absl::flat_hash_set<int> null_indices;
    {
      AbstractContextPtr func_ctx(BuildFunction(fn_name));
      std::vector<AbstractTensorHandle*> func_inputs;
      func_inputs.reserve(inputs.size());
      TF_RETURN_IF_ERROR(
          CreateParamsForInputs(func_ctx.get(), inputs, &func_inputs));
      std::vector<AbstractTensorHandle*> model_outputs;
      model_outputs.resize(outputs.size());

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/platform/types.h"

struct TF_StringStream {
  std::vector<::tensorflow::string>* list;
  size_t position;
};

void TF_CreateDir(const char* dirname, TF_Status* status) {
  TF_SetStatus(status, TF_OK, "");
  ::tensorflow::Set_TF_Status_from_Status(

class UnifiedAPI
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    Status s = StatusFromTF_Status(status.get());
    CHECK_EQ(errors::OK, s.code()) << s.message();
  }

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

class Callback {
public:
	virtual ~Callback() { }
	virtual std::string run() { return "Callback::run"; }
};

class Caller {
private:
	Callback *callback_;
public:
	Caller(): callback_(0) { }
	~Caller() { delCallback(); }
	void delCallback() { delete callback_; callback_ = 0; }
	void setCallback(Callback *cb) { delCallback(); callback_ = cb; }
	std::string call();

  return SetAttrShape(attr_name, shape.dim_sizes().data(), shape.dims());
}

inline Status AbstractOperation::SetAttrStringList(
    const char* attr_name, absl::Span<string const> values) {
  std::vector<const char*> raw_strs;
  std::vector<size_t> lengths;
  raw_strs.reserve(values.size());
  lengths.reserve(values.size());
  for (const auto& s : values) {
    raw_strs.emplace_back(s.data());
    lengths.emplace_back(s.size());

    AbstractTensorHandlePtr B(conj_output);

    // Calc Grad
    AbstractTensorHandle* matmul_A_output;
    AbstractTensorHandle* matmul_B_output;
    std::string name_grad_A = "MatMul_Grad_A";
    std::string name_grad_B = "MatMul_Grad_B";
    if (!t_a && !t_b) {
      TF_RETURN_IF_ERROR(MatMul(ctx, upstream_grad, B.get(), &matmul_A_output,
                                /*transpose_a = */ false,

  }
  // For LLVM style RTTI.
  static bool classof(const AbstractContext* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  std::unique_ptr<TF_Graph, decltype(&TF_DeleteGraph)> graph_;
  std::vector<TF_Output> inputs_;
  string name_;
};

static TracingContext* GraphTracingFactory(const char* name, TF_Status* s) {
  return new GraphContext(name);
}

  TFE_OpSetAttrString(op, "final_op", "Id", 2);
  std::vector<int64_t> subdiv_offsets;
  TFE_OpSetAttrIntList(op, "subdiv_offsets", subdiv_offsets.data(),
                       subdiv_offsets.size());

  return op;
}

TFE_Op* SendOp(TFE_Context* ctx, TFE_TensorHandle* in,
               const std::string& op_name, const std::string& send_device,
               const std::string& recv_device,

  return Env::Default()->RegisterFileSystem(
      info->ops[index].scheme,
      std::make_unique<tensorflow::ModularFileSystem>(
          std::move(filesystem), std::move(core_filesystem_ops),
          std::move(core_random_access_file_ops),
          std::move(core_writable_file_ops),
          std::move(core_read_only_memory_region_ops),
          info->plugin_memory_allocate, info->plugin_memory_free));
}

  EXPECT_TF_META("v", list_size, TF_ATTR_INT, -1);
  TF_OperationGetAttrIntList(oper, "v", values, list_size, s_);
  EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  EXPECT_TRUE(std::equal(std::begin(list), std::end(list), std::begin(values)));
}

TEST_F(CApiAttributesTest, Float) {
  auto desc = init("float");
  TF_SetAttrFloat(desc, "v", 2.718);

  auto oper = TF_FinishOperation(desc, s_);