VariableAddFunctionSignature(), &def));
  return def.SerializeAsString();
}

// A graph optimization pass that would fail when triggered for more than once.
class GraphErrorInjectionPass : public tensorflow::GraphOptimizationPass {
 public:
  static bool enabled_;
  GraphErrorInjectionPass() {}

  tensorflow::Status Run(

             BaseType(dtype) != DT_VARIANT) {
    return errors::InvalidArgument(
        "Expected numeric or variant tensor, got dtype ", dtype);
  }
  return tensorflow::ops::Conj(ctx, input, output, name);
}

class AddGradientFunction : public GradientFunction {
 public:
  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,

namespace tracing {
namespace graph {

class GraphContext;
class GraphOperation;
class GraphTensor;

auto& kUnknownDim = shape_inference::InferenceContext::kUnknownDim;
auto& kUnknownRank = shape_inference::InferenceContext::kUnknownRank;

// GraphTensor wraps a `TF_Output`, i.e. a pointer to TF_Operation and the index
// into the list of outputs for the operation.
class GraphTensor : public TracingTensorHandle {
 public:

  EXPECT_EQ(assign, 1);
  int id = TF_OpIsStateful("Identity", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  EXPECT_EQ(id, 0);
}

class ShapeInferenceTest : public ::testing::Test {
 protected:
  ShapeInferenceTest()
      : status_(TF_NewStatus()), tfe_context_options_(TFE_NewContextOptions()) {
    tfe_context_ = TFE_NewContext(tfe_context_options_, status_);

#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace {
class UnifiedAPI
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());

// result of `gradient_checker` and `[*]_grad`. The tests here test the
// functionality of `gradient_checker` by comparing the result with expected
// manual user-provided gradients.
class GradientCheckerTest
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());

  if (!status->status.ok()) {
    return nullptr;
  }
  return const_cast<void*>(
      static_cast<const void*>(tensor->tensor_data().data()));
}

namespace tensorflow {
namespace {
class CustomDeviceAPI : public tensorflow::CustomDevice {
 public:
  CustomDeviceAPI(TFE_Context* context, TFE_CustomDevice device, void* info,
                  string name)

  if (!metadata) return TF_SetStatusFromGCSStatus(metadata.status(), status);
  stat->generation_number = metadata->generation();
  stat->base.length = metadata->size();
  stat->base.mtime_nsec =
      metadata->time_storage_class_updated().time_since_epoch().count();
  stat->base.is_directory = object.back() == '/';
  TF_VLog(1,
          "Stat of: gs://%s/%s --  length: %u generation: %u; mtime_nsec: %u;",

  typedef std::pair<string, string> Base;

  // Inherit the set of constructors
  using Base::pair;

  string ToString() const { return strings::StrCat(first, "->", second); }
};

class CApiFunctionTest : public ::testing::Test {
 protected:
  CApiFunctionTest()
      : s_(TF_NewStatus()),
        func_graph_(TF_NewGraph()),
        host_graph_(TF_NewGraph()),
        func_(nullptr) {}

#include "tensorflow/core/util/saved_tensor_slice_util.h"
#include "tensorflow/core/util/tensor_bundle/naming.h"
#include "tensorflow/core/util/tensor_bundle/tensor_bundle.h"

namespace tensorflow {
namespace checkpoint {

class TensorSliceReader;

CheckpointReader::CheckpointReader(const string& filename, TF_Status* status)
    : reader_(nullptr),
      v2_reader_(nullptr),
      var_to_shape_map_(nullptr),
      var_to_data_type_map_(nullptr) {