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1// RUN: mlir-opt %s -allow-unregistered-dialect -one-shot-bufferize="allow-unknown-ops" -split-input-file | FileCheck %s2 3// Test bufferization using memref types that have no layout map.4// RUN: mlir-opt %s -allow-unregistered-dialect -one-shot-bufferize="allow-unknown-ops unknown-type-conversion=identity-layout-map" -split-input-file | FileCheck %s --check-prefix=CHECK-NO-LAYOUT-MAP5 6// Run fuzzer with different seeds.7// RUN: mlir-opt %s -allow-unregistered-dialect -one-shot-bufferize="test-analysis-only analysis-heuristic=fuzzer analysis-fuzzer-seed=23" -split-input-file -o /dev/null8// RUN: mlir-opt %s -allow-unregistered-dialect -one-shot-bufferize="test-analysis-only analysis-heuristic=fuzzer analysis-fuzzer-seed=59" -split-input-file -o /dev/null9// RUN: mlir-opt %s -allow-unregistered-dialect -one-shot-bufferize="test-analysis-only analysis-heuristic=fuzzer analysis-fuzzer-seed=91" -split-input-file -o /dev/null10 11// RUN: mlir-opt %s -allow-unregistered-dialect -one-shot-bufferize="dialect-filter=tensor,bufferization allow-unknown-ops" -canonicalize -split-input-file | FileCheck %s --check-prefix=CHECK-TENSOR12// RUN: mlir-opt %s -allow-unregistered-dialect -one-shot-bufferize="dialect-filter=scf,bufferization allow-unknown-ops" -canonicalize -split-input-file | FileCheck %s --check-prefix=CHECK-SCF13 14// CHECK-LABEL: func @use_of_unknown_op_1(15// CHECK-SAME: %[[t1:.*]]: tensor<?xf32>16// CHECK-NO-LAYOUT-MAP-LABEL: func @use_of_unknown_op_1(17// CHECK-NO-LAYOUT-MAP-SAME: %[[t1:.*]]: tensor<?xf32>18func.func @use_of_unknown_op_1(%t1: tensor<?xf32>)19 -> vector<5xf32> {20 // ToTensorOp is generated because the function is bufferized and has a21 // memref block argument.22 // CHECK: %[[dummy:.*]] = "test.dummy_op"(%[[t1]])23 // CHECK-NO-LAYOUT-MAP: %[[dummy:.*]] = "test.dummy_op"(%[[t1]])24 %0 = "test.dummy_op"(%t1) : (tensor<?xf32>) -> tensor<?xf32>25 26 %idx = arith.constant 0 : index27 %cst = arith.constant 0.0 : f3228 // CHECK: %[[dummy_memref:.*]] = bufferization.to_buffer %[[dummy]] : tensor<?xf32> to memref<?xf32, strided<[?], offset: ?>>29 // CHECK: vector.transfer_read %[[dummy_memref]][%{{.*}}], %{{.*}} : memref<?xf32, strided<[?], offset: ?>>30 // CHECK-NO-LAYOUT-MAP: %[[dummy_memref:.*]] = bufferization.to_buffer %[[dummy]] : tensor<?xf32> to memref<?xf32>31 // CHECK-NO-LAYOUT-MAP: vector.transfer_read %[[dummy_memref]][%{{.*}}], %{{.*}} : memref<?xf32>32 %1 = vector.transfer_read %0[%idx], %cst : tensor<?xf32>, vector<5xf32>33 return %1 : vector<5xf32>34}35 36// -----37 38// CHECK-LABEL: func @use_of_unknown_op_2(39// CHECK-SAME: %[[t1:.*]]: tensor<?xf32>40func.func @use_of_unknown_op_2(%t1: tensor<?xf32>) -> tensor<?xf32> {41 // CHECK: %[[dummy1:.*]] = "test.dummy_op"(%[[t1]])42 %0 = "test.dummy_op"(%t1) : (tensor<?xf32>) -> tensor<?xf32>43 // CHECK: %[[dummy2:.*]] = "test.another_dummy_op"(%[[dummy1]])44 %1 = "test.another_dummy_op"(%0) : (tensor<?xf32>) -> tensor<?xf32>45 46 // CHECK: return %[[dummy2]]47 return %1 : tensor<?xf32>48}49 50// -----51 52// CHECK-LABEL: func @use_of_unknown_op_3(53// CHECK-SAME: %[[t1:.*]]: tensor<?xf32>54func.func @use_of_unknown_op_3(%t1: tensor<?xf32>)55 -> (vector<5xf32>, vector<5xf32>) {56 %idx = arith.constant 0 : index57 %cst = arith.constant 0.0 : f3258 // CHECK: %[[m1:.*]] = bufferization.to_buffer %[[t1]]59 // CHECK: %[[v1:.*]] = vector.transfer_read %[[m1]]60 %1 = vector.transfer_read %t1[%idx], %cst : tensor<?xf32>, vector<5xf32>61 62 // CHECK: %[[dummy:.*]] = "test.dummy_op"(%[[t1]])63 %0 = "test.dummy_op"(%t1) : (tensor<?xf32>) -> tensor<?xf32>64 // CHECK: %[[dummy_memref:.*]] = bufferization.to_buffer %[[dummy]] : tensor<?xf32> to memref<?xf32, strided<[?], offset: ?>>65 // CHECK: %[[v2:.*]] = vector.transfer_read %[[dummy_memref]]66 %2 = vector.transfer_read %0[%idx], %cst : tensor<?xf32>, vector<5xf32>67 68 // CHECK: return %[[v1]], %[[v2]]69 return %1, %2 : vector<5xf32>, vector<5xf32>70}71 72// -----73 74// CHECK-LABEL: func @use_of_unknown_op_4(75// CHECK-SAME: %[[t1:.*]]: tensor<?xf32>76func.func @use_of_unknown_op_4(%t1: tensor<?xf32>)77 -> (vector<5xf32>, tensor<?xf32>) {78 %idx = arith.constant 0 : index79 %cst = arith.constant 0.0 : f3280 81 // CHECK: %[[dummy:.*]] = "test.dummy_op"(%[[t1]])82 %0 = "test.dummy_op"(%t1) : (tensor<?xf32>) -> tensor<?xf32>83 84 // CHECK: %[[dummy_memref:.*]] = bufferization.to_buffer %[[dummy]]85 // CHECK: %[[v1:.*]] = vector.transfer_read %[[dummy_memref]]86 %1 = vector.transfer_read %0[%idx], %cst : tensor<?xf32>, vector<5xf32>87 88 // CHECK: %[[another_dummy:.*]] = "test.another_dummy_op"(%[[dummy]])89 %2 = "test.another_dummy_op"(%0) : (tensor<?xf32>) -> tensor<?xf32>90 91 // CHECK: return %[[v1]], %[[another_dummy]]92 return %1, %2 : vector<5xf32>, tensor<?xf32>93}94 95// -----96 97// CHECK-LABEL: func @use_of_bufferizable_op_in_unbufferizable_op98// CHECK-SAME: %[[t1:.*]]: tensor<?xf32>99func.func @use_of_bufferizable_op_in_unbufferizable_op(100 %t1: tensor<?xf32>, %o: index, %s: index) -> (tensor<?xf32>, tensor<?xf32>) {101 // CHECK: %[[m1:.*]] = bufferization.to_buffer %[[t1]]102 // CHECK: %[[subview:.*]] = memref.subview %[[m1]]103 // The op must alloc because "test.dummy" may bufferize to a memory write.104 // CHECK: %[[alloc:.*]] = memref.alloc105 // CHECK: memref.copy %[[subview]], %[[alloc]]106 %0 = tensor.extract_slice %t1[%o][%s][1] : tensor<?xf32> to tensor<?xf32>107 // CHECK: %[[alloc_tensor:.*]] = bufferization.to_tensor %[[alloc]]108 // CHECK: %[[dummy:.*]] = "test.dummy_op"(%[[alloc_tensor]])109 %1 = "test.dummy_op"(%0) : (tensor<?xf32>) -> tensor<?xf32>110 // CHECK: return %[[alloc_tensor]], %[[dummy]]111 return %0, %1 : tensor<?xf32>, tensor<?xf32>112}113 114// -----115 116// CHECK-LABEL: func @unused_unknown_op(117// CHECK-SAME: %[[t1:.*]]: tensor<?xf32>118func.func @unused_unknown_op(%t1 : tensor<?xf32>) -> vector<5xf32> {119 %idx = arith.constant 0 : index120 %cst = arith.constant 0.0 : f32121 122 // CHECK: %[[m1:.*]] = bufferization.to_buffer %[[t1]]123 // CHECK: vector.transfer_read %[[m1]]124 %1 = vector.transfer_read %t1[%idx], %cst : tensor<?xf32>, vector<5xf32>125 126 // CHECK: "test.dummy_op"(%[[t1]])127 "test.dummy_op"(%t1) : (tensor<?xf32>) -> ()128 129 return %1 : vector<5xf32>130}131 132// -----133 134// CHECK-LABEL: func @unknown_op_may_read(135func.func @unknown_op_may_read(%v: vector<5xf32>)136 -> (tensor<10xf32>, tensor<10xf32>) {137 %idx = arith.constant 0 : index138 %cst = arith.constant 5.0 : f32139 140 // One alloc for the alloc_tensor, another one because the transfer_write141 // bufferizes out-of-place.142 // CHECK: %[[m1:.*]] = memref.alloc() {{.*}} : memref<10xf32>143 // CHECK: linalg.fill ins(%{{.*}}{{.*}}outs(%[[m1]]144 // CHECK: %[[filled_tensor:.*]] = bufferization.to_tensor %[[m1]]145 %t1 = bufferization.alloc_tensor() : tensor<10xf32>146 %filled = linalg.fill ins(%cst : f32) outs(%t1 : tensor<10xf32>) -> tensor<10xf32>147 148 // The transfer_write is out-of-place because "dummy_op" may read.149 // CHECK: %[[alloc:.*]] = memref.alloc() {{.*}} : memref<10xf32>150 // CHECK: memref.copy %[[m1]], %[[alloc]]151 // CHECK: vector.transfer_write %{{.*}}, %[[alloc]]152 // CHECK: %[[alloc_tensor:.*]] = bufferization.to_tensor %[[alloc]]153 %1 = vector.transfer_write %v, %filled[%idx] : vector<5xf32>, tensor<10xf32>154 155 // CHECK: %[[dummy:.*]] = "test.dummy_op"(%[[filled_tensor]])156 %2 = "test.dummy_op"(%filled) : (tensor<10xf32>) -> (tensor<10xf32>)157 158 // CHECK: return %[[alloc_tensor]], %[[dummy]]159 return %1, %2 : tensor<10xf32>, tensor<10xf32>160}161 162// -----163 164// CHECK-LABEL: func @unknown_op_not_writable165// CHECK-SAME: %[[t1:.*]]: tensor<?xf32>166func.func @unknown_op_not_writable(167 %t1 : tensor<?xf32>, %v : vector<5xf32>, %idx : index) -> tensor<?xf32> {168 // CHECK: %[[dummy:.*]] = "test.dummy_op"(%[[t1]])169 // CHECK: %[[dummy_memref:.*]] = bufferization.to_buffer %[[dummy]]170 %0 = "test.dummy_op"(%t1) : (tensor<?xf32>) -> (tensor<?xf32>)171 172 // The result of an unknown op is not writable. Always generate a copy.173 // CHECK: %[[dim:.*]] = memref.dim %[[dummy_memref]]174 // CHECK: %[[alloc:.*]] = memref.alloc(%[[dim]])175 // CHECK: memref.copy %[[dummy_memref]], %[[alloc]]176 // CHECK: vector.transfer_write %{{.*}}, %[[alloc]]177 %1 = vector.transfer_write %v, %0[%idx] : vector<5xf32>, tensor<?xf32>178 179 // CHECK: %[[alloc_tensor:.*]] = bufferization.to_tensor %[[alloc]]180 // CHECK: return %[[alloc_tensor]]181 return %1 : tensor<?xf32>182}183 184// -----185 186// CHECK-TENSOR-LABEL: func @simple_tensor_test(187// CHECK-TENSOR-SAME: %[[t1:.*]]: tensor<?xf32>188func.func @simple_tensor_test(%t1 : tensor<?xf32>, %f : f32) -> tensor<?xf32> {189 // CHECK-TENSOR: %[[t1_memref:.*]] = bufferization.to_buffer %[[t1]]190 %c0 = arith.constant 0 : index191 // CHECK-TENSOR: %[[alloc:.*]] = memref.alloc192 // CHECK-TENSOR: memref.copy %[[t1_memref]], %[[alloc]]193 // CHECK-TENSOR: memref.store %{{.*}}, %[[alloc]]194 %0 = tensor.insert %f into %t1[%c0] : tensor<?xf32>195 // CHECK-TENSOR: %[[casted_alloc:.*]] = bufferization.to_tensor %[[alloc]]196 // CHECK-TENSOR: return %[[casted_alloc]]197 return %0 : tensor<?xf32>198}199 200// -----201 202// CHECK-SCF-LABEL: func @simple_scf_if(203// CHECK-SCF-SAME: %[[t1:.*]]: tensor<?xf32> {bufferization.writable = true}, %[[c:.*]]: i1, %[[pos:.*]]: index204func.func @simple_scf_if(%t1: tensor<?xf32> {bufferization.writable = true}, %c: i1, %pos: index, %f: f32)205 -> (tensor<?xf32>, index) {206 // CHECK-SCF: %[[t1_memref:.*]] = bufferization.to_buffer %[[t1]]207 // CHECK-SCF: %[[r:.*]] = scf.if %[[c]] -> (memref<?xf32, strided{{.*}}>) {208 %r1, %r2 = scf.if %c -> (tensor<?xf32>, index) {209 // CHECK-SCF: scf.yield %[[t1_memref]]210 scf.yield %t1, %pos : tensor<?xf32>, index211 // CHECK-SCF: } else {212 } else {213 // CHECK-SCF: %[[insert:.*]] = tensor.insert %{{.*}} into %[[t1]][{{.*}}]214 // CHECK-SCF: %[[insert_memref:.*]] = bufferization.to_buffer %[[insert]]215 %1 = tensor.insert %f into %t1[%pos] : tensor<?xf32>216 // CHECK-SCF: scf.yield %[[insert_memref]]217 scf.yield %1, %pos : tensor<?xf32>, index218 }219 220 // CHECK-SCF: %[[r_tensor:.*]] = bufferization.to_tensor %[[r]]221 // CHECK-SCF: return %[[r_tensor]], %[[pos]]222 return %r1, %r2 : tensor<?xf32>, index223}224