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1// RUN: mlir-opt -split-input-file -transform-interpreter %s | FileCheck %s2 3module attributes {transform.with_named_sequence} {4  transform.named_sequence @__transform_main(%root : !transform.any_op {transform.readonly}) {5    %func_op = transform.structured.match ops{["func.func"]} in %root : (!transform.any_op) -> !transform.op<"func.func">6    transform.apply_patterns to %func_op {7      transform.apply_patterns.tensor.fold_tensor_subset_ops_into_vector_transfers8    } : !transform.op<"func.func">9    transform.yield10  }11}12 13// CHECK: #[[$map:.*]] = affine_map<()[s0] -> (s0 + 4)>14// CHECK: #[[$map1:.*]] = affine_map<()[s0] -> (s0 + 3)>15// CHECK: #[[$map2:.*]] = affine_map<(d0, d1, d2) -> (d0, d2)>16 17// CHECK-LABEL: func @transfer_read_of_extract_slice(18//  CHECK-SAME:     %[[t:.*]]: tensor<?x?xf32>, %[[s1:.*]]: index, %[[s2:.*]]: index19//   CHECK-DAG:   %[[c8:.*]] = arith.constant 8 : index20//       CHECK:   %[[add:.*]] = affine.apply #[[$map]]()[%[[s1]]]21//       CHECK:   %[[r:.*]] = vector.transfer_read %[[t]][%[[c8]], %[[add]]], %{{.*}} {in_bounds = [true, true]} : tensor<?x?xf32>, vector<5x6xf32>22//       CHECK:   return %[[r]]23func.func @transfer_read_of_extract_slice(%t : tensor<?x?xf32>, %s1 : index, %s2 : index) -> vector<5x6xf32> {24  %c3 = arith.constant 3 : index25  %c4 = arith.constant 4 : index26  %cst = arith.constant 0.0 : f3227  %0 = tensor.extract_slice %t[5, %s1] [10, %s2] [1, 1] : tensor<?x?xf32> to tensor<10x?xf32>28  %1 = vector.transfer_read %0[%c3, %c4], %cst {in_bounds = [true, true]} : tensor<10x?xf32>, vector<5x6xf32>29  return %1 : vector<5x6xf32>30}31 32// CHECK-LABEL: func @transfer_read_of_extract_slice_1d(33//  CHECK-SAME:     %[[t:.*]]: tensor<?x?xf32>, %[[s1:.*]]: index, %[[s2:.*]]: index34//   CHECK-DAG:   %[[c8:.*]] = arith.constant 8 : index35//       CHECK:   %[[add:.*]] = affine.apply #[[$map]]()[%[[s1]]]36//       CHECK:   %[[r:.*]] = vector.transfer_read %[[t]][%[[c8]], %[[add]]], %{{.*}} {in_bounds = [true]} : tensor<?x?xf32>, vector<6xf32>37//       CHECK:   return %[[r]]38func.func @transfer_read_of_extract_slice_1d(%t : tensor<?x?xf32>, %s1 : index, %s2 : index) -> vector<6xf32> {39  %c3 = arith.constant 3 : index40  %c4 = arith.constant 4 : index41  %cst = arith.constant 0.0 : f3242  %0 = tensor.extract_slice %t[5, %s1] [10, %s2] [1, 1] : tensor<?x?xf32> to tensor<10x?xf32>43  %1 = vector.transfer_read %0[%c3, %c4], %cst {in_bounds = [true]} : tensor<10x?xf32>, vector<6xf32>44  return %1 : vector<6xf32>45}46 47// CHECK-LABEL: func @transfer_read_of_extract_slice_rank_reducing(48//  CHECK-SAME:     %[[t:.*]]: tensor<?x?x?xf32>, %[[s1:.*]]: index, %[[s2:.*]]: index49//   CHECK-DAG:   %[[c5:.*]] = arith.constant 5 : index50//   CHECK-DAG:   %[[c10:.*]] = arith.constant 10 : index51//       CHECK:   %[[add:.*]] = affine.apply #[[$map1]]()[%[[s1]]]52//       CHECK:   %[[r:.*]] = vector.transfer_read %[[t]][%[[c5]], %[[add]], %[[c10]]], %{{.*}} {in_bounds = [true, true]} : tensor<?x?x?xf32>, vector<5x6xf32>53//       CHECK:   return %[[r]]54func.func @transfer_read_of_extract_slice_rank_reducing(%t : tensor<?x?x?xf32>, %s1 : index, %s2 : index) -> vector<5x6xf32> {55  %c3 = arith.constant 3 : index56  %c4 = arith.constant 4 : index57  %cst = arith.constant 0.0 : f3258  %0 = tensor.extract_slice %t[5, %s1, 6] [1, %s2, 12] [1, 1, 1] : tensor<?x?x?xf32> to tensor<?x12xf32>59  %1 = vector.transfer_read %0[%c3, %c4], %cst {in_bounds = [true, true]} : tensor<?x12xf32>, vector<5x6xf32>60  return %1 : vector<5x6xf32>61}62 63// CHECK-LABEL: func @transfer_read_of_extract_slice_non_leading_rank_reduction(64//  CHECK-SAME:     %[[t:.*]]: tensor<?x?x?xf32>, %[[s1:.*]]: index, %[[s2:.*]]: index65//   CHECK-DAG:   %[[c8:.*]] = arith.constant 8 : index66//   CHECK-DAG:   %[[c10:.*]] = arith.constant 10 : index67//       CHECK:   %[[r:.*]] = vector.transfer_read %[[t]][%[[c8]], %[[s1]], %[[c10]]], %{{.*}} {in_bounds = [true, true], permutation_map = #[[$map2]]} : tensor<?x?x?xf32>, vector<5x6xf32>68//       CHECK:   return %[[r]]69func.func @transfer_read_of_extract_slice_non_leading_rank_reduction(%t : tensor<?x?x?xf32>, %s1 : index, %s2 : index) -> vector<5x6xf32> {70  %c3 = arith.constant 3 : index71  %c4 = arith.constant 4 : index72  %cst = arith.constant 0.0 : f3273  %0 = tensor.extract_slice %t[5, %s1, 6] [%s2, 1, 12] [1, 1, 1] : tensor<?x?x?xf32> to tensor<?x12xf32>74  %1 = vector.transfer_read %0[%c3, %c4], %cst {in_bounds = [true, true]} : tensor<?x12xf32>, vector<5x6xf32>75  return %1 : vector<5x6xf32>76}77 78// CHECK-LABEL: func @masked_transfer_read_of_extract_slice79//  CHECK-SAME:     %[[t:.*]]: tensor<?x?xf32>, %[[s1:.*]]: index, %[[s2:.*]]: index80//   CHECK-DAG: %[[m:.*]] = vector.create_mask{{.*}} : vector<5x6xi1>81//   CHECK-DAG: %[[a:.*]] = affine.apply {{.*}}[[s1]]82//       CHECK: vector.mask %[[m]] { vector.transfer_read %[[t]]{{.*}}: tensor<?x?xf32>, vector<5x6xf32> } : vector<5x6xi1> -> vector<5x6xf32>83func.func @masked_transfer_read_of_extract_slice(%t : tensor<?x?xf32>, %s1 : index, %s2 : index) -> vector<5x6xf32> {84  %c3 = arith.constant 3 : index85  %c4 = arith.constant 4 : index86  %cst = arith.constant 0.0 : f3287  %0 = tensor.extract_slice %t[5, %s1] [10, %s2] [1, 1] : tensor<?x?xf32> to tensor<10x?xf32>88  %mask = vector.create_mask %c3, %c4 : vector<5x6xi1>89  %1 = vector.mask %mask {vector.transfer_read %0[%c3, %c4], %cst {in_bounds = [true, true]} : tensor<10x?xf32>, vector<5x6xf32>} : vector<5x6xi1> -> vector<5x6xf32>90  return %1 : vector<5x6xf32>91}92 93// CHECK-LABEL: func @insert_slice_of_transfer_write(94//  CHECK-SAME:     %[[t1:.*]]: tensor<?x12xf32>, %[[v:.*]]: vector<5x6xf32>, %[[s:.*]]: index95//       CHECK:   %[[c3:.*]] = arith.constant 3 : index96//       CHECK:   %[[r:.*]] = vector.transfer_write %[[v]], %[[t1]][%[[c3]], %[[s]]] {in_bounds = [true, true]} : vector<5x6xf32>, tensor<?x12xf32>97//       CHECK:   return %[[r]]98func.func @insert_slice_of_transfer_write(%t1 : tensor<?x12xf32>, %v : vector<5x6xf32>, %s : index, %t2 : tensor<5x6xf32>) -> tensor<?x12xf32> {99  %c0 = arith.constant 0 : index100  %0 = vector.transfer_write %v, %t2[%c0, %c0] {in_bounds = [true, true]} : vector<5x6xf32>, tensor<5x6xf32>101  %1 = tensor.insert_slice %0 into %t1[3, %s] [5, 6] [1, 1] : tensor<5x6xf32> into tensor<?x12xf32>102  return %1 : tensor<?x12xf32>103}104 105// CHECK-LABEL: func @unit_insert_slice_of_unit_transfer_write(106//  CHECK-SAME:     %[[t1:.*]]: tensor<1x1x12xf32>, %[[v:.*]]: vector<1x6xf32>, %[[s:.*]]: index107//       CHECK:   %[[c0:.*]] = arith.constant 0 : index108//       CHECK:   %[[r:.*]] = vector.transfer_write %[[v]], %[[t1]][%[[c0]], %[[c0]], %[[s]]] {in_bounds = [true, true]} : vector<1x6xf32>, tensor<1x1x12xf32>109//       CHECK:   return %[[r]]110func.func @unit_insert_slice_of_unit_transfer_write(%t1 : tensor<1x1x12xf32>, %v : vector<1x6xf32>, %s : index, %t2 : tensor<1x6xf32>) -> tensor<1x1x12xf32> {111  %c0 = arith.constant 0 : index112  %0 = vector.transfer_write %v, %t2[%c0, %c0] {in_bounds = [true, true]} : vector<1x6xf32>, tensor<1x6xf32>113  %1 = tensor.insert_slice %0 into %t1[0, 0, %s] [1, 1, 6] [1, 1, 1] : tensor<1x6xf32> into tensor<1x1x12xf32>114  return %1 : tensor<1x1x12xf32>115}116 117// CHECK-LABEL: func @insert_slice_of_transfer_write_non_leading_rank_reduction(118//  CHECK-SAME:     %[[t1:.*]]: tensor<?x?x12xf32>, %[[v:.*]]: vector<5x6xf32>, %[[s:.*]]: index119//   CHECK-DAG:   %[[c3:.*]] = arith.constant 3 : index120//   CHECK-DAG:   %[[c4:.*]] = arith.constant 4 : index121//       CHECK:   %[[r:.*]] = vector.transfer_write %[[v]], %[[t1]][%[[c4]], %[[c3]], %[[s]]] {in_bounds = [true, true], permutation_map = #[[$map2]]} : vector<5x6xf32>, tensor<?x?x12xf32>122func.func @insert_slice_of_transfer_write_non_leading_rank_reduction(%t1 : tensor<?x?x12xf32>, %v : vector<5x6xf32>, %s : index, %t2 : tensor<5x6xf32>) -> tensor<?x?x12xf32> {123  %c0 = arith.constant 0 : index124  %0 = vector.transfer_write %v, %t2[%c0, %c0] {in_bounds = [true, true]} : vector<5x6xf32>, tensor<5x6xf32>125  %1 = tensor.insert_slice %0 into %t1[4, 3, %s] [5, 1, 6] [1, 1, 1] : tensor<5x6xf32> into tensor<?x?x12xf32>126  return %1 : tensor<?x?x12xf32>127}128 129// CHECK-LABEL: func @insert_slice_of_transfer_write_rank_extending(130//  CHECK-SAME:     %[[t1:.*]]: tensor<?x?x12xf32>, %[[v:.*]]: vector<5x6xf32>, %[[s:.*]]: index131//   CHECK-DAG:   %[[c3:.*]] = arith.constant 3 : index132//   CHECK-DAG:   %[[c4:.*]] = arith.constant 4 : index133//       CHECK:   %[[r:.*]] = vector.transfer_write %[[v]], %[[t1]][%[[c4]], %[[c3]], %[[s]]] {in_bounds = [true, true]} : vector<5x6xf32>, tensor<?x?x12xf32>134//       CHECK:   return %[[r]]135func.func @insert_slice_of_transfer_write_rank_extending(%t1 : tensor<?x?x12xf32>, %v : vector<5x6xf32>, %s : index, %t2 : tensor<5x6xf32>) -> tensor<?x?x12xf32> {136  %c0 = arith.constant 0 : index137  %0 = vector.transfer_write %v, %t2[%c0, %c0] {in_bounds = [true, true]} : vector<5x6xf32>, tensor<5x6xf32>138  %1 = tensor.insert_slice %0 into %t1[4, 3, %s] [1, 5, 6] [1, 1, 1] : tensor<5x6xf32> into tensor<?x?x12xf32>139  return %1 : tensor<?x?x12xf32>140}141