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1// RUN: mlir-opt %s --sparse-reinterpret-map --sparsification --canonicalize --cse | FileCheck %s2 3#DCSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed, d1 : compressed) }>4#SparseTensor = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : compressed, d1 : compressed, d2 : compressed) }>5 6#trait = {7 indexing_maps = [8 affine_map<(d0, d1, d2) -> (d0, d2)>,9 affine_map<(d0, d1, d2) -> (d0, d1, d2)>10 ],11 iterator_types = ["parallel", "parallel", "parallel"]12}13 14// CHECK-LABEL: @main(15// CHECK-SAME: %[[TMP_arg0:.*]]: tensor<4x5xi32,16// CHECK-DAG: %[[TMP_c3:.*]] = arith.constant 3 : index17// CHECK-DAG: %[[TMP_c0:.*]] = arith.constant 0 : index18// CHECK-DAG: %[[TMP_c1:.*]] = arith.constant 1 : index19// CHECK-DAG: %[[TMP_0:.*]] = tensor.empty()20// CHECK-DAG: %[[TMP_1:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 0 : index}21// CHECK-DAG: %[[TMP_2:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 0 : index}22// CHECK-DAG: %[[TMP_3:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 1 : index}23// CHECK-DAG: %[[TMP_4:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 1 : index}24// CHECK-DAG: %[[TMP_5:.*]] = sparse_tensor.values %[[TMP_arg0]]25// CHECK: %[[TMP_6:.*]] = memref.load %[[TMP_1]][%[[TMP_c0]]] : memref<?xindex>26// CHECK: %[[TMP_7:.*]] = memref.load %[[TMP_1]][%[[TMP_c1]]] : memref<?xindex>27// CHECK: %[[T:.*]] = scf.for %[[TMP_arg1:.*]] = %[[TMP_6]] to %[[TMP_7]] step %[[TMP_c1]] {{.*}} {28// CHECK: %[[TMP_9:.*]] = memref.load %[[TMP_2]][%[[TMP_arg1]]] : memref<?xindex>29// CHECK: %[[L1:.*]] = scf.for %[[TMP_arg2:.*]] = %[[TMP_c0]] to %[[TMP_c3]] step %[[TMP_c1]] {{.*}} {30// CHECK: %[[TMP_10:.*]] = memref.load %[[TMP_3]][%[[TMP_arg1]]] : memref<?xindex>31// CHECK: %[[TMP_11:.*]] = arith.addi %[[TMP_arg1]], %[[TMP_c1]] : index32// CHECK: %[[TMP_12:.*]] = memref.load %[[TMP_3]][%[[TMP_11]]] : memref<?xindex>33// CHECK: %[[L2:.*]] = scf.for %[[TMP_arg3:.*]] = %[[TMP_10]] to %[[TMP_12]] step %[[TMP_c1]] {{.*}} {34// CHECK: %[[TMP_13:.*]] = memref.load %[[TMP_4]][%[[TMP_arg3]]] : memref<?xindex>35// CHECK: %[[TMP_14:.*]] = memref.load %[[TMP_5]][%[[TMP_arg3]]] : memref<?xi32>36// CHECK: %[[Y:.*]] = tensor.insert %[[TMP_14]] into %{{.*}}[%[[TMP_9]], %[[TMP_arg2]], %[[TMP_13]]]37// CHECK: scf.yield %[[Y]]38// CHECK: }39// CHECK: scf.yield %[[L2]]40// CHECK: }41// CHECK: scf.yield %[[L1]]42// CHECK: }43// CHECK: %[[TMP_8:.*]] = sparse_tensor.load %[[T]] hasInserts44// CHECK: return %[[TMP_8]]45module @func_sparse {46 func.func public @main(%arg0: tensor<4x5xi32, #DCSR>) -> tensor<4x3x5xi32, #SparseTensor> {47 %0 = tensor.empty() : tensor<4x3x5xi32, #SparseTensor>48 %1 = linalg.generic #trait49 ins(%arg0 : tensor<4x5xi32, #DCSR>) outs(%0 : tensor<4x3x5xi32, #SparseTensor>) {50 ^bb0(%in: i32, %out: i32):51 linalg.yield %in : i3252 } -> tensor<4x3x5xi32, #SparseTensor>53 return %1 : tensor<4x3x5xi32, #SparseTensor>54 }55}56