return tsl::io::JoinPath(
        getenv("TEST_UNDECLARED_OUTPUTS_DIR"),
        absl::StrCat(test_info->test_suite_name(), ".", test_info->name()));
  }
};

TEST_F(InitPassManagerTest, CrashReproducer) {
  converter::DebugOptions debug_options;
  *debug_options.mutable_ir_dump_dir() = path_;

  mlir::PassManager pm(&context_);
  InitPassManager(pm, debug_options);

	in2 In2
	in3 In3
	out Out
}

func test1[In, Out any](t *testing.T, tests []testCase1[In, Out], name string, f func(In) Out) {
	t.Helper()
	for _, tt := range tests {
		if out := f(tt.in); !reflect.DeepEqual(out, tt.out) {
			t.Errorf("%s(%v) = %v, want %v", name, tt.in, out, tt.out)
		}
	}
}

func test2[In1, In2, Out any](t *testing.T, tests []testCase2[In1, In2, Out], name string, f func(In1, In2) Out) {

    }
    return absl::OkStatus();
  }

  DialectRegistry registry_;
  MLIRContext context_;
  OwningOpRef<mlir::ModuleOp> mlir_module_;
};

TEST_F(TensorflowDialectToExecutorTest, ConvertsToExecutor) {
  CellReader<int64_t> compilation_status(kExportStreamzName);

  TF_ASSERT_OK(CreateMlirModule("empty_func.mlir"));

						Expression: "this.expression == unit.test",
						Message:    "test2",
					},
				},
			},
			policyDecision: []PolicyDecision{
				{
					Action:  ActionDeny,
					Reason:  metav1.StatusReasonForbidden,
					Message: "test1",
				},
				{
					Action:  ActionDeny,
					Reason:  metav1.StatusReasonForbidden,
					Message: "test2",
				},
			},
			failPolicy: &fail,
		},

using mlir::UnknownLoc;
using mlir::chlo::ChloDialect;
using mlir::TF::TensorFlowDialect;
using tensorflow::tf2xla::internal::IsInBridgeAcceptableDialects;

class SharedUtilsTest : public ::testing::Test {};

TEST_F(SharedUtilsTest, IsInFunctionalDialectPasses) {
  MLIRContext context;
  context.loadDialect<TensorFlowDialect>();
  OpBuilder opBuilder(&context);
  OperationState state(UnknownLoc::get(opBuilder.getContext()),

  }
  return nullptr;
}

TEST_F(QuantizeWeightsTest, QuantizationSucceeds) {
  LoadBasicModel();
  flatbuffers::FlatBufferBuilder builder;
  auto status = QuantizeWeights(&builder, model_, 0);
  EXPECT_EQ(status, kTfLiteOk);

  const uint8_t* buffer = builder.GetBufferPointer();
  const Model* output_model = GetModel(buffer);
  ASSERT_TRUE(output_model);
}

TEST_F(QuantizeWeightsTest, QuantizationFails) {

            assert it.group == "task group ${it.name-'test'}"
        }
    }

    def "provide getGroup on Task using GradleProject shouldn't fail if group is null"() {
        file("build.gradle") << '''
task test1()
task test2()
'''

        when:
        def gradleProject = withConnection { ProjectConnection connection ->
            connection.getModel(GradleProject)
        }

  auto value = static_cast<T*>(TF_TensorData(result_t));
  EXPECT_EQ(*value, expected);
  TF_DeleteTensor(result_t);
}

// TODO(srbs): Add tests for captures.
// TODO(srbs): Add tests for polymorphism (different shapes and dtypes).
TEST_P(FunctionTest, Square) {
  // Construct a scalar.
  impl::TaggedValueTensor x = CreateScalarTensor<float, TF_FLOAT>(2.0f);
  FunctionDef fdef = SquareFunc();

#include "xla/shape.h"
#include "xla/shape_util.h"
#include "xla/tests/literal_test_util.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tsl/platform/errors.h"
#include "tsl/platform/statusor.h"

namespace mlir::quant::stablehlo {
namespace {

using ::testing::Test;

class ConvertTfQuantToMhloIntTest : public Test {
 protected:
  void SetUp() override {

                                                    GetShapeDeterminationFns());
}

class XlaCompilerOptionsTest : public ::testing::Test {
 protected:
  void SetUp() override {
    tensorflow::GetXlaDeviceFlags()->tf_xla_enable_xla_devices = true;
  }

  DeviceSetup device_setup_;
};

TEST_F(XlaCompilerOptionsTest, PjRtOptionsXlaDevice) {
  device_setup_.AddDevicesAndSetUp({DEVICE_XLA_GPU});