device_name, "\")");
}

absl::Status ImmediateExecutionTensorHandle::SummarizeValue(
    std::string& summary) const {
  absl::Status status;
  AbstractTensorPtr resolved(
      // TODO(allenl): Resolve should be const, and the caches that get updated
      // marked mutable.
      const_cast<ImmediateExecutionTensorHandle*>(this)->Resolve(&status));
  if (!status.ok()) {
    return status;
  }

  // Create a handle to wrap and manage a Tensor
  virtual ImmediateExecutionTensorHandle* CreateLocalHandle(
      AbstractTensorInterface* t) = 0;
  // Copy the handle to another device.
  virtual ImmediateExecutionTensorHandle* CopyTensorHandleToDevice(
      ImmediateExecutionTensorHandle* handle, const char* device_name,
      absl::Status* status) = 0;

  }

 protected:
  explicit ImmediateExecutionTensorHandle(AbstractTensorHandleKind kind)
      : AbstractTensorHandle(kind) {}
  ~ImmediateExecutionTensorHandle() override {}
};

namespace internal {
struct ImmediateExecutionTensorHandleDeleter {
  void operator()(ImmediateExecutionTensorHandle* p) const {
    if (p != nullptr) {
      p->Unref();
    }
  }
};

 public:
  virtual void Clear() = 0;

  // Returns the inputs of this op.
  virtual absl::Span<ImmediateExecutionTensorHandle* const> GetInputs()
      const = 0;
  virtual absl::Status SetInput(size_t index,
                                ImmediateExecutionTensorHandle* input) = 0;

  virtual ImmediateExecutionContext* GetContext() const = 0;

  // Following two methods are used to support custom device.

using tensorflow::AbstractContext;
using tensorflow::AbstractTensorHandle;
using tensorflow::dyn_cast;
using tensorflow::ImmediateExecutionContext;
using tensorflow::ImmediateExecutionTensorHandle;
using tensorflow::string;
using tensorflow::unwrap;
using tensorflow::wrap;
using tensorflow::strings::StrCat;

TF_ExecutionContext* TF_NewEagerExecutionContext(TFE_ContextOptions* options,

  ~CustomDeviceAPI() override { device_.delete_device(info_); }

  const string& name() override { return name_; }

  absl::Status CopyTensorToDevice(
      ImmediateExecutionTensorHandle* handle,
      ImmediateExecutionTensorHandle** result) override {
    handle->Ref();
    TF_Status status;
    TFE_TensorHandle* result_handle = device_.copy_tensor_to_device(

          tensorflow::down_cast<tensorflow::CustomDeviceTensorHandle*>(
              unwrapped_handle);
      tensorflow::ImmediateExecutionTensorHandle* result;
      status->status = custom_device_handle->device()->Pack(
          absl::Span<tensorflow::ImmediateExecutionTensorHandle*>(
              tensorflow::unwrap(handles), *num_handles),
          &result);
      return tensorflow::wrap(result);
    }

    // devices limiting themselves to a C API (for ABI compatibility) would need
    // to implement summarization for component tensors themselves.
    ImmediateExecutionTensorHandle* component =
        tensorflow::unwrap(tensors_[component_index].get());
    std::string component_summary;
    TF_RETURN_IF_ERROR(component->SummarizeValue(component_summary));

  TensorHandlePtr device_value = CreatePerDeviceValues(
      context.get(), components, device_name, status.get());
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
  ImmediateExecutionTensorHandle* unwrapped_handle =
      tensorflow::unwrap(device_value.get());
  std::string summarized;
  TF_ASSERT_OK(unwrapped_handle->SummarizeValue(summarized));
  EXPECT_THAT(summarized, HasSubstr("\"CPU:0\": 3"));