EXPECT_LT(max_error, 1e-3);
  }

  Scope scope_;
};

TEST_F(LinalgGradTest, Einsum_Transpose) {
  TensorShape x_shape({2, 3});
  Output x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape));
  auto y = Einsum(scope_, {x}, "ij->ji");
  TensorShape y_shape({3, 2});
  RunTest({x}, {x_shape}, {y}, {y_shape});
}

TEST_F(LinalgGradTest, Einsum_TransposeBroadcast) {
  TensorShape x_shape({3, 2, 3});

#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/protobuf/error_codes.pb.h"
#include "tensorflow/core/protobuf/saved_object_graph.pb.h"

namespace tensorflow {
namespace {

class SavedConcreteFunctionLoadingTest : public ::testing::Test {
 public:
  SavedConcreteFunctionLoadingTest()
      : device_mgr_(testing::CreateTestingDeviceMgr()),

import XCTest

class SomeIntegTest: XCTestCase {
    public static var allTests = [
        ("test1", test1),
        ("test2", test2)
    ]
    func test1() {}
    func test2() {}

        reportTask.testResults.from([[test2.binaryResultsDirectory], test3.binaryResultsDirectory])

        then:
        reportTask.testResults.files as List == [test1, test2, test3]*.binaryResultsDirectory*.getAsFile()*.get()
        reportTask.testResults.buildDependencies.getDependencies(reportTask) == [test1, test2, test3] as Set
    }

    def "can attach result dirs"() {

namespace mlir::quant {
namespace {

using ::testing::IsNull;
using ::testing::NotNull;

using FindMainFuncOpTest = ::mlir::quant::QuantizationTestBase;

TEST_F(FindMainFuncOpTest, ReturnsMainFuncOp) {
  constexpr absl::string_view kModuleWithMainFunc = R"mlir(
    module {
      func.func @main() -> () {
        return
      }
    }
  )mlir";

			evaluations: []cel.EvaluationResult{
				{
					EvalResult: celtypes.False,
					ExpressionAccessor: &MatchCondition{
						Name: "test1",
					},
				},
				{
					EvalResult: celtypes.True,
					ExpressionAccessor: &MatchCondition{
						Name: "test2",
					},
				},
			},
			shouldMatch:  false,
			returnedName: "test1",
		},
		{

namespace mlir {
namespace TFDevice {

using ::mlir::MLIRContext;
using ::mlir::ModuleOp;
using ::mlir::OwningOpRef;
using ::mlir::mhlo::test::GetMlirModuleFromString;

class VerifyNoOutsideCompilationMarkersPassTest : public ::testing::Test {
 protected:
  void CreateModule(const char* module_string) {
    TF_ASSERT_OK_AND_ASSIGN(module_,

	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) {

  Env* env_;
  std::string test_dir_;
  std::string test_group_name_;
};

TEST_F(LowerClusterToRuntimeOpsTest, SanityCheck) {
  TF_ASSERT_OK(CreateMlirModule("empty_func.mlir"));

  TF_EXPECT_OK(RunLowerClusterToRuntimeOpsPassPipeline(
      *mlir_module_, DeviceType(DEVICE_TPU_XLA_JIT)));
}

TEST_F(LowerClusterToRuntimeOpsTest, LowersClusterOpsTPU) {
  TF_ASSERT_OK(CreateMlirModule("basic_cluster.mlir"));

  const LogicalResult parse_result =
      parseSourceString(module_op_str, &block, ParserConfig(&ctx));
  EXPECT_TRUE(succeeded(parse_result));

  return cast<ModuleOp>(block.front());
}

TEST_F(TfSavedModelTest,
       GetInitializerFunctionReturnsNullWhenNoSessionInitializerOp) {
  constexpr StringRef kModuleOpStr =
      R"mlir(module attributes {tf_saved_model.semantics} {})mlir";

  Block block;