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1// RUN: mlir-opt -test-linalg-pad-fusion -split-input-file %s | FileCheck %s2 3func.func @dynamic_pad_fusion(%arg0 : tensor<?x?xf32>, %arg1 : index, %arg2 : index,4    %arg3 : index, %arg4 : index, %arg5 : f32) -> tensor<?x?xf32> {5  %c0 = arith.constant 0 : index6  %c1 = arith.constant 1 : index7  %d0 = tensor.dim %arg0, %c0 : tensor<?x?xf32>8  %d1 = tensor.dim %arg0, %c1 : tensor<?x?xf32>9  %init = tensor.empty(%d0, %d1) : tensor<?x?xf32>10  %0 = linalg.generic {11    indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, affine_map<(d0, d1) -> (d0, d1)>],12    iterator_types = ["parallel", "parallel"]}13    ins(%arg0 : tensor<?x?xf32>) outs(%init : tensor<?x?xf32>) {14    ^bb0(%arg6 : f32, %arg7 : f32):15      %1 = arith.mulf %arg6, %arg6 : f3216      linalg.yield %1 : f3217    } -> tensor<?x?xf32>18  %1 = tensor.pad %0 low [%arg1, %arg2] high [%arg3, %arg4] {19    ^bb0(%arg6: index, %arg7 : index):20      tensor.yield %arg5 : f3221    } : tensor<?x?xf32> to tensor<?x?xf32>22  return %1 : tensor<?x?xf32>23}24 25//  CHECK-DAG: #[[MAP:.+]] = affine_map<()[s0, s1, s2] -> (s0 + s1 + s2)>26//      CHECK: func @dynamic_pad_fusion27// CHECK-SAME:     %[[ARG0:.+]]: tensor<?x?xf32>28// CHECK-SAME:     %[[ARG1:[a-zA-Z0-9]+]]: index29// CHECK-SAME:     %[[ARG2:[a-zA-Z0-9]+]]: index30// CHECK-SAME:     %[[ARG3:[a-zA-Z0-9]+]]: index31// CHECK-SAME:     %[[ARG4:[a-zA-Z0-9]+]]: index32// CHECK-SAME:     %[[ARG5:[a-zA-Z0-9]+]]: f3233//  CHECK-DAG:   %[[C0:.+]] = arith.constant 0 : index34//  CHECK-DAG:   %[[C1:.+]] = arith.constant 1 : index35//  CHECK-DAG:   %[[SOURCE:.+]] = linalg.generic36//  CHECK-DAG:   %[[SOURCE_D0:.+]] = tensor.dim %[[SOURCE]], %[[C0]]37//  CHECK-DAG:   %[[TARGET_D0:.+]] = affine.apply #[[MAP]]()[%[[SOURCE_D0]], %[[ARG1]], %[[ARG3]]]38//  CHECK-DAG:   %[[SOURCE_D1:.+]] = tensor.dim %[[SOURCE]], %[[C1]]39//  CHECK-DAG:   %[[TARGET_D1:.+]] = affine.apply #[[MAP]]()[%[[SOURCE_D1]], %[[ARG2]], %[[ARG4]]]40//      CHECK:   %[[INIT:.+]] = tensor.empty(%[[TARGET_D0]], %[[TARGET_D1]])41//      CHECK:   %[[FILL:.+]] = linalg.fill ins(%[[ARG5]]{{.*}}outs(%[[INIT]]42//  CHECK-DAG:   %[[SIZE_D0:.+]] = tensor.dim %[[SOURCE]], %[[C0]]43//  CHECK-DAG:   %[[SIZE_D1:.+]] = tensor.dim %[[SOURCE]], %[[C1]]44//      CHECK:   %[[SLICE:.+]] = tensor.extract_slice %[[FILL]]45// CHECK-SAME:       [%[[ARG1]], %[[ARG2]]] [%[[SIZE_D0]], %[[SIZE_D1]]] [1, 1]46//      CHECK:   %[[SOURCE:.+]] = linalg.generic47// CHECK-SAME:       outs(%[[SLICE]] : tensor<?x?xf32>)48//      CHECK:   %[[RESULT:.+]] = tensor.insert_slice %[[SOURCE]] into %[[FILL]]49// CHECK-SAME:       [%[[ARG1]], %[[ARG2]]] [%[[SIZE_D0]], %[[SIZE_D1]]] [1, 1]50//      CHECK:   return %[[RESULT]]51 52// -----53 54func.func @mixed_pad_fusion(%arg0 : tensor<?x42xf32>, %arg1 : index, %arg2 : index,55    %arg3 : f32) -> tensor<49x?xf32> {56  %c0 = arith.constant 0 : index57  %d0 = tensor.dim %arg0, %c0 : tensor<?x42xf32>58  %init = tensor.empty(%d0) : tensor<42x?xf32>59  %0 = linalg.generic {60    indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, affine_map<(d0, d1) -> (d1, d0)>],61    iterator_types = ["parallel", "parallel"]}62    ins(%arg0 : tensor<?x42xf32>) outs(%init : tensor<42x?xf32>) {63    ^bb0(%arg4 : f32, %arg5 : f32):64      %1 = arith.mulf %arg4, %arg4 : f3265      linalg.yield %1 : f3266    } -> tensor<42x?xf32>67  %1 = tensor.pad %0 low [3, %arg1] high [4, %arg2] {68    ^bb0(%arg4: index, %arg5 : index):69      tensor.yield %arg3 : f3270    } : tensor<42x?xf32> to tensor<49x?xf32>71  return %1 : tensor<49x?xf32>72}73//  CHECK-DAG: #[[MAP:.+]] = affine_map<()[s0, s1, s2] -> (s0 + s1 + s2)>74//      CHECK: func @mixed_pad_fusion75// CHECK-SAME:     %[[ARG0:.+]]: tensor<?x42xf32>76// CHECK-SAME:     %[[ARG1:[a-zA-Z0-9]+]]: index77// CHECK-SAME:     %[[ARG2:[a-zA-Z0-9]+]]: index78// CHECK-SAME:     %[[ARG3:[a-zA-Z0-9]+]]: f3279//  CHECK-DAG:   %[[C0:.+]] = arith.constant 0 : index80//  CHECK-DAG:   %[[C1:.+]] = arith.constant 1 : index81//  CHECK-DAG:   %[[SOURCE:.+]] = linalg.generic82//  CHECK-DAG:   %[[SOURCE_D1:.+]] = tensor.dim %[[SOURCE]], %[[C1]]83//  CHECK-DAG:   %[[TARGET_D1:.+]] = affine.apply #[[MAP]]()[%[[SOURCE_D1]], %[[ARG1]], %[[ARG2]]]84//      CHECK:   %[[INIT:.+]] = tensor.empty(%[[TARGET_D1]])85//      CHECK:   %[[FILL:.+]] = linalg.fill ins(%[[ARG3]]{{.*}}outs(%[[INIT]]86//  CHECK-DAG:   %[[SIZE_D1:.+]] = tensor.dim %[[SOURCE]], %[[C1]]87//      CHECK:   %[[SLICE:.+]] = tensor.extract_slice %[[FILL]]88// CHECK-SAME:       [3, %[[ARG1]]] [42, %[[SIZE_D1]]] [1, 1]89//      CHECK:   %[[SOURCE:.+]] = linalg.generic90// CHECK-SAME:       outs(%[[SLICE]] : tensor<42x?xf32>)91//      CHECK:   %[[RESULT:.+]] = tensor.insert_slice %[[SOURCE]] into %[[FILL]]92// CHECK-SAME:       [3, %[[ARG1]]] [42, %[[SIZE_D1]]] [1, 1]93//      CHECK:   return %[[RESULT]]94