"tensorflow/compiler/mlir/tf2xla/internal/testdata/");
}

class LoggingHooksTest : public ::testing::Test {
 public:
  LoggingHooksTest() {
    mlir::RegisterCommonToolingDialects(registry_);
    context_.appendDialectRegistry(registry_);
    context_.loadAllAvailableDialects();
    env_ = Env::Default();

    test_group_name_ = "TestGroup";
    test_dir_ = testing::TmpDir();

  explicit MlirV1CompatGraphOptimizationPass(
      const MlirV1CompatOptimizationPassRegistry* registry =
          &MlirV1CompatOptimizationPassRegistry::Global())
      : registry_(registry) {}

  Status Run(const GraphOptimizationPassOptions& options) override;

 private:
  const MlirV1CompatOptimizationPassRegistry* registry_;
};

// -------------------------------------------------------------------------- //

}

class TpuMetadataUtilsTest : public ::testing::Test {
 public:
  TpuMetadataUtilsTest() {
    mlir::RegisterCommonToolingDialects(registry_);
    context_.appendDialectRegistry(registry_);
    context_.loadAllAvailableDialects();
  }

  absl::StatusOr<std::vector<mlir::tf_device::ClusterFuncOp>> GetClusterFuncOps(
      absl::string_view mlir_module_filename) {

  return grad_op_registry;
}

bool GradOpRegistry::Register(const string& op, GradFunc func) {
  CHECK(registry_.insert({op, func}).second) << "Existing gradient for " << op;
  return true;
}

Status GradOpRegistry::Lookup(const string& op, GradFunc* func) const {
  auto iter = registry_.find(op);
  if (iter == registry_.end()) {
    const string error_msg =
        "No gradient defined for op: " + op +
        ". Please see "

  }

  AbstractContextPtr immediate_execution_ctx_;
  GradientRegistry registry_;
  Status status_;

 public:
  bool UseMlir() const { return strcmp(std::get<0>(GetParam()), "mlir") == 0; }
  bool UseFunction() const { return std::get<2>(GetParam()); }
};

TEST_P(CppGradients, TestReluGrad) {
  status_ = registry_.Register("Relu", ReluRegisterer);
  ASSERT_EQ(errors::OK, status_.code()) << status_.message();

}

class SessionClusterTensorflowDialectTest : public ::testing::Test {
 public:
  SessionClusterTensorflowDialectTest() {
    mlir::RegisterCommonToolingDialects(registry_);
    context_.appendDialectRegistry(registry_);
    context_.loadAllAvailableDialects();
  }

  absl::Status CreateMlirModule(std::string mlir_module_filename) {
    std::string mlir_module_path = TestDataPath() + mlir_module_filename;

}

class TensorflowDialectToExecutorTest : public ::testing::Test {
 public:
  TensorflowDialectToExecutorTest() {
    mlir::RegisterCommonToolingDialects(registry_);
    context_.appendDialectRegistry(registry_);
    context_.loadAllAvailableDialects();
  }

  absl::Status CreateMlirModule(std::string mlir_module_filename) {
    std::string mlir_module_path = TestDataPath() + mlir_module_filename;

  }
  return count;
}

class TensorflowDialectToExecutorTest : public ::testing::Test {
 public:
  TensorflowDialectToExecutorTest() {
    mlir::RegisterCommonToolingDialects(registry_);
    context_.appendDialectRegistry(registry_);
    context_.loadAllAvailableDialects();
  }

  absl::Status CreateMlirModule(std::string mlir_module_filename) {
    std::string mlir_module_path = TestDataPath() + mlir_module_filename;

class FunctionClusterTensorflowDialectTest : public ::testing::Test {
 public:
  FunctionClusterTensorflowDialectTest() {
    mlir::RegisterCommonToolingDialects(registry_);
    context_.appendDialectRegistry(registry_);
    context_.loadAllAvailableDialects();
  }

  absl::Status CreateMlirModule(std::string mlir_module_filename) {
    std::string mlir_module_path = TestDataPath() + mlir_module_filename;

                         << ", FallbackEnabled: " << num_passes_fallback_enabled
                         << ", Total: " << registry_->passes().size();
  }

  GraphDebugInfo debug_info;
  mlir::DialectRegistry registry;
  RegisterDialects(registry);
  mlir::MLIRContext context(registry);
  GraphImportConfig import_config;
  import_config.graph_as_function = true;
  import_config.control_outputs = *control_ret_node_names;