| // RUN: mlir-opt %s --sparse-reinterpret-map -sparsification | FileCheck %s |
| |
| #map = affine_map<(d0, d1, d2) -> (d0, d1, d2)> |
| #BCSR = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : batch, d1 : dense, d2 : compressed)}> |
| |
| // CHECK-LABEL: func.func @main( |
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<8x4x2xf32, #sparse{{[0-9]*}}>) -> tensor<8x4x2xf32> { |
| // CHECK: %[[VAL_1:.*]] = arith.constant 1 : index |
| // CHECK: %[[VAL_2:.*]] = arith.constant 0 : index |
| // CHECK: %[[VAL_3:.*]] = arith.constant 0.000000e+00 : f32 |
| // CHECK: %[[VAL_4:.*]] = arith.constant 4 : index |
| // CHECK: %[[VAL_5:.*]] = arith.constant 8 : index |
| // CHECK: %[[VAL_6:.*]] = tensor.empty() : tensor<8x4x2xf32> |
| // CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<8x4x2xf32, #sparse{{[0-9]*}}> to memref<8x?xindex> |
| // CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<8x4x2xf32, #sparse{{[0-9]*}}> to memref<8x?xindex> |
| // CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x4x2xf32, #sparse{{[0-9]*}}> to memref<8x?xf32> |
| // CHECK: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_6]] : memref<8x4x2xf32> |
| // CHECK: linalg.fill ins(%[[VAL_3]] : f32) outs(%[[VAL_10]] : memref<8x4x2xf32>) |
| // CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_2]] to %[[VAL_5]] step %[[VAL_1]] { |
| // CHECK: scf.for %[[VAL_12:.*]] = %[[VAL_2]] to %[[VAL_4]] step %[[VAL_1]] { |
| // CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_11]], %[[VAL_12]]] : memref<8x?xindex> |
| // CHECK: %[[VAL_14:.*]] = arith.addi %[[VAL_12]], %[[VAL_1]] : index |
| // CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_11]], %[[VAL_14]]] : memref<8x?xindex> |
| // CHECK: scf.for %[[VAL_16:.*]] = %[[VAL_13]] to %[[VAL_15]] step %[[VAL_1]] { |
| // CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_11]], %[[VAL_16]]] : memref<8x?xindex> |
| // CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_11]], %[[VAL_16]]] : memref<8x?xf32> |
| // CHECK: %[[VAL_19:.*]] = arith.negf %[[VAL_18]] : f32 |
| // CHECK: memref.store %[[VAL_19]], %[[VAL_10]]{{\[}}%[[VAL_11]], %[[VAL_12]], %[[VAL_17]]] : memref<8x4x2xf32> |
| // CHECK: } |
| // CHECK: } |
| // CHECK: } |
| // CHECK: %[[VAL_20:.*]] = bufferization.to_tensor %[[VAL_10]] : memref<8x4x2xf32> |
| // CHECK: return %[[VAL_20]] : tensor<8x4x2xf32> |
| // CHECK: } |
| func.func @main(%arg0: tensor<8x4x2xf32, #BCSR>) -> tensor<8x4x2xf32> { |
| %0 = tensor.empty() : tensor<8x4x2xf32> |
| %1 = linalg.generic { |
| indexing_maps = [#map, #map], |
| iterator_types = ["parallel", "parallel", "parallel"] |
| } |
| ins(%arg0 : tensor<8x4x2xf32, #BCSR>) |
| outs(%0 : tensor<8x4x2xf32>) { |
| ^bb0(%in: f32, %out: f32): |
| %2 = arith.negf %in : f32 |
| linalg.yield %2 : f32 |
| } -> tensor<8x4x2xf32> |
| return %1 : tensor<8x4x2xf32> |
| } |
