| // RUN: mlir-opt %s --sparse-reinterpret-map -sparsification | FileCheck %s |
| |
| // |
| // A contrived example where the sparse tensor B is only |
| // used in the linalg op to determine the number of iterations |
| // for the k-loop. This is included to make sure the sparse |
| // compiler still generates the correct loop nest for this case. |
| // |
| |
| #SM = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }> |
| |
| #trait = { |
| indexing_maps = [ |
| affine_map<(i,j,k) -> (i,j)>, // A |
| affine_map<(i,j,k) -> (k,j)>, // B |
| affine_map<(i,j,k) -> (i,j)> // S_out |
| ], |
| iterator_types = ["parallel", "parallel", "reduction"], |
| doc = "C(i,j) = SUM_k A(i,j)" |
| } |
| |
| // CHECK-LABEL: func.func @b_ununsed( |
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<2x4xf64>, |
| // CHECK-SAME: %[[VAL_1:.*]]: tensor<8x4xf64, #sparse{{[0-9]*}}>, |
| // CHECK-SAME: %[[VAL_2:.*]]: tensor<2x4xf64>) -> tensor<2x4xf64> { |
| // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 8 : index |
| // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2 : index |
| // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 4 : index |
| // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index |
| // CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : memref<2x4xf64> |
| // CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_2]] : memref<2x4xf64> |
| // CHECK: scf.for %[[VAL_10:.*]] = %[[VAL_6]] to %[[VAL_4]] step %[[VAL_7]] { |
| // CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_6]] to %[[VAL_3]] step %[[VAL_7]] { |
| // CHECK: scf.for %[[VAL_12:.*]] = %[[VAL_6]] to %[[VAL_5]] step %[[VAL_7]] { |
| // CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_10]], %[[VAL_12]]] : memref<2x4xf64> |
| // CHECK: %[[VAL_14:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_10]], %[[VAL_12]]] : memref<2x4xf64> |
| // CHECK: %[[VAL_15:.*]] = arith.addf %[[VAL_13]], %[[VAL_14]] : f64 |
| // CHECK: memref.store %[[VAL_15]], %[[VAL_9]]{{\[}}%[[VAL_10]], %[[VAL_12]]] : memref<2x4xf64> |
| // CHECK: } |
| // CHECK: } |
| // CHECK: } |
| // CHECK: %[[VAL_16:.*]] = bufferization.to_tensor %[[VAL_9]] : memref<2x4xf64> |
| // CHECK: return %[[VAL_16]] : tensor<2x4xf64> |
| // CHECK: } |
| func.func @b_ununsed(%argA: tensor<2x4xf64>, |
| %argB: tensor<8x4xf64, #SM>, |
| %argC: tensor<2x4xf64>) -> tensor<2x4xf64> { |
| %result = linalg.generic #trait |
| ins(%argA, %argB: tensor<2x4xf64>, tensor<8x4xf64, #SM>) |
| outs(%argC: tensor<2x4xf64>) { |
| ^bb(%a: f64, %b: f64, %c: f64): |
| %0 = arith.addf %c, %a : f64 |
| linalg.yield %0 : f64 |
| } -> tensor<2x4xf64> |
| return %result : tensor<2x4xf64> |
| } |
