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1// RUN: mlir-opt %s --canonicalize --cse | FileCheck %s2 3#SparseVector = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed)}>4 5// CHECK-LABEL: func @sparse_nop_dense2dense_convert(6// CHECK-SAME: %[[A:.*]]: tensor<64xf32>)7// CHECK-NOT: sparse_tensor.convert8// CHECK: return %[[A]] : tensor<64xf32>9func.func @sparse_nop_dense2dense_convert(%arg0: tensor<64xf32>) -> tensor<64xf32> {10 %0 = sparse_tensor.convert %arg0 : tensor<64xf32> to tensor<64xf32>11 return %0 : tensor<64xf32>12}13 14// CHECK-LABEL: func @sparse_dce_convert(15// CHECK-SAME: %[[A:.*]]: tensor<64xf32>)16// CHECK-NOT: sparse_tensor.convert17// CHECK: return18func.func @sparse_dce_convert(%arg0: tensor<64xf32>) {19 %0 = sparse_tensor.convert %arg0 : tensor<64xf32> to tensor<64xf32, #SparseVector>20 return21}22 23// CHECK-LABEL: func @sparse_dce_getters(24// CHECK-SAME: %[[A:.*]]: tensor<64xf32, #sparse{{[0-9]*}}>)25// CHECK-NOT: sparse_tensor.positions26// CHECK-NOT: sparse_tensor.coordinates27// CHECK-NOT: sparse_tensor.values28// CHECK: return29func.func @sparse_dce_getters(%arg0: tensor<64xf32, #SparseVector>) {30 %0 = sparse_tensor.positions %arg0 { level = 0 : index } : tensor<64xf32, #SparseVector> to memref<?xindex>31 %1 = sparse_tensor.coordinates %arg0 { level = 0 : index } : tensor<64xf32, #SparseVector> to memref<?xindex>32 %2 = sparse_tensor.values %arg0 : tensor<64xf32, #SparseVector> to memref<?xf32>33 return34}35 36// CHECK-LABEL: func @sparse_concat_dce(37// CHECK-NOT: sparse_tensor.concatenate38// CHECK: return39func.func @sparse_concat_dce(%arg0: tensor<2xf64, #SparseVector>,40 %arg1: tensor<3xf64, #SparseVector>,41 %arg2: tensor<4xf64, #SparseVector>) {42 %0 = sparse_tensor.concatenate %arg0, %arg1, %arg2 {dimension = 0 : index}43 : tensor<2xf64, #SparseVector>,44 tensor<3xf64, #SparseVector>,45 tensor<4xf64, #SparseVector> to tensor<9xf64, #SparseVector>46 return47}48 49// CHECK-LABEL: func @sparse_get_specifier_dce_fold(50// CHECK-SAME: %[[A0:.*]]: !sparse_tensor.storage_specifier51// CHECK-SAME: %[[A1:.*]]: index,52// CHECK-SAME: %[[A2:.*]]: index)53// CHECK-NOT: sparse_tensor.storage_specifier.set54// CHECK-NOT: sparse_tensor.storage_specifier.get55// CHECK: return %[[A1]]56func.func @sparse_get_specifier_dce_fold(%arg0: !sparse_tensor.storage_specifier<#SparseVector>, %arg1: index, %arg2: index) -> index {57 %0 = sparse_tensor.storage_specifier.set %arg0 lvl_sz at 0 with %arg158 : !sparse_tensor.storage_specifier<#SparseVector>59 %1 = sparse_tensor.storage_specifier.set %0 pos_mem_sz at 0 with %arg260 : !sparse_tensor.storage_specifier<#SparseVector>61 %2 = sparse_tensor.storage_specifier.get %1 lvl_sz at 062 : !sparse_tensor.storage_specifier<#SparseVector>63 return %2 : index64}65 66 67 68#COO = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)}>69 70// CHECK-LABEL: func @sparse_reorder_coo(71// CHECK-SAME: %[[A:.*]]: tensor<?x?xf32, #sparse{{[0-9]*}}>72// CHECK-NOT: %[[R:.*]] = sparse_tensor.reorder_coo73// CHECK: return %[[A]]74func.func @sparse_reorder_coo(%arg0 : tensor<?x?xf32, #COO>) -> tensor<?x?xf32, #COO> {75 %ret = sparse_tensor.reorder_coo quick_sort %arg0 : tensor<?x?xf32, #COO> to tensor<?x?xf32, #COO>76 return %ret : tensor<?x?xf32, #COO>77}78 79 80#BSR = #sparse_tensor.encoding<{81 map = ( i, j ) ->82 ( i floordiv 2 : dense,83 j floordiv 3 : compressed,84 i mod 2 : dense,85 j mod 3 : dense86 )87}>88 89// CHECK-LABEL: func @sparse_crd_translate(90// CHECK-NOT: sparse_tensor.crd_translate91func.func @sparse_crd_translate(%arg0: index, %arg1: index) -> (index, index) {92 %l0, %l1, %l2, %l3 = sparse_tensor.crd_translate dim_to_lvl [%arg0, %arg1] as #BSR : index, index, index, index93 %d0, %d1 = sparse_tensor.crd_translate lvl_to_dim [%l0, %l1, %l2, %l3] as #BSR : index, index94 return %d0, %d1 : index, index95}96 97// CHECK-LABEL: func.func @sparse_lvl_0(98// CHECK: %[[C5:.*]] = arith.constant 5 : index99// CHECK: return %[[C5]] : index100func.func @sparse_lvl_0(%t : tensor<10x?xi32, #BSR>) -> index {101 %lvl = arith.constant 0 : index102 %l0 = sparse_tensor.lvl %t, %lvl : tensor<10x?xi32, #BSR>103 return %l0 : index104}105 106// CHECK-LABEL: func.func @sparse_lvl_3(107// CHECK: %[[C3:.*]] = arith.constant 3 : index108// CHECK: return %[[C3]] : index109func.func @sparse_lvl_3(%t : tensor<?x?xi32, #BSR>) -> index {110 %lvl = arith.constant 3 : index111 %l0 = sparse_tensor.lvl %t, %lvl : tensor<?x?xi32, #BSR>112 return %l0 : index113}114 115#DSDD = #sparse_tensor.encoding<{116 map = (i, j, k, l) -> (i: dense, j: compressed, k: dense, l: dense)117}>118 119 120// CHECK-LABEL: func.func @sparse_reinterpret_map(121// CHECK-NOT: sparse_tensor.reinterpret_map122func.func @sparse_reinterpret_map(%t0 : tensor<6x12xi32, #BSR>) -> tensor<6x12xi32, #BSR> {123 %t1 = sparse_tensor.reinterpret_map %t0 : tensor<6x12xi32, #BSR>124 to tensor<3x4x2x3xi32, #DSDD>125 %t2 = sparse_tensor.reinterpret_map %t1 : tensor<3x4x2x3xi32, #DSDD>126 to tensor<6x12xi32, #BSR>127 return %t2 : tensor<6x12xi32, #BSR>128}129