// Registers a custom device for use with eager execution.
//
// Eager operations may be placed on this device, e.g.  `with
// tf.device("CUSTOM"):` from Python if `device_name` for this call is
// "/job:localhost/replica:0/task:0/device:CUSTOM:0".
//
// The custom device defines copy operations for moving TensorHandles on and
// off, and an execution operation for named operations. Often execution will

TF_CAPI_EXPORT extern void TF_DeleteGraph(TF_Graph*);

// Operation being built. The underlying graph must outlive this.
typedef struct TF_OperationDescription TF_OperationDescription;

// Operation that has been added to the graph. Valid until the graph is
// deleted -- in particular adding a new operation to the graph does not
// invalidate old TF_Operation* pointers.
typedef struct TF_Operation TF_Operation;

};

// Map from tensor_id to internally-defined operation-id of the operation which
// produced this tensor. A value of -1 means that the tensor was directly
// watched and not the result of any operation in the tape.
using TensorTape = std::unordered_map<int64_t, int64_t>;

// Map from operation-id to tape entry.
template <typename BackwardFunction, typename TapeTensor>
using OpTape =

enum ContextDevicePlacementPolicy {
  // Running operations with input tensors on the wrong device will fail.
  DEVICE_PLACEMENT_EXPLICIT = 0,
  // Copy the tensor to the right device but log a warning.
  DEVICE_PLACEMENT_WARN = 1,
  // Silently copy the tensor, which has a performance cost since the operation
  // will be blocked till the copy completes. This is the default policy.