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/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/compiler/xla/service/hlo_ordering.h"
#include <memory>
#include <string>
#include "tensorflow/compiler/xla/service/hlo_computation.h"
#include "tensorflow/compiler/xla/service/hlo_instruction.h"
#include "tensorflow/compiler/xla/service/hlo_opcode.h"
#include "tensorflow/compiler/xla/shape_util.h"
#include "tensorflow/compiler/xla/tests/hlo_test_base.h"
#include "tensorflow/compiler/xla/types.h"
#include "tensorflow/compiler/xla/xla_data.pb.h"
namespace xla {
namespace {
class HloOrderingTest : public HloTestBase {};
TEST_F(HloOrderingTest, LastUseScheduledFirst) {
// Tests scheduling of the following HLO code:
//
// %ab = abs(%param)
// %exp = exp(%param)
// %add = add(%ab, %exp)
// %negate = negate(%exp)
// %sub = subtract(%add, %negate)
//
// %add should be scheduled before %negate because %add is the last (and only)
// use of %ab. Scheduling %add first then frees up %ab's buffer.
const Shape vec = ShapeUtil::MakeShape(xla::F32, {42});
auto builder = HloComputation::Builder(TestName());
auto param =
builder.AddInstruction(HloInstruction::CreateParameter(0, vec, "param"));
auto ab = builder.AddInstruction(
HloInstruction::CreateUnary(vec, HloOpcode::kAbs, param));
auto exp = builder.AddInstruction(
HloInstruction::CreateUnary(vec, HloOpcode::kExp, param));
auto add = builder.AddInstruction(
HloInstruction::CreateBinary(vec, HloOpcode::kAdd, ab, exp));
auto negate = builder.AddInstruction(
HloInstruction::CreateUnary(vec, HloOpcode::kNegate, exp));
auto sub = builder.AddInstruction(
HloInstruction::CreateBinary(vec, HloOpcode::kSubtract, add, negate));
HloModule module(TestName());
module.AddEntryComputation(builder.Build());
TF_ASSIGN_OR_ASSERT_OK(
SequentialHloOrdering::HloModuleSequence sequence,
CreateMemoryMinimizingSequence(module, [](const LogicalBuffer& buffer) {
return ShapeUtil::ByteSizeOf(buffer.shape());
}));
// Verify that all instructions are in the sequence.
EXPECT_EQ(module.entry_computation()->instruction_count(),
sequence.at(module.entry_computation()).size());
// The first instruction should be the parameter and the last the root "sub".
EXPECT_EQ(param, sequence.at(module.entry_computation()).front());
EXPECT_EQ(sub, sequence.at(module.entry_computation()).back());
SequentialHloOrdering ordering(&module, sequence);
EXPECT_TRUE(ordering.ExecutesBefore(add, negate));
}
} // namespace
} // namespace xla
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