diff options
author | A. Unique TensorFlower <gardener@tensorflow.org> | 2018-08-23 11:10:41 -0700 |
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committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-08-23 11:18:30 -0700 |
commit | 4e2203c04f24493fbb88f34ed0e232a2ebb54ea1 (patch) | |
tree | 8c6353b0401160df2f2dd17c8991b0af1832f209 /tensorflow/compiler/xla/service/hlo_dataflow_analysis_test.cc | |
parent | dfcb6d67d53e36dacdce57dd763190a574d8edeb (diff) |
[TF:XLA] Make the two functions for computing HLO buffer interference consistent.
Consider only real uses of fusion parameters when computing buffer interference
using HloDataflowAnalysis.
This is a step in unifying our HLO dataflow framework
to a single source of truth and improves HloOrdering::LiveRangeStrictlyBefore
to match the behavior of BufferLiveness::live_range_strictly_before (which uses
TuplePointsToAnalysis)
PiperOrigin-RevId: 209966644
Diffstat (limited to 'tensorflow/compiler/xla/service/hlo_dataflow_analysis_test.cc')
-rw-r--r-- | tensorflow/compiler/xla/service/hlo_dataflow_analysis_test.cc | 48 |
1 files changed, 48 insertions, 0 deletions
diff --git a/tensorflow/compiler/xla/service/hlo_dataflow_analysis_test.cc b/tensorflow/compiler/xla/service/hlo_dataflow_analysis_test.cc index 4755c4a0cf..d1a96c10f8 100644 --- a/tensorflow/compiler/xla/service/hlo_dataflow_analysis_test.cc +++ b/tensorflow/compiler/xla/service/hlo_dataflow_analysis_test.cc @@ -1963,6 +1963,54 @@ TEST_F(DoesNotUseOperandBufferTest, FusedDynamicUpdateSlice) { EXPECT_FALSE(dataflow_analysis_->DoesNotUseOperandBuffer(tuple, {1}, fusion)); } +// Similar to FusedDynamicUpdateSlice above, but tests indirect uses of the +// parameter tuple. +TEST_F(DoesNotUseOperandBufferTest, IndirectUses) { + auto builder = HloComputation::Builder(TestName()); + + Shape data_shape = ShapeUtil::MakeShape(F32, {8}); + auto tuple_param = builder.AddInstruction(HloInstruction::CreateParameter( + 0, ShapeUtil::MakeTupleShape({data_shape, data_shape}), "tuple")); + auto t0 = builder.AddInstruction( + HloInstruction::CreateGetTupleElement(data_shape, tuple_param, 0)); + auto t1 = builder.AddInstruction( + HloInstruction::CreateGetTupleElement(data_shape, tuple_param, 1)); + // Swap the tuple elements. + auto tuple = builder.AddInstruction(HloInstruction::CreateTuple({t1, t0})); + + auto gte0 = builder.AddInstruction( + HloInstruction::CreateGetTupleElement(data_shape, tuple, 0)); + auto gte1 = builder.AddInstruction( + HloInstruction::CreateGetTupleElement(data_shape, tuple, 1)); + + // Create a DynamicUpdateSlice instruction of tuple element 1. + auto starts = builder.AddInstruction( + HloInstruction::CreateConstant(LiteralUtil::CreateR1<int32>({2}))); + auto update = builder.AddInstruction(HloInstruction::CreateConstant( + LiteralUtil::CreateR1<float>({2.f, 2.f, 2.f}))); + auto dynamic_update_slice = + builder.AddInstruction(HloInstruction::CreateDynamicUpdateSlice( + data_shape, gte1, update, starts)); + builder.AddInstruction( + HloInstruction::CreateTuple({gte0, dynamic_update_slice})); + + BuildModule(builder.Build()); + auto fusion = computation_->CreateFusionInstruction( + {dynamic_update_slice, starts, update, gte1}, + HloInstruction::FusionKind::kLoop); + RunAnalysis(); + + // The fusion instruction never uses tuple element 0, but does use element 1. + EXPECT_TRUE(dataflow_analysis_->DoesNotUseOperandBuffer(tuple, {0}, fusion)); + EXPECT_FALSE(dataflow_analysis_->DoesNotUseOperandBuffer(tuple, {1}, fusion)); + // The same holds for the parameter tuple, except that the tuple elements are + // swapped in 'tuple'. + EXPECT_TRUE( + dataflow_analysis_->DoesNotUseOperandBuffer(tuple_param, {1}, fusion)); + EXPECT_FALSE( + dataflow_analysis_->DoesNotUseOperandBuffer(tuple_param, {0}, fusion)); +} + class CanShareOperandBufferWithUserTest : public HloDataflowAnalysisTestBase {}; TEST_F(CanShareOperandBufferWithUserTest, ElementWiseSameShape) { |