ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TFE_DeleteExecutor(executor);
  TFE_DeleteContext(ctx);
}

void ExecuteAdd(bool async, bool forward_input, bool tfrt) {
#ifdef PLATFORM_WINDOWS
  // On windows, we flakily get a failure due to pointer instability.
  // Disable the 4 tests using this helper until we fix the issue.
  return;
#else

#include <memory>
#include <sstream>
#include <utility>

#include "absl/synchronization/mutex.h"
#include "tensorflow/c/experimental/filesystem/plugins/gcs/cleanup.h"

namespace tf_gcs_filesystem {

bool RamFileBlockCache::BlockNotStale(const std::shared_ptr<Block>& block) {
  absl::MutexLock l(&block->mu);
  if (block->state != FetchState::FINISHED) {
    return true;  // No need to check for staleness.
  }

#include "tensorflow/core/protobuf/cluster.pb.h"
#include "tensorflow/core/protobuf/config.pb.h"

using tensorflow::string;

namespace tensorflow {
namespace {

static bool HasSubstr(absl::string_view base, absl::string_view substr) {
  bool ok = absl::StrContains(base, substr);
  EXPECT_TRUE(ok) << base << ", expected substring " << substr;
  return ok;
}

TEST(CAPI, MonitoringCounter0) {

              const std::vector<TF_Operation*>& inputs,
              const std::vector<TF_Operation*>& outputs,
              const std::vector<string>& output_names,
              bool expect_failure = false) {
    DefineT(num_opers, opers, ToOutput(inputs), ToOutput(outputs), output_names,
            expect_failure);
  }

  // Caller must delete[] the returned value

#endif  // !defined(TENSORFLOW_NO_SHARED_OBJECTS)
#endif  // !defined(PLATFORM_WINDOWS)
}

void DefineFunction(const char* name, TF_Function** func,
                    const char* description = nullptr,
                    bool append_hash = false) {
  std::unique_ptr<TF_Graph, decltype(&TF_DeleteGraph)> func_graph(
      TF_NewGraph(), TF_DeleteGraph);
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> s(TF_NewStatus(),

        new TensorSliceReader::VarToShapeMap(reader_->GetVariableToShapeMap()));
    var_to_data_type_map_.reset(new TensorSliceReader::VarToDataTypeMap(
        reader_->GetVariableToDataTypeMap()));
  }
}

bool CheckpointReader::HasTensor(const string& name) const {
  if (reader_ != nullptr) {
    return reader_->HasTensor(name, nullptr, nullptr);
  }
  return v2_reader_->Contains(name);
}

  ops_->path_exists(filesystem_.get(), translated_name.c_str(),
                    plugin_status.get());
  return StatusFromTF_Status(plugin_status.get());
}

bool ModularFileSystem::FilesExist(const std::vector<std::string>& files,
                                   TransactionToken* token,
                                   std::vector<Status>* status) {
  if (ops_->paths_exist == nullptr)

static bool GetURIScheme(const std::string& scheme) {
  tensorflow::SchemeVector()->push_back(scheme);
  return true;
}

// This function is used for cloud filesystem
// `S3` and `GCS` require the `root_dir_` to have bucket name
// `HDFS` requires the `root_dir` to have namenode
// `root_dir_ = scheme + "://" cloud_path_ + root_dir_`
static bool SetCloudPath(const std::string& cloud_path_) {

    }
  }
}

TEST(RamFileBlockCacheTest, OutOfRange) {
  // Tests reads of a 24-byte file with block size 16.
  const size_t block_size = 16;
  const size_t file_size = 24;
  bool first_block = false;
  bool second_block = false;
  auto fetcher = [block_size, file_size, &first_block, &second_block](
                     const string& filename, size_t offset, size_t n,

// - a string representing the tracing implementation: "mlir" or "graphdef".
// - a boolean that when true enables TFRT as the execution engine.
class UnifiedCAPI
    : public ::testing::TestWithParam<std::tuple<const char*, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    Status s = StatusFromTF_Status(status.get());