15]], %[[VAL_20:.*]] = %[[VAL_12]]) : (index, index, f32) -> (index, index, f32) {319// CHECK: %[[VAL_21:.*]] = arith.cmpi ult, %[[VAL_18]], %[[VAL_14]] : index320// CHECK: %[[VAL_22:.*]] = arith.cmpi ult, %[[VAL_19]], %[[VAL_16]] : index321// CHECK: %[[VAL_23:.*]] = arith.andi %[[VAL_21]], %[[VAL_22]] : i1322// CHECK: scf.condition(%[[VAL_23]]) %[[VAL_18]], %[[VAL_19]], %[[VAL_20]] : index, index, f32323// CHECK: } do {324// CHECK: ^bb0(%[[VAL_24:.*]]: index, %[[VAL_25:.*]]: index, %[[VAL_26:.*]]: f32):325// CHECK: %[[VAL_27:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_24]]] : memref<?xindex>326// CHECK: %[[VAL_28:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_25]]] : memref<?xindex>327// CHECK: %[[VAL_29:.*]] = arith.cmpi ult, %[[VAL_28]], %[[VAL_27]] : index328// CHECK: %[[VAL_30:.*]] = arith.select %[[VAL_29]], %[[VAL_28]], %[[VAL_27]] : index329// CHECK: %[[VAL_31:.*]] = arith.cmpi eq, %[[VAL_27]], %[[VAL_30]] : index330// CHECK: %[[VAL_32:.*]] = arith.cmpi eq, %[[VAL_28]], %[[VAL_30]] : index331// CHECK: %[[VAL_33:.*]] = arith.andi %[[VAL_31]], %[[VAL_32]] : i1332// CHECK: %[[VAL_34:.*]] = scf.if %[[VAL_33]] -> (f32) {333// CHECK: %[[VAL_35:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_24]]] : memref<?xf32>334// CHECK: %[[VAL_36:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_25]]] : memref<?xf32>335// CHECK: %[[VAL_37:.*]] = arith.mulf %[[VAL_35]], %[[VAL_36]] : f32336// CHECK: %[[VAL_38:.*]] = arith.addf %[[VAL_26]], %[[VAL_37]] : f32337// CHECK: scf.yield %[[VAL_38]] : f32338// CHECK: } else {339// CHECK: scf.yield %[[VAL_26]] : f32340// CHECK: }341// CHECK: %[[VAL_39:.*]] = arith.cmpi eq, %[[VAL_27]], %[[VAL_30]] : index342// CHECK: %[[VAL_40:.*]] = arith.addi %[[VAL_24]], %[[VAL_4]] : index343// CHECK: %[[VAL_41:.*]] = arith.select %[[VAL_39]], %[[VAL_40]], %[[VAL_24]] : index344// CHECK: %[[VAL_42:.*]] = arith.cmpi eq, %[[VAL_28]], %[[VAL_30]] : index345// CHECK: %[[VAL_43:.*]] = arith.addi %[[VAL_25]], %[[VAL_4]] : index346// CHECK: %[[VAL_44:.*]] = arith.select %[[VAL_42]], %[[VAL_43]], %[[VAL_25]] : index347// CHECK: scf.yield %[[VAL_41]], %[[VAL_44]], %[[VAL_45:.*]] : index, index, f32348// CHECK: }349// CHECK: memref.store %[[VAL_46:.*]]#2, %[[VAL_11]][] : memref<f32>350// CHECK: %[[VAL_47:.*]] = bufferization.to_tensor %[[VAL_11]] : memref<f32>351// CHECK: return %[[VAL_47]] : tensor<f32>352// CHECK: }353func.func @sparse_dot(%a: tensor<1024xf32, #SparseVector>,354 %b: tensor<1024xf32, #SparseVector>,355 %x: tensor<f32>) -> tensor<f32> {356 %dot = linalg.dot ins(%a, %b: tensor<1024xf32, #SparseVector>,357 tensor<1024xf32, #SparseVector>)358 outs(%x: tensor<f32>) -> tensor<f32>359 return %dot : tensor<f32>360}361