// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

class Callback {
public:
	virtual ~Callback() { }
	virtual std::string run() { return "Callback::run"; }
};

class Caller {
private:
	Callback *callback_;
public:
	Caller(): callback_(0) { }
	~Caller() { delCallback(); }
	void delCallback() { delete callback_; callback_ = 0; }

  bool async = false;
  TFE_ContextDevicePlacementPolicy device_placement_policy{
      TFE_DEVICE_PLACEMENT_SILENT};
  // If true, use TFRT backend
  bool use_tfrt = false;
  // Whether to run elementary eager ops wrapped in a call op.
  bool run_eager_op_as_function = false;
  // Whether to rewrite jit_compile functions.
  bool jit_compile_rewrite = false;
};

    f_ = src.release();
    return *this;
  }

  ~Cleanup() {
    if (!released_) f_();
  }

  // Releases the cleanup function instead of running it.
  // Hint: use c.release()() to run early.
  F release() {
    released_ = true;
    return std::move(f_);
  }

  bool is_released() const { return released_; }

 private:
  static_assert(!std::is_reference<F>::value, "F must not be a reference");

  void SetOutputs(std::initializer_list<TF_Operation*> outputs);
  void SetOutputs(const std::vector<TF_Output>& outputs);
  void SetTargets(std::initializer_list<TF_Operation*> targets);

  void Run(TF_Status* s);

  void CloseAndDelete(TF_Status* s);

  TF_Tensor* output_tensor(int i) { return output_values_[i]; }

  TF_Session* mutable_session() { return session_; }

 private:

limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_
#define TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_

// Run a function containing a MatMul op and check its output.
// If heavy_load_on_streaming_rpc is true, send some rpc requests before the one
// which creates a remote input, to simulate a scenario that the remote input

      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each
  // value records whether the graph has been mutated since the corresponding
  // session has been run (this is detected in RecordMutation function). If the
  // string is empty, no mutation has occurred. Otherwise the string is a
  // description of the mutation suitable for returning to the user.
  //