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1// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification | FileCheck %s2 3#SM = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>4 5#trait = {6 indexing_maps = [7 affine_map<(i,j) -> (i,j)> // A8 ],9 iterator_types = ["parallel", "parallel"],10 doc = "A(i,j) += 2.0 where A(i,j) != 0"11}12 13module {14 // Example of a semi-ring operation that only adds a15 // constant at stored values (something that would16 // typically not sparsify since it would densify the17 // implicit zeros in the normal case). The sparse18 // compiler should see that this is a "simply dynamic"19 // operation, and the values can be change "in-place".20 //21 // CHECK-LABEL: func.func @add_only_where_nonzero(22 // CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse{{[0-9]*}}>) -> tensor<8x8xf64, #sparse{{[0-9]*}}> {23 // CHECK-DAG: %[[VAL_1:.*]] = arith.constant 8 : index24 // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index25 // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index26 // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2.000000e+00 : f6427 // CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>28 // CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>29 // CHECK: scf.for %[[VAL_7:.*]] = %[[VAL_2]] to %[[VAL_1]] step %[[VAL_3]] {30 // CHECK: %[[VAL_8:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_7]]] : memref<?xindex>31 // CHECK: %[[VAL_9:.*]] = arith.addi %[[VAL_7]], %[[VAL_3]] : index32 // CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_9]]] : memref<?xindex>33 // CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_8]] to %[[VAL_10]] step %[[VAL_3]] {34 // CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_11]]] : memref<?xf64>35 // CHECK: %[[VAL_13:.*]] = arith.addf %[[VAL_12]], %[[VAL_4]] : f6436 // CHECK: memref.store %[[VAL_13]], %[[VAL_6]]{{\[}}%[[VAL_11]]] : memref<?xf64>37 // CHECK: } {"Emitted from" = "linalg.generic"}38 // CHECK: } {"Emitted from" = "linalg.generic"}39 // CHECK: %[[VAL_14:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}>40 // CHECK: return %[[VAL_14]] : tensor<8x8xf64, #sparse{{[0-9]*}}>41 // CHECK: }42 func.func @add_only_where_nonzero(%argA: tensor<8x8xf64, #SM>) -> tensor<8x8xf64, #SM> {43 %c = arith.constant 2.0 : f6444 %result = linalg.generic #trait45 outs(%argA: tensor<8x8xf64, #SM>) {46 ^bb(%a: f64):47 %u = sparse_tensor.unary %a : f64 to f6448 present={49 ^bb0(%p: f64):50 %add = arith.addf %p, %c : f6451 sparse_tensor.yield %add : f6452 }53 absent={}54 linalg.yield %u : f6455 } -> tensor<8x8xf64, #SM>56 return %result : tensor<8x8xf64, #SM>57 }58}59