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1// RUN: mlir-opt %s -test-linalg-elementwise-fusion-patterns=fuse-generic-ops-control -split-input-file | FileCheck %s2 3#map0 = affine_map<(d0, d1) -> (d0, d1)>4#binary2Dpointwise = {5 indexing_maps = [#map0, #map0, #map0],6 iterator_types = ["parallel", "parallel"]7}8#ternary2Dpointwise = {9 indexing_maps = [#map0, #map0, #map0, #map0],10 iterator_types = ["parallel", "parallel"]11}12func.func @test_fusion_limit(13 %arg0 : tensor<?x?xf32>, %arg1 : tensor<?x?xf32>, %arg2 : tensor<?x?xf32>,14 %arg3 : tensor<?x?xf32>, %arg4 : tensor<?x?xf32>, %arg5 : tensor<?x?xf32>)15 -> tensor<?x?xf32> {16 %c0 = arith.constant 0 : index17 %c1 = arith.constant 1 : index18 %d0 = tensor.dim %arg0, %c0 : tensor<?x?xf32>19 %d1 = tensor.dim %arg0, %c1 : tensor<?x?xf32>20 %init = tensor.empty(%d0, %d1) : tensor<?x?xf32>21 %0 = linalg.generic #binary2Dpointwise22 ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>)23 outs(%init : tensor<?x?xf32>) {24 ^bb0(%arg6 : f32, %arg7 : f32, %arg8 : f32):25 %1 = arith.mulf %arg6, %arg7 : f3226 linalg.yield %1 : f3227 } -> tensor<?x?xf32>28 %2 = linalg.generic #binary2Dpointwise29 ins(%arg2, %arg3 : tensor<?x?xf32>, tensor<?x?xf32>)30 outs(%init : tensor<?x?xf32>) {31 ^bb0(%arg6 : f32, %arg7 : f32, %arg8 : f32):32 %3 = arith.mulf %arg6, %arg7 : f3233 linalg.yield %3 : f3234 } -> tensor<?x?xf32>35 %4 = linalg.generic #binary2Dpointwise36 ins(%arg4, %arg5 : tensor<?x?xf32>, tensor<?x?xf32>)37 outs(%init : tensor<?x?xf32>) {38 ^bb0(%arg6 : f32, %arg7 : f32, %arg8 : f32):39 %5 = arith.mulf %arg6, %arg7 : f3240 linalg.yield %5 : f3241 } -> tensor<?x?xf32>42 %6 = linalg.generic #ternary2Dpointwise43 ins(%0, %2, %4 : tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>)44 outs(%init : tensor<?x?xf32>) {45 ^bb0(%arg6 : f32, %arg7 : f32, %arg8 : f32, %arg9 : f32):46 %7 = arith.addf %arg6, %arg7 : f3247 %8 = arith.addf %7, %arg8 : f3248 linalg.yield %8 : f3249 } -> tensor<?x?xf32>50 return %6 : tensor<?x?xf32>51}52 53// CHECK-LABEL: func @test_fusion_limit54// CHECK-SAME: %[[ARG0:[a-zA-z0-9_]+]]: tensor<?x?xf32>55// CHECK-SAME: %[[ARG1:[a-zA-z0-9_]+]]: tensor<?x?xf32>56// CHECK-SAME: %[[ARG2:[a-zA-z0-9_]+]]: tensor<?x?xf32>57// CHECK-SAME: %[[ARG3:[a-zA-z0-9_]+]]: tensor<?x?xf32>58// CHECK-SAME: %[[ARG4:[a-zA-z0-9_]+]]: tensor<?x?xf32>59// CHECK-SAME: %[[ARG5:[a-zA-z0-9_]+]]: tensor<?x?xf32>60// CHECK: %[[OP1:.+]] = linalg.generic {{.+}} ins(%[[ARG2]], %[[ARG3]]61// CHECK: %[[OP2:.+]] = linalg.generic {{.+}} ins(%[[ARG4]], %[[ARG5]]62// CHECK: %[[OP3:.+]] = linalg.generic {{.+}} ins(%[[ARG0]], %[[ARG1]], %[[OP1]], %[[OP2]]63// CHECK: return %[[OP3]]64