| // RUN: mlir-opt -test-linalg-elementwise-fusion-patterns=fuse-multiuse-producer -split-input-file %s | FileCheck %s |
| |
| #map = affine_map<(d0, d1) -> (d0, d1)> |
| func.func @multi_use_producer(%arg0 : tensor<?x?xf32>, %arg1 : tensor<?x?xf32>, |
| %arg2 : tensor<?x?xf32>, %arg3 : tensor<?x?xf32>, %arg4 : tensor<?x?xf32>) |
| -> (tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>) { |
| %0:2 = linalg.generic { |
| indexing_maps = [#map, #map, #map], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0 : tensor<?x?xf32>) |
| outs(%arg1, %arg2 : tensor<?x?xf32>, tensor<?x?xf32>) { |
| ^bb0(%b0: f32, %b1 : f32, %b2 : f32): |
| %1 = arith.addf %b0, %b1 : f32 |
| linalg.yield %1, %1 : f32, f32 |
| } -> (tensor<?x?xf32>, tensor<?x?xf32>) |
| %2 = linalg.generic { |
| indexing_maps = [#map, #map, #map], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%0#1, %arg3 : tensor<?x?xf32>, tensor<?x?xf32>) |
| outs(%arg4 : tensor<?x?xf32>) { |
| ^bb0(%b0 : f32, %b1 : f32, %b2 : f32): |
| %3 = arith.mulf %b0, %b1 : f32 |
| linalg.yield %3 : f32 |
| } -> tensor<?x?xf32> |
| return %0#0, %0#1, %2 : tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32> |
| } |
| // CHECK: func @multi_use_producer( |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG4:[a-zA-Z0-9]+]]: tensor<?x?xf32>) |
| // CHECK: %[[RESULT:.+]]:3 = linalg.generic |
| // CHECK: return %[[RESULT]]#0, %[[RESULT]]#1, %[[RESULT]]#2 |
