06514c5501
`isOpOperandCanBeDroppedAfterFusedLinalgs` crashes when `indexingMaps` is empty. This can occur when `producer` only has DPS init operands and `consumer ` only has a single DPS input operand (all operands are ignored and nothing gets added to `indexingMaps`). This is because `concatAffineMaps` wasn't handling the maps being empty properly. Similar to `canOpOperandsBeDroppedImpl`, I added an early return when the maps are of size zero. Additionally, `concatAffineMaps`'s declaration comment says it returns an empty map when `maps` is empty but it has no way to get the `MLIRContext` needed to construct the empty affine map when the array is empty. So, I changed this to take the context. __NOTE: concatAffineMaps now takes an MLIRContext to be able to construct an empty map in the case where `maps` is empty.__ --------- Signed-off-by: Ian Wood <ianwood2024@u.northwestern.edu> Co-authored-by: Quinn Dawkins <quinn.dawkins@gmail.com>
62 lines
2.5 KiB
MLIR
62 lines
2.5 KiB
MLIR
// RUN: mlir-opt %s -test-linalg-elementwise-fusion-patterns=fuse-generic-ops-control -split-input-file | FileCheck %s
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#map = affine_map<(d0, d1) -> (d0, d1)>
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func.func @drop_unused_producer_result(%arg0 : tensor<?x?xf32>,
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%arg1 : tensor<?x?xf32>) -> tensor<?x?xf32> {
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%0:2 = linalg.generic {
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indexing_maps = [#map, #map, #map],
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iterator_types = ["parallel", "parallel"]}
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ins(%arg0 : tensor<?x?xf32>) outs(%arg0, %arg0 : tensor<?x?xf32>, tensor<?x?xf32>) {
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^bb0(%b0: f32, %b1: f32, %b2: f32):
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%1 = arith.addf %b0, %b0 : f32
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%2 = arith.mulf %b0, %b0 : f32
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linalg.yield %1, %2 : f32, f32
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} -> (tensor<?x?xf32>, tensor<?x?xf32>)
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%3 = linalg.generic {
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indexing_maps = [#map, #map, #map],
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iterator_types = ["parallel", "parallel"]}
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ins(%0#0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) outs(%arg0 : tensor<?x?xf32>) {
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^bb0(%b0: f32, %b1: f32, %b2: f32):
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%4 = arith.subf %b0, %b1 : f32
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linalg.yield %4 : f32
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} -> tensor<?x?xf32>
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return %3 : tensor<?x?xf32>
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}
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// CHECK-LABEL: func @drop_unused_producer_result
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// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor<?x?xf32>
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// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor<?x?xf32>
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// CHECK: %[[FUSED_OP:.+]] = linalg.generic
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// CHECK-SAME: ins(%[[ARG0]], %[[ARG1]] :
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// CHECK: return %[[FUSED_OP]]
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// -----
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#map = affine_map<(d0) -> (d0)>
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func.func @handle_unused_operands(%arg0: tensor<8xf32>, %arg1: tensor<8xf32>) -> tensor<8xf32> {
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%cst_0 = arith.constant 0.000000e+00 : f32
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%cst_1 = arith.constant 1.000000e+00 : f32
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%0:2 = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel"]} outs(%arg0, %arg1 : tensor<8xf32>, tensor<8xf32>) {
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^bb0(%out: f32, %out_2: f32):
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%1 = linalg.index 0 : index
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%2 = arith.index_cast %1 : index to i64
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%3 = arith.sitofp %2 : i64 to f32
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%4 = arith.divf %3, %cst_0 : f32
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linalg.yield %3, %4 : f32, f32
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} -> (tensor<8xf32>, tensor<8xf32>)
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linalg.generic {indexing_maps = [#map], iterator_types = ["parallel"]} ins(%0#1 : tensor<8xf32>) {
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^bb0(%in: f32):
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%2 = arith.cmpf one, %in, %cst_1 : f32
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cf.assert %2, "Side effect op"
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linalg.yield
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}
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func.return %arg1 : tensor<8xf32>
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}
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// CHECK-LABEL: func @handle_unused_operands
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// CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor<8xf32>
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// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor<8xf32>
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// CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<8xf32>
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// CHECK: %[[FUSED_OP:.+]] = linalg.generic
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// CHECK-SAME: outs(%[[EMPTY]] :
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// CHECK-NOT: linalg.generic
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