struct TFE_MonitoringCounterReader {
  explicit TFE_MonitoringCounterReader(const char* name) {
    counter = std::make_unique<
        ::tensorflow::monitoring::testing::CellReader<int64_t>>(name);
  }
  template <typename... LabelType>
  int64_t Read(const LabelType&... labels);
  std::unique_ptr<::tensorflow::monitoring::testing::CellReader<int64_t>>
      counter;
};

  void operator()(ImmediateExecutionOperation* p) const {
    if (p != nullptr) {
      p->Release();
    }
  }
};
}  // namespace internal

using ImmediateOpPtr =
    std::unique_ptr<ImmediateExecutionOperation,
                    internal::ImmediateExecutionOperationDeleter>;

}  // namespace tensorflow

  return TensorHandlePtr(result_handle);
}

template <typename value_type>
void ExpectScalarEq(TFE_TensorHandle* handle, value_type expected_value) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  std::unique_ptr<TF_Tensor, decltype(&TF_DeleteTensor)> actual_value(
      TFE_TensorHandleResolve(handle, status.get()), TF_DeleteTensor);

struct AbstractContextDeleter {
  void operator()(AbstractContext* p) const {
    if (p != nullptr) {
      p->Release();
    }
  }
};
}  // namespace internal

using AbstractContextPtr =
    std::unique_ptr<AbstractContext, internal::AbstractContextDeleter>;

}  // namespace tensorflow

  std::shared_ptr<RamFileBlockCache> file_block_cache
      ABSL_GUARDED_BY(block_cache_lock);
  uint64_t block_size;  // Reads smaller than block_size will trigger a read
                        // of block_size.
  std::unique_ptr<ExpiringLRUCache<GcsFileStat>> stat_cache;
  GCSFile(google::cloud::storage::Client&& gcs_client);
  // This constructor is used for testing purpose only.
  GCSFile(google::cloud::storage::Client&& gcs_client, bool compose,

  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};

struct TFE_MonitoringBuckets {
  explicit TFE_MonitoringBuckets(
      std::function<std::unique_ptr<tensorflow::monitoring::Buckets>(void)>
          fn) {
    create_buckets = fn;
  }

  std::function<std::unique_ptr<tensorflow::monitoring::Buckets>(void)>
      create_buckets;
};

struct TFE_MonitoringSamplerCell {
  tensorflow::monitoring::SamplerCell cell;

  Cleanup(Cleanup<G>&& src)  // NOLINT
      : released_(src.is_released()), f_(src.release()) {}

  // Assignment to a Cleanup object behaves like destroying it
  // and making a new one in its place, analogous to unique_ptr
  // semantics.
  Cleanup& operator=(Cleanup&& src) {  // NOLINT
    if (!released_) f_();
    released_ = src.released_;
    f_ = src.release();
    return *this;
  }

  ~Cleanup() {

struct AbstractOperationDeleter {
  void operator()(AbstractOperation* p) const {
    if (p != nullptr) {
      p->Release();
    }
  }
};
}  // namespace internal

using AbstractOperationPtr =
    std::unique_ptr<AbstractOperation, internal::AbstractOperationDeleter>;

}  // namespace tensorflow

class ModularFileSystem final : public FileSystem {
 public:
  ModularFileSystem(
      std::unique_ptr<TF_Filesystem> filesystem,
      std::unique_ptr<const TF_FilesystemOps> filesystem_ops,
      std::unique_ptr<const TF_RandomAccessFileOps> random_access_file_ops,
      std::unique_ptr<const TF_WritableFileOps> writable_file_ops,
      std::unique_ptr<const TF_ReadOnlyMemoryRegionOps>
          read_only_memory_region_ops,

  Status Lookup(const ForwardOperation& op,
                std::unique_ptr<GradientFunction>* gradient_function) const;

 private:
  absl::flat_hash_map<string, GradientFunctionFactory> registry_;
};

// TODO(srbs): Figure out if we can avoid declaring this in the public header.
// Wrapper for a tensor output of an operation executing under a tape.
//
// `GetID` returns a unique id for the wrapped tensor which is used to maintain