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1// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification | FileCheck %s2 3#map = affine_map<(d0, d1, d2) -> (d0, d1, d2)>4#BCSR = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : batch, d1 : dense, d2 : compressed)}>5 6// CHECK-LABEL: func.func @main(7// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x4x2xf32, #sparse{{[0-9]*}}>) -> tensor<8x4x2xf32> {8// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 1 : index9// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index10// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0.000000e+00 : f3211// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 4 : index12// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 8 : index13// CHECK-DAG: %[[VAL_6:.*]] = tensor.empty() : tensor<8x4x2xf32>14// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<8x4x2xf32, #sparse{{[0-9]*}}> to memref<8x?xindex>15// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<8x4x2xf32, #sparse{{[0-9]*}}> to memref<8x?xindex>16// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x4x2xf32, #sparse{{[0-9]*}}> to memref<8x?xf32>17// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_buffer %[[VAL_6]] : tensor<8x4x2xf32>18// CHECK-DAG: linalg.fill ins(%[[VAL_3]] : f32) outs(%[[VAL_10]] : memref<8x4x2xf32>)19// CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_2]] to %[[VAL_5]] step %[[VAL_1]] {20// CHECK: scf.for %[[VAL_12:.*]] = %[[VAL_2]] to %[[VAL_4]] step %[[VAL_1]] {21// CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_11]], %[[VAL_12]]] : memref<8x?xindex>22// CHECK: %[[VAL_14:.*]] = arith.addi %[[VAL_12]], %[[VAL_1]] : index23// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_11]], %[[VAL_14]]] : memref<8x?xindex>24// CHECK: scf.for %[[VAL_16:.*]] = %[[VAL_13]] to %[[VAL_15]] step %[[VAL_1]] {25// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_11]], %[[VAL_16]]] : memref<8x?xindex>26// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_11]], %[[VAL_16]]] : memref<8x?xf32>27// CHECK: %[[VAL_19:.*]] = arith.negf %[[VAL_18]] : f3228// CHECK: memref.store %[[VAL_19]], %[[VAL_10]]{{\[}}%[[VAL_11]], %[[VAL_12]], %[[VAL_17]]] : memref<8x4x2xf32>29// CHECK: }30// CHECK: }31// CHECK: }32// CHECK: %[[VAL_20:.*]] = bufferization.to_tensor %[[VAL_10]] : memref<8x4x2xf32>33// CHECK: return %[[VAL_20]] : tensor<8x4x2xf32>34// CHECK: }35func.func @main(%arg0: tensor<8x4x2xf32, #BCSR>) -> tensor<8x4x2xf32> {36 %0 = tensor.empty() : tensor<8x4x2xf32>37 %1 = linalg.generic {38 indexing_maps = [#map, #map],39 iterator_types = ["parallel", "parallel", "parallel"]40 }41 ins(%arg0 : tensor<8x4x2xf32, #BCSR>)42 outs(%0 : tensor<8x4x2xf32>) {43 ^bb0(%in: f32, %out: f32):44 %2 = arith.negf %in : f3245 linalg.yield %2 : f3246 } -> tensor<8x4x2xf32>47 return %1 : tensor<8x4x2xf32>48}49