// RUN: mlir-opt %s -test-linalg-elementwise-fusion-patterns=fuse-generic-ops-control -split-input-file | FileCheck %s #map = affine_map<(d0, d1) -> (d0, d1)> func.func @drop_unused_producer_result(%arg0 : tensor, %arg1 : tensor) -> tensor { %0:2 = linalg.generic { indexing_maps = [#map, #map, #map], iterator_types = ["parallel", "parallel"]} ins(%arg0 : tensor) outs(%arg0, %arg0 : tensor, tensor) { ^bb0(%b0: f32, %b1: f32, %b2: f32): %1 = arith.addf %b0, %b0 : f32 %2 = arith.mulf %b0, %b0 : f32 linalg.yield %1, %2 : f32, f32 } -> (tensor, tensor) %3 = linalg.generic { indexing_maps = [#map, #map, #map], iterator_types = ["parallel", "parallel"]} ins(%0#0, %arg1 : tensor, tensor) outs(%arg0 : tensor) { ^bb0(%b0: f32, %b1: f32, %b2: f32): %4 = arith.subf %b0, %b1 : f32 linalg.yield %4 : f32 } -> tensor return %3 : tensor } // CHECK-LABEL: func @drop_unused_producer_result // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor // CHECK: %[[FUSED_OP:.+]] = linalg.generic // CHECK-SAME: ins(%[[ARG0]], %[[ARG1]] : // CHECK: return %[[FUSED_OP]]