| // RUN: mlir-opt %s --sparse-reinterpret-map -sparsification | FileCheck %s |
| |
| #SM = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }> |
| |
| #trait = { |
| indexing_maps = [ |
| affine_map<(i,j) -> (i,j)> // A |
| ], |
| iterator_types = ["parallel", "parallel"], |
| doc = "A(i,j) += 2.0 where A(i,j) != 0" |
| } |
| |
| module { |
| // Example of a semi-ring operation that only adds a |
| // constant at stored values (something that would |
| // typically not sparsify since it would densify the |
| // implicit zeros in the normal case). The sparse |
| // compiler should see that this is a "simply dynamic" |
| // operation, and the values can be change "in-place". |
| // |
| // CHECK-LABEL: func.func @add_only_where_nonzero( |
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse{{[0-9]*}}>) -> tensor<8x8xf64, #sparse{{[0-9]*}}> { |
| // CHECK-DAG: %[[VAL_1:.*]] = arith.constant 8 : index |
| // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index |
| // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2.000000e+00 : f64 |
| // CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex> |
| // CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xf64> |
| // CHECK: scf.for %[[VAL_7:.*]] = %[[VAL_2]] to %[[VAL_1]] step %[[VAL_3]] { |
| // CHECK: %[[VAL_8:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_7]]] : memref<?xindex> |
| // CHECK: %[[VAL_9:.*]] = arith.addi %[[VAL_7]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_9]]] : memref<?xindex> |
| // CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_8]] to %[[VAL_10]] step %[[VAL_3]] { |
| // CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_11]]] : memref<?xf64> |
| // CHECK: %[[VAL_13:.*]] = arith.addf %[[VAL_12]], %[[VAL_4]] : f64 |
| // CHECK: memref.store %[[VAL_13]], %[[VAL_6]]{{\[}}%[[VAL_11]]] : memref<?xf64> |
| // CHECK: } {"Emitted from" = "linalg.generic"} |
| // CHECK: } {"Emitted from" = "linalg.generic"} |
| // CHECK: %[[VAL_14:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}> |
| // CHECK: return %[[VAL_14]] : tensor<8x8xf64, #sparse{{[0-9]*}}> |
| // CHECK: } |
| func.func @add_only_where_nonzero(%argA: tensor<8x8xf64, #SM>) -> tensor<8x8xf64, #SM> { |
| %c = arith.constant 2.0 : f64 |
| %result = linalg.generic #trait |
| outs(%argA: tensor<8x8xf64, #SM>) { |
| ^bb(%a: f64): |
| %u = sparse_tensor.unary %a : f64 to f64 |
| present={ |
| ^bb0(%p: f64): |
| %add = arith.addf %p, %c : f64 |
| sparse_tensor.yield %add : f64 |
| } |
| absent={} |
| linalg.yield %u : f64 |
| } -> tensor<8x8xf64, #SM> |
| return %result : tensor<8x8xf64, #SM> |
| } |
| } |
