#include "tsl/platform/statusor.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {

namespace {

using mlir::mhlo::test::GetMlirModuleFromString;

class VerifyClusteringPassTest : public testing::Test {
 protected:
  void CreateModule(const char* module_string) {
    TF_ASSERT_OK_AND_ASSIGN(module_,
                            GetMlirModuleFromString(module_string, &context_));

#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/util/tensor_bundle/tensor_bundle.h"
#include "tsl/platform/status.h"
#include "tsl/platform/status_matchers.h"

namespace tensorflow {
namespace quantization {
namespace {

using ::tensorflow::test::AsTensor;
using ::tensorflow::test::ExpectEqual;
using ::testing::IsEmpty;
using ::testing::Not;

REGISTER_OP("StreamOp").Output("output1: float");

TEST_F(DeviceKernelOpTest, TestStream) {
  auto my_compute_func = [](void* kernel, TF_OpKernelContext* ctx) {
    TF_Status* s = TF_NewStatus();
    SP_Stream stream = TF_GetStream(ctx, s);
    // Stream is always null if device is not a pluggable device. More test
    // cases will be added when pluggable device mechanism is supported.

}  // namespace gtest_internal

template <GTEST_$(n)_TYPENAMES_(T), GTEST_$(n)_TYPENAMES_(U)>
inline bool operator==(const GTEST_$(n)_TUPLE_(T)& t,
                       const GTEST_$(n)_TUPLE_(U)& u) {
  return gtest_internal::SameSizeTuplePrefixComparator<
      tuple_size<GTEST_$(n)_TUPLE_(T) >::value,
      tuple_size<GTEST_$(n)_TUPLE_(U) >::value>::Eq(t, u);
}

template <GTEST_$(n)_TYPENAMES_(T), GTEST_$(n)_TYPENAMES_(U)>

  TF_DeleteFunction(funcs[0]);
}

TEST_F(CApiExperimentalFunctionTest, EmptyGraphRemoveNonExistentFunction) {
  TF_GraphRemoveFunction(func_graph_, "wrong_name", s_);
  EXPECT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s_));
  EXPECT_EQ(string("Tried to remove non-existent function 'wrong_name'."),
            string(TF_Message(s_)));
}

TEST_F(CApiExperimentalFunctionTest, GraphRemoveNonExistentFunction) {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/core/platform/test.h"

namespace mlir {
namespace quant {
namespace {

using ::testing::NotNull;
using ::testing::SizeIs;

using ConstantFoldingTest = ::mlir::quant::QuantizationTestBase;

TEST_F(ConstantFoldingTest, FoldLargeConstant) {
  constexpr absl::string_view kModuleCode = R"mlir(
    module {

        def header1 = includeDir.createFile("test.h")
        includePaths << includeDir

        macros << macro("TEST", '"test.h"')
        macroFunctions << macroFunction("TEST1", "TEST")
        macros << macro("TEST2", "TEST1()")
        macros << macro("TEST3", "TEST2")
        macros << unresolvableMacro("IGNORE")

        expect:
        def result = resolve(include('TEST3'))
        result.complete

}

// This value parameterized test allows us to test both TFRT
// and non TFRT runtimes.
// https://github.com/google/googletest/blob/dcc92d0ab6c4ce022162a23566d44f673251eee4/googletest/docs/advanced.md#value-parameterized-tests
class CSavedModelAPITest : public ::testing::TestWithParam<bool> {};

TEST_P(CSavedModelAPITest, LoadsSavedModelWithTags) {
  TF_Status* status = TF_NewStatus();

  std::unique_ptr<ProcessFunctionLibraryRuntime> pflr_;

  std::unique_ptr<OpKernel> kernel_;
};

AttrValue BoolAttr(bool b) {
  AttrValue v;
  v.set_b(b);
  return v;
}

TEST_F(XlaKernelCreatorTest, OneFloatOneResourceArgument) {
  FunctionDef fdef = XTimesY();
  (*fdef.mutable_attr())["_XlaMustCompile"] = BoolAttr(true);
  Init({fdef});
  XlaKernelCreator xla_kernel_creator;
  auto callsite =

  mlir::OpBuilder builder_;
};

TEST_F(XlaLegalizeTargetsTest, CreatesConversionTargets) {
  auto const_int = builder_.create<mlir::arith::ConstantIntOp>(
      builder_.getUnknownLoc(), /*value=*/10, builder_.getI32Type());

  ConversionTarget target =
      GetDefaultLegalConversionTargets(context_, /*legalize_chlo=*/false);
  EXPECT_TRUE(target.isLegal(const_int));
}

TEST_F(XlaLegalizeTargetsTest, AllowsCHLODialect) {