// files. The interface lists the common functionality that must be provided by
// any concrete implementation. However, in cases where the true concrete class
// is needed a static_cast can be applied.
class ImmediateExecutionTensorHandle : public AbstractTensorHandle {
 public:
  // Returns number of dimensions.
  virtual Status NumDims(int* num_dims) const = 0;

  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
  ASSERT_EQ(TF_TensorType(actual_value.get()),
            static_cast<TF_DataType>(DataTypeToEnum<value_type>().value));
  EXPECT_EQ(expected_value,
            *static_cast<value_type*>(TF_TensorData(actual_value.get())));
}

template <std::size_t num_devices>
void RegisterParallelDevice(

    TF_SetStatus(
        status, TF_INVALID_ARGUMENT,
        "Number of values did not match number of underlying devices.");
    return nullptr;
  }
  TF_DataType datatype_enum(
      static_cast<TF_DataType>(DataTypeToEnum<DataType>().value));
  for (int device_index = 0; device_index < num_underlying_devices();
       ++device_index) {
    auto device_value = absl::make_unique<DataType>();

  // We can not pass a lambda with capture as a function pointer to
  // `TF_StartThread`, so we have to wrap `Prune` inside a static function.
  static void PruneThread(void* param) {
    auto ram_file_block_cache = static_cast<RamFileBlockCache*>(param);
    ram_file_block_cache->Prune();
  }

 private:
  /// The size of the blocks stored in the LRU cache, as well as the size of the
  /// reads from the underlying filesystem.