limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_DISTRIBUTED_MANAGER_H_
#define TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_DISTRIBUTED_MANAGER_H_

#include <cstdint>
#include <string>

#include "tensorflow/core/platform/status.h"

namespace tsl {
class CoordinationServiceAgent;
}

namespace tensorflow {

// Associates the given `cancellation_manager` with `op`, so that invoking
// `TFE_CancellationManagerStartCancel(cancellation_manager)` will cancel the
// execution of `op`.
typedef struct TFE_CancellationManager TFE_CancellationManager;
TF_CAPI_EXPORT extern void TFE_OpSetCancellationManager(
    TFE_Op* op, TFE_CancellationManager* cancellation_manager,
    TF_Status* status);

  virtual bool UsesTFRT() = 0;

  // List attributes of available devices
  virtual void ListDevices(std::vector<DeviceAttributes>* devices) = 0;

  // Add `devices` into context's device manager. Context's device manager
  // will take ownership and maintain devices' lifetime.
  virtual Status AddDevices(std::vector<std::unique_ptr<Device>> devices) = 0;

  // Block until all pending nodes are finished.

    // instead allow ForwardAccumulator some control over the current tape set
    // (so it can deactivate itself and activate its GradientTape). Currently
    // that is managed by the language binding and would require relatively
    // messy callbacks.
    call_state_.top().backward_tape->RecordOperation(
        op_type, output_tensors, input_tensor_id, input_dtypes,