/* 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/tuple_points_to_analysis.h"

#include <map>
#include <memory>

#include "tensorflow/compiler/xla/literal_util.h"
#include "tensorflow/compiler/xla/service/hlo_matchers.h"
#include "tensorflow/compiler/xla/service/hlo_opcode.h"
#include "tensorflow/compiler/xla/service/instruction_fusion.h"
#include "tensorflow/compiler/xla/shape_util.h"
#include "tensorflow/compiler/xla/test.h"
#include "tensorflow/compiler/xla/test_helpers.h"
#include "tensorflow/compiler/xla/tests/hlo_test_base.h"
#include "tensorflow/compiler/xla/xla_data.pb.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/test.h"

namespace op = xla::testing::opcode_matchers;

namespace xla {
namespace {

using ::testing::UnorderedElementsAreArray;
using ::testing::UnorderedElementsAre;

class TuplePointsToAnalysisTest : public HloTestBase {
 protected:
  // Builds a module with the given entry computation and runs points to
  // analysis.
  void BuildModuleAndRunAnalysis(std::unique_ptr<HloComputation> computation) {
    BuildModule(std::move(computation));
    RunAnalysis();
  }

  void BuildModule(std::unique_ptr<HloComputation> computation) {
    module_.reset(new HloModule(TestName()));
    module_->AddEntryComputation(std::move(computation));
  }

  void RunAnalysis() {
    CHECK_NOTNULL(module_.get());
    points_to_analysis_ =
        TuplePointsToAnalysis::Run(module_.get()).ConsumeValueOrDie();
  }

  // Returns the LogicalBuffer defined at the given instruction and
  // index. CHECKs if no buffer is defined at that point.
  const LogicalBuffer* const GetBuffer(const HloInstruction* instruction,
                                       const ShapeIndex& index) {
    const std::vector<const LogicalBuffer*>& pointed_to =
        points_to_analysis_->GetPointsToSet(instruction).element(index);
    CHECK_EQ(1, pointed_to.size());
    CHECK_EQ(instruction, pointed_to[0]->instruction());
    CHECK(index == pointed_to[0]->index());
    return pointed_to[0];
  }

  // Checks that the given points-to set contains exactly (unordered) the given
  // LogicalBuffers.
  void ExpectHasBuffers(
      const std::vector<const LogicalBuffer*>& points_to_set,
      tensorflow::gtl::ArraySlice<const LogicalBuffer*> buffers) {
    std::vector<const LogicalBuffer*> vec(buffers.begin(), buffers.end());
    EXPECT_THAT(points_to_set, UnorderedElementsAreArray(vec));
  }

  // Checks that the given points-to set contains exactly (unordered) the
  // top-level buffers of the given instructions.
  void ExpectHasTopLevelBuffers(
      const std::vector<const LogicalBuffer*>& points_to_set,
      tensorflow::gtl::ArraySlice<HloInstruction*> instructions) {
    std::vector<const LogicalBuffer*> buffers;
    for (auto instruction : instructions) {
      buffers.push_back(GetBuffer(instruction, /*index=*/{}));
    }
    ExpectHasBuffers(points_to_set, buffers);
  }

  // Overload which takes a std::set instead of a std::vector.
  void ExpectHasTopLevelBuffers(
      const tensorflow::gtl::FlatSet<const LogicalBuffer*>& points_to_set,
      tensorflow::gtl::ArraySlice<HloInstruction*> instructions) {
    ExpectHasTopLevelBuffers(std::vector<const LogicalBuffer*>(
                                 points_to_set.begin(), points_to_set.end()),
                             instructions);
  }

  // Checks that the buffer defined at the given instruction and index has
  // aliases which are exactly (unordered) the given instruction/index pairs.
  void ExpectHasBufferAliases(
      const HloInstruction* instruction, const ShapeIndex& index,
      tensorflow::gtl::ArraySlice<std::pair<HloInstruction*, ShapeIndex>>
          expected) {
    const LogicalBuffer* buffer =
        points_to_analysis_->GetBufferDefinedAt(instruction, index)
            .ValueOrDie();
    std::vector<BufferAlias> expected_aliases;
    for (auto& pair : expected) {
      expected_aliases.push_back(BufferAlias(*buffer, pair.first, pair.second));
    }
    EXPECT_THAT(points_to_analysis_->GetBufferAliases(*buffer),
                UnorderedElementsAreArray(expected_aliases));
  }

  std::unique_ptr<HloModule> module_;
  std::unique_ptr<TuplePointsToAnalysis> points_to_analysis_;
};

TEST_F(TuplePointsToAnalysisTest, SimpleTuple) {
  auto builder = HloComputation::Builder(TestName());
  auto constant1 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1.0)));
  auto constant2 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(2.0)));
  auto tuple = builder.AddInstruction(
      HloInstruction::CreateTuple({constant1, constant2}));

  BuildModuleAndRunAnalysis(builder.Build());
  EXPECT_EQ(1, points_to_analysis_->GetPointsToSet(constant1).size());
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(constant1).element({}), {constant1});
  EXPECT_TRUE(
      points_to_analysis_->GetPointsToSet(constant1).tuple_sources({}).empty());
  EXPECT_TRUE(points_to_analysis_->GetPointsToSet(tuple).IsDistinct());

  EXPECT_EQ(1, points_to_analysis_->GetPointsToSet(constant2).size());
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(constant2).element({}), {constant2});
  EXPECT_TRUE(
      points_to_analysis_->GetPointsToSet(constant2).tuple_sources({}).empty());

  EXPECT_EQ(3, points_to_analysis_->GetPointsToSet(tuple).size());
  EXPECT_FALSE(points_to_analysis_->GetPointsToSet(tuple).IsAmbiguous());
  EXPECT_THAT(points_to_analysis_->GetPointsToSet(tuple).tuple_sources({}),
              UnorderedElementsAre(tuple));

  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).CreateFlattenedSet(),
      {constant1, constant2, tuple});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({}), {tuple});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({0}), {constant1});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({1}), {constant2});

  const PointsToSet& tuple_points_to_set =
      points_to_analysis_->GetPointsToSet(tuple);
  EXPECT_TRUE(tuple_points_to_set.ContainsBufferAtIndex(
      *GetBuffer(constant1, {}), {0}));
  EXPECT_TRUE(tuple_points_to_set.ContainsBufferAtIndex(
      *GetBuffer(constant2, {}), {1}));
  EXPECT_FALSE(tuple_points_to_set.ContainsBufferAtIndex(
      *GetBuffer(constant2, {}), {0}));
  EXPECT_TRUE(tuple_points_to_set.ContainsBuffer(*GetBuffer(constant1, {})));
  EXPECT_TRUE(tuple_points_to_set.ContainsBuffer(*GetBuffer(constant2, {})));
}

TEST_F(TuplePointsToAnalysisTest, NestedTuple) {
  // Create a (nested) tuple containing an inner tuple. The points-to set of the
  // outer tuple should contain all elements of the points-to set of the inner
  // tuple.
  auto builder = HloComputation::Builder(TestName());
  auto constant1 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1.0)));
  auto constant2 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(2.0)));
  auto inner_tuple = builder.AddInstruction(
      HloInstruction::CreateTuple({constant1, constant2}));

  auto constant3 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(3.0)));
  auto tuple = builder.AddInstruction(
      HloInstruction::CreateTuple({inner_tuple, constant3}));

  BuildModuleAndRunAnalysis(builder.Build());
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(constant1).element({}), {constant1});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(constant2).element({}), {constant2});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(constant3).element({}), {constant3});

  EXPECT_EQ(3, points_to_analysis_->GetPointsToSet(inner_tuple).size());
  EXPECT_FALSE(points_to_analysis_->GetPointsToSet(inner_tuple).IsAmbiguous());
  EXPECT_TRUE(points_to_analysis_->GetPointsToSet(inner_tuple).IsDistinct());
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(inner_tuple).CreateFlattenedSet(),
      {constant1, constant2, inner_tuple});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(inner_tuple).element({}),
      {inner_tuple});
  EXPECT_THAT(
      points_to_analysis_->GetPointsToSet(inner_tuple).tuple_sources({}),
      UnorderedElementsAre(inner_tuple));

  EXPECT_EQ(5, points_to_analysis_->GetPointsToSet(tuple).size());
  EXPECT_FALSE(points_to_analysis_->GetPointsToSet(tuple).IsAmbiguous());
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).CreateFlattenedSet(),
      {constant1, constant2, constant3, inner_tuple, tuple});

  EXPECT_THAT(points_to_analysis_->GetPointsToSet(tuple).tuple_sources({}),
              UnorderedElementsAre(tuple));
  EXPECT_THAT(points_to_analysis_->GetPointsToSet(tuple).tuple_sources({0}),
              UnorderedElementsAre(inner_tuple));
  EXPECT_TRUE(
      points_to_analysis_->GetPointsToSet(tuple).tuple_sources({1}).empty());

  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({0}), {inner_tuple});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({0, 0}), {constant1});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({0, 1}), {constant2});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({1}), {constant3});
}

TEST_F(TuplePointsToAnalysisTest, GetTupleElement) {
  // Create a nested tuple, then extract the inner tuple with GetTupleElement.
  // The points-to set of the GetTupleElement should be the same as the inner
  // tuple.
  auto builder = HloComputation::Builder(TestName());
  auto constant1 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1.0)));
  auto constant2 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(2.0)));
  auto inner_tuple = builder.AddInstruction(
      HloInstruction::CreateTuple({constant1, constant2}));

  auto constant3 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(3.0)));
  auto tuple = builder.AddInstruction(
      HloInstruction::CreateTuple({inner_tuple, constant3}));

  auto get_tuple_element = builder.AddInstruction(
      HloInstruction::CreateGetTupleElement(inner_tuple->shape(), tuple, 0));

  BuildModuleAndRunAnalysis(builder.Build());

  auto& points_to_set = points_to_analysis_->GetPointsToSet(get_tuple_element);
  EXPECT_EQ(3, points_to_set.size());
  EXPECT_FALSE(points_to_set.IsAmbiguous());
  EXPECT_TRUE(points_to_set.IsDistinct());
  ExpectHasTopLevelBuffers(points_to_set.CreateFlattenedSet(),
                           {constant1, constant2, inner_tuple});
  ExpectHasTopLevelBuffers(points_to_set.element({}), {inner_tuple});

  EXPECT_THAT(points_to_set.tuple_sources({}),
              UnorderedElementsAre(inner_tuple));
}

TEST_F(TuplePointsToAnalysisTest, DuplicatedElement) {
  // Create a tuple which contains duplicate elements.
  auto builder = HloComputation::Builder(TestName());
  auto constant = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1.0)));
  auto tuple = builder.AddInstruction(
      HloInstruction::CreateTuple({constant, constant, constant}));

  BuildModuleAndRunAnalysis(builder.Build());

  EXPECT_EQ(2, points_to_analysis_->GetPointsToSet(tuple).size());
  EXPECT_FALSE(points_to_analysis_->GetPointsToSet(tuple).IsAmbiguous());
  EXPECT_FALSE(points_to_analysis_->GetPointsToSet(tuple).IsDistinct());
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({}), {tuple});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).CreateFlattenedSet(),
      {constant, tuple});
}

TEST_F(TuplePointsToAnalysisTest, TupleCopy) {
  // Create a copy (HloOpcode::kCopy) of a tuple. The points to sets should be
  // the same.
  auto builder = HloComputation::Builder(TestName());
  auto constant1 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1.0)));
  auto constant2 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(2.0)));
  auto tuple = builder.AddInstruction(
      HloInstruction::CreateTuple({constant1, constant2}));
  auto copy = builder.AddInstruction(
      HloInstruction::CreateUnary(tuple->shape(), HloOpcode::kCopy, tuple));

  BuildModuleAndRunAnalysis(builder.Build());

  EXPECT_FALSE(points_to_analysis_->GetPointsToSet(copy).IsAmbiguous());
  EXPECT_TRUE(points_to_analysis_->GetPointsToSet(copy).IsDistinct());
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).CreateFlattenedSet(),
      {constant1, constant2, tuple});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(copy).element({}), {copy});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(copy).CreateFlattenedSet(),
      {constant1, constant2, copy});
}

TEST_F(TuplePointsToAnalysisTest, TupleSelect) {
  // Select from two different tuples. This should create an ambiguous points to
  // set containing the union of both sides.
  auto builder = HloComputation::Builder(TestName());
  auto constant1 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1.0)));
  auto constant2 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(2.0)));
  auto tuple1 = builder.AddInstruction(
      HloInstruction::CreateTuple({constant1, constant2}));
  auto tuple2 = builder.AddInstruction(
      HloInstruction::CreateTuple({constant2, constant2}));

  auto pred = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<bool>(false)));
  auto select = builder.AddInstruction(HloInstruction::CreateTernary(
      tuple1->shape(), HloOpcode::kSelect, pred, tuple1, tuple2));

  BuildModuleAndRunAnalysis(builder.Build());

  auto& points_to_set = points_to_analysis_->GetPointsToSet(select);
  EXPECT_EQ(3, points_to_set.size());
  EXPECT_TRUE(points_to_set.IsAmbiguous());
  EXPECT_FALSE(points_to_set.IsDistinct());
  ExpectHasTopLevelBuffers(points_to_set.element({}), {select});
  ExpectHasTopLevelBuffers(points_to_set.element({0}), {constant1, constant2});
  ExpectHasTopLevelBuffers(points_to_set.element({1}), {constant2});
  ExpectHasTopLevelBuffers(points_to_set.CreateFlattenedSet(),
                           {constant1, constant2, select});
}

TEST_F(TuplePointsToAnalysisTest, SelectTupleParameters) {
  // Create a Select which selects between two tuple parameters. Verify the
  // points-to sets and tuple sources are properly set.
  Shape tuple_shape = ShapeUtil::MakeTupleShape(
      {ShapeUtil::MakeShape(F32, {1, 2, 3}), ShapeUtil::MakeShape(U32, {5})});

  auto builder = HloComputation::Builder(TestName());
  auto param0 = builder.AddInstruction(
      HloInstruction::CreateParameter(0, tuple_shape, "param0"));
  auto param1 = builder.AddInstruction(
      HloInstruction::CreateParameter(1, tuple_shape, "param1"));
  auto pred = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<bool>(false)));
  auto select = builder.AddInstruction(HloInstruction::CreateTernary(
      tuple_shape, HloOpcode::kSelect, pred, param0, param1));
  auto copy = builder.AddInstruction(
      HloInstruction::CreateUnary(tuple_shape, HloOpcode::kCopy, select));

  BuildModuleAndRunAnalysis(builder.Build());

  // The points-to set of each element of a tuple parameters should be itself
  // with the appropriate index.
  ExpectHasBuffers(points_to_analysis_->GetPointsToSet(param0).element({}),
                   {GetBuffer(param0, {})});
  ExpectHasBuffers(points_to_analysis_->GetPointsToSet(param0).element({0}),
                   {GetBuffer(param0, {0})});
  ExpectHasBuffers(points_to_analysis_->GetPointsToSet(param0).element({1}),
                   {GetBuffer(param0, {1})});

  // Select's point-to set of its subelements should be the respective
  // subelements of param0 and param1. The top-level buffer, however, does not
  // alias as it is created by the select instruction.
  ExpectHasBuffers(points_to_analysis_->GetPointsToSet(select).element({}),
                   {GetBuffer(select, {})});
  ExpectHasBuffers(points_to_analysis_->GetPointsToSet(select).element({0}),
                   {GetBuffer(param0, {0}), GetBuffer(param1, {0})});
  ExpectHasBuffers(points_to_analysis_->GetPointsToSet(select).element({1}),
                   {GetBuffer(param0, {1}), GetBuffer(param1, {1})});

  // Copy should be identical to select other than the top-level buffer.
  ExpectHasBuffers(points_to_analysis_->GetPointsToSet(copy).element({}),
                   {GetBuffer(copy, {})});
  ExpectHasBuffers(points_to_analysis_->GetPointsToSet(copy).element({0}),
                   {GetBuffer(param0, {0}), GetBuffer(param1, {0})});
  ExpectHasBuffers(points_to_analysis_->GetPointsToSet(copy).element({1}),
                   {GetBuffer(param0, {1}), GetBuffer(param1, {1})});
}

TEST_F(TuplePointsToAnalysisTest, UnambiguousTupleSelect) {
  // Select from two identical tuples. The result should not be ambiguous.
  auto builder = HloComputation::Builder(TestName());
  auto constant1 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1.0)));
  auto constant2 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(2.0)));
  auto tuple1 = builder.AddInstruction(
      HloInstruction::CreateTuple({constant1, constant2}));
  auto tuple2 = builder.AddInstruction(
      HloInstruction::CreateTuple({constant1, constant2}));

  auto pred = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<bool>(false)));
  auto select = builder.AddInstruction(HloInstruction::CreateTernary(
      tuple1->shape(), HloOpcode::kSelect, pred, tuple1, tuple2));

  BuildModuleAndRunAnalysis(builder.Build());

  auto& points_to_set = points_to_analysis_->GetPointsToSet(select);
  EXPECT_EQ(3, points_to_set.size());
  EXPECT_FALSE(points_to_set.IsAmbiguous());
  EXPECT_TRUE(points_to_set.IsDistinct());
  ExpectHasTopLevelBuffers(points_to_set.element({}), {select});
  ExpectHasTopLevelBuffers(points_to_set.element({0}), {constant1});
  ExpectHasTopLevelBuffers(points_to_set.element({1}), {constant2});
  ExpectHasTopLevelBuffers(points_to_set.CreateFlattenedSet(),
                           {constant1, constant2, select});
}

TEST_F(TuplePointsToAnalysisTest, NestedTupleSelect) {
  // Select from nested tuples. Verify that the nested points-to sets contain
  // the right values.
  auto builder = HloComputation::Builder(TestName());
  auto constant1 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1.0)));
  auto constant2 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(2.0)));
  auto inner_tuple1 = builder.AddInstruction(
      HloInstruction::CreateTuple({constant1, constant2}));
  auto inner_tuple2 = builder.AddInstruction(
      HloInstruction::CreateTuple({constant2, constant2}));

  auto tuple1 =
      builder.AddInstruction(HloInstruction::CreateTuple({inner_tuple1}));
  auto tuple2 =
      builder.AddInstruction(HloInstruction::CreateTuple({inner_tuple2}));

  auto pred = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<bool>(false)));
  auto select = builder.AddInstruction(HloInstruction::CreateTernary(
      tuple1->shape(), HloOpcode::kSelect, pred, tuple1, tuple2));

  BuildModuleAndRunAnalysis(builder.Build());

  auto& points_to_set = points_to_analysis_->GetPointsToSet(select);
  EXPECT_EQ(5, points_to_set.size());
  EXPECT_TRUE(points_to_set.IsAmbiguous());
  EXPECT_FALSE(points_to_set.IsDistinct());

  // Verify points-to set.
  ExpectHasTopLevelBuffers(points_to_set.element({}), {select});
  ExpectHasTopLevelBuffers(points_to_set.element({0}),
                           {inner_tuple1, inner_tuple2});
  ExpectHasTopLevelBuffers(points_to_set.element({0, 0}),
                           {constant1, constant2});
  ExpectHasTopLevelBuffers(points_to_set.element({0, 1}), {constant2});

  // Verify tuple sources.
  EXPECT_THAT(points_to_set.tuple_sources({}),
              UnorderedElementsAre(tuple1, tuple2));
  EXPECT_THAT(points_to_set.tuple_sources({0}),
              UnorderedElementsAre(inner_tuple1, inner_tuple2));
  EXPECT_EQ(0, points_to_set.tuple_sources({0, 0}).size());
  EXPECT_EQ(0, points_to_set.tuple_sources({0, 1}).size());
}

TEST_F(TuplePointsToAnalysisTest, TupleWithBitcast) {
  // Bitcast is an alias of its operand. A tuple with a bitcast element should
  // have the operand of the bitcast in its points-to set.
  auto builder = HloComputation::Builder(TestName());
  auto constant1 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1.0)));
  auto constant2 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(2.0)));
  auto bitcast = builder.AddInstruction(HloInstruction::CreateUnary(
      constant2->shape(), HloOpcode::kBitcast, constant2));
  auto tuple =
      builder.AddInstruction(HloInstruction::CreateTuple({constant1, bitcast}));

  BuildModuleAndRunAnalysis(builder.Build());

  EXPECT_EQ(1, points_to_analysis_->GetPointsToSet(bitcast).size());
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(bitcast).element({}), {constant2});
  EXPECT_TRUE(
      points_to_analysis_->GetPointsToSet(bitcast).tuple_sources({}).empty());

  EXPECT_EQ(3, points_to_analysis_->GetPointsToSet(tuple).size());
  EXPECT_FALSE(points_to_analysis_->GetPointsToSet(tuple).IsAmbiguous());
  EXPECT_THAT(points_to_analysis_->GetPointsToSet(tuple).tuple_sources({}),
              UnorderedElementsAre(tuple));

  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).CreateFlattenedSet(),
      {constant1, constant2, tuple});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({}), {tuple});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({0}), {constant1});
  ExpectHasTopLevelBuffers(
      points_to_analysis_->GetPointsToSet(tuple).element({1}), {constant2});
}

TEST_F(TuplePointsToAnalysisTest, PointsToTupleConstantElements) {
  // Construct a tuple constant and kCopy it. Verify the points-to set of the
  // copy correctly correctly points into the nested elements of the constant.
  auto builder = HloComputation::Builder(TestName());
  auto tuple_constant = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::MakeTuple(
          {LiteralUtil::CreateR2<float>({{1.0}, {2.0}}).get(),
           LiteralUtil::CreateR1<float>({2.0, 42}).get()})));
  auto copy = builder.AddInstruction(HloInstruction::CreateUnary(
      tuple_constant->shape(), HloOpcode::kCopy, tuple_constant));

  BuildModuleAndRunAnalysis(builder.Build());

  auto& points_to_set = points_to_analysis_->GetPointsToSet(copy);

  ExpectHasBuffers(points_to_set.element({}), {GetBuffer(copy, {})});
  ExpectHasBuffers(points_to_set.element({0}),
                   {GetBuffer(tuple_constant, {0})});
  ExpectHasBuffers(points_to_set.element({1}),
                   {GetBuffer(tuple_constant, {1})});
}

TEST_F(TuplePointsToAnalysisTest, BufferAliases) {
  // Create a nested tuple in which individual elements appear multiple
  // times. Verify buffer alias sets.
  auto builder = HloComputation::Builder(TestName());
  auto constant1 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1.0)));
  auto constant2 = builder.AddInstruction(
      HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(2.0)));
  auto inner_tuple = builder.AddInstruction(
      HloInstruction::CreateTuple({constant1, constant2}));
  auto tuple = builder.AddInstruction(
      HloInstruction::CreateTuple({inner_tuple, constant2}));

  BuildModuleAndRunAnalysis(builder.Build());

  ExpectHasBufferAliases(
      constant1, /*index=*/{},
      {{constant1, {}}, {inner_tuple, {0}}, {tuple, {0, 0}}});
  ExpectHasBufferAliases(
      constant2, /*index=*/{},
      {{constant2, {}}, {inner_tuple, {1}}, {tuple, {0, 1}}, {tuple, {1}}});
  ExpectHasBufferAliases(inner_tuple, /*index=*/{},
                         {{inner_tuple, {}}, {tuple, {0}}});
  ExpectHasBufferAliases(tuple, /*index=*/{}, {{tuple, {}}});
}

class FusionPointsToAnalysisTest : public TuplePointsToAnalysisTest {
 protected:
  // Builds a computation, runs instruction fusion HloPass, runs points-to
  // analysis, then checks for expected results (see unit test cases for
  // example computation graphs).
  void Run(const bool add_additional_gte0_user) {
    Shape input_shape = ShapeUtil::MakeShape(F32, {8});
    Shape update_shape = ShapeUtil::MakeShape(F32, {3});
    Shape starts_shape = ShapeUtil::MakeShape(S32, {1});
    Shape tuple_shape =
        ShapeUtil::MakeTupleShape({input_shape, update_shape, starts_shape});

    auto builder = HloComputation::Builder(TestName());
    // Create tuple-shaped parameter.
    auto tuple_param0 = builder.AddInstruction(
        HloInstruction::CreateParameter(0, tuple_shape, "param0"));
    // Create 'tuple_element1' = GetTupleElement(tuple_param0, 1).
    auto tuple_element1 = builder.AddInstruction(
        HloInstruction::CreateGetTupleElement(update_shape, tuple_param0, 1));
    auto ones = builder.AddInstruction(HloInstruction::CreateConstant(
        LiteralUtil::CreateR1<float>({1.f, 1.f, 1.f, 1.f})));
    // Create 'update' = Add(GetTupleElement(tuple_param0, 1), ones)
    auto update = builder.AddInstruction(HloInstruction::CreateBinary(
        update_shape, HloOpcode::kAdd, tuple_element1, ones));
    // Create 'input' = GetTupleElement(tuple_param0, 0).
    auto input = builder.AddInstruction(
        HloInstruction::CreateGetTupleElement(input_shape, tuple_param0, 0));

    if (add_additional_gte0_user) {
      // Create 'slice' as an additional user of 'input'.
      auto slice = builder.AddInstruction(
          HloInstruction::CreateSlice(update_shape, input, {0}, {3}));
      // Modify 'update' to take 'slice' output.
      update = builder.AddInstruction(HloInstruction::CreateBinary(
          update_shape, HloOpcode::kAdd, update, slice));
    }

    // Create slice 'starts' = GetTupleElement(tuple_param0, 2).
    auto starts = builder.AddInstruction(
        HloInstruction::CreateGetTupleElement(starts_shape, tuple_param0, 2));
    // Update 'input' with 'update' at dynamic 'starts' indices.
    builder.AddInstruction(HloInstruction::CreateDynamicUpdateSlice(
        input_shape, input, update, starts));

    // Build computation and add it to module as entry computation.
    BuildModule(builder.Build());
    // Run instruction fusion HloPass.
    EXPECT_TRUE(InstructionFusion(InstructionFusion::IsExpensive)
                    .Run(module_.get())
                    .ValueOrDie());
    // Get computation root instruction (should be a kFusion).
    auto* fusion = module_->entry_computation()->root_instruction();
    EXPECT_THAT(fusion, op::Fusion(tuple_param0));
    // Run points-to analysis (should include fused instructions from 'fusion').
    RunAnalysis();

    // Check points-to set of fusion parameter associated with 'tuple_param0'.
    auto* fusion_param = GetFusionParameterForOperand(fusion, tuple_param0);
    ExpectHasBuffers(
        points_to_analysis_->GetPointsToSet(fusion_param).element({}),
        {GetBuffer(fusion_param, {})});
    ExpectHasBuffers(
        points_to_analysis_->GetPointsToSet(fusion_param).element({0}),
        {GetBuffer(fusion_param, {0})});
    ExpectHasBuffers(
        points_to_analysis_->GetPointsToSet(fusion_param).element({1}),
        {GetBuffer(fusion_param, {1})});
    ExpectHasBuffers(
        points_to_analysis_->GetPointsToSet(fusion_param).element({2}),
        {GetBuffer(fusion_param, {2})});

    // Check that Gte at tuple_index = 0 points-to fusion_param({0})
    auto fused_gte0 = GetUniqueFusionParameterUserAt(fusion_param, 0);
    ExpectHasBuffers(
        points_to_analysis_->GetPointsToSet(fused_gte0).element({}),
        {GetBuffer(fusion_param, {0})});
    // Check that Gte at tuple_index = 1 points-to fusion_param({1})
    auto fused_gte1 = GetUniqueFusionParameterUserAt(fusion_param, 1);
    ExpectHasBuffers(
        points_to_analysis_->GetPointsToSet(fused_gte1).element({}),
        {GetBuffer(fusion_param, {1})});
    // Check that Gte at tuple_index = 2 points-to fusion_param({2})
    auto fused_gte2 = GetUniqueFusionParameterUserAt(fusion_param, 2);
    ExpectHasBuffers(
        points_to_analysis_->GetPointsToSet(fused_gte2).element({}),
        {GetBuffer(fusion_param, {2})});

    // Check buffer aliases of 'fusion_param' at shape index {0}.
    ExpectHasBufferAliases(fusion_param, /*index=*/{0},
                           {{fusion_param, {0}}, {fused_gte0, {}}});
    // Check buffer aliases of 'fusion_param' at shape index {1}.
    ExpectHasBufferAliases(fusion_param, /*index=*/{1},
                           {{fusion_param, {1}}, {fused_gte1, {}}});
    // Check buffer aliases of 'fusion_param' at shape index {2}.
    ExpectHasBufferAliases(fusion_param, /*index=*/{2},
                           {{fusion_param, {2}}, {fused_gte2, {}}});

    // Check number of users of 'fusion_param' aliases at shape index {0}.
    ExpectNumUsersOfAliases(fusion_param, {0},
                            add_additional_gte0_user ? 2 : 1);
  }

  // Returns fusion parameter (from 'fusion.fused_instructions') corresponding
  // to fusion 'operand'.
  HloInstruction* GetFusionParameterForOperand(HloInstruction* fusion,
                                               HloInstruction* operand) {
    auto it = std::find_if(
        fusion->fused_instructions().begin(),
        fusion->fused_instructions().end(),
        [=](const std::unique_ptr<HloInstruction>& fused) {
          return fused->opcode() == HloOpcode::kParameter &&
                 fusion->operand(fused->parameter_number()) == operand;
        });
    CHECK(it != fusion->fused_instructions().end());
    return (*it).get();
  }

  // Returns all users of 'fusion_paran' at 'tuple_index'.
  std::vector<HloInstruction*> GetFusionParameterUsersAt(
      HloInstruction* fusion_param, int64 tuple_index) {
    CHECK(ShapeUtil::IsTuple(fusion_param->shape()));
    std::vector<HloInstruction*> users_at_tuple_index;
    for (auto user : fusion_param->users()) {
      CHECK_EQ(HloOpcode::kGetTupleElement, user->opcode());
      if (user->tuple_index() == tuple_index) {
        users_at_tuple_index.push_back(user);
      }
    }
    return users_at_tuple_index;
  }

  // Returns the unique user of 'fusion_param' at 'tuple_index'.
  HloInstruction* GetUniqueFusionParameterUserAt(HloInstruction* fusion_param,
                                                 int64 tuple_index) {
    std::vector<HloInstruction*> users =
        GetFusionParameterUsersAt(fusion_param, tuple_index);
    CHECK_EQ(1, users.size());
    return users[0];
  }

  // Checks that the count of all users of all aliases of 'instruction' at
  // 'index' match 'expected_num_users'.
  void ExpectNumUsersOfAliases(const HloInstruction* instruction,
                               const ShapeIndex& index,
                               const int64 expected_num_users) {
    const auto* buffer = GetBuffer(instruction, index);
    int64 num_users = 0;
    for (const auto& alias : points_to_analysis_->GetBufferAliases(*buffer)) {
      for (auto user : alias.instruction()->users()) {
        if (user->opcode() == HloOpcode::kGetTupleElement && !index.empty()) {
          // Gte instructions only access the top-level buffer of their operand.
          continue;
        }
        ++num_users;
      }
    }
    EXPECT_EQ(expected_num_users, num_users);
  }
};

// Tests the points-to set of tuple-shaped fusion parameter 0 and all GTE users.
// Tests the alias set of tuple-shaped fusion parameter 0 at all shape indices.
// Tests that there is a single user of the aliases of tuple-shaped fusion
// parameter 0 at shape index {0}.
//
//             Param0    Const
//                 \      /
//                  Fusion
//                 /      \
//        FusionParam0   FusionParam1
//        /     |    \       |
//     Gte(0) Gte(2) Gte(1)  /
//        \     |      \    /
//         \    |       Add
//          \   |        /
//           \0 |2      /1
//          DynamicUpdateSlice  // fused root.
//
TEST_F(FusionPointsToAnalysisTest, FusionParam0OneUser) {
  Run(/*add_additional_gte0_user=*/false);
}

// Tests the points-to set of tuple-shaped fusion parameter 0 and all GTE users.
// Tests the alias set of tuple-shaped fusion parameter 0 at all shape indices.
// Tests that there are two users of the aliases of tuple-shaped fusion
// parameter 0 at shape index {0}.
//
//             Param0    Const
//                 \      /
//                  Fusion
//                 /      \
//        FusionParam0   FusionParam1
//        /     |    \       |
//     Gte(2) Gte(0) Gte(1)  /
//        \     |      \    /
//         \    |\      Add
//          \   | \      /
//           |  | Slice /
//           |  |   \  /
//           |  |   Add
//           |  |    |
//           |2 |0   |1
//          DynamicUpdateSlice  // fused root.
//
TEST_F(FusionPointsToAnalysisTest, FusionParam0TwoUsers) {
  Run(/*add_additional_gte0_user=*/true);
}

}  // namespace
}  // namespace xla
