==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_TAPE_H_
#define TENSORFLOW_C_EAGER_TAPE_H_

// Language-agnostic gradient tape. Does not perform backpropagation, just
// maintains the data structures required to do so.

#include <stack>
#include <unordered_map>
#include <unordered_set>
#include <vector>

#include "tensorflow/core/config/flag_defs.h"

TF_CAPI_EXPORT extern void TF_GetOutputPropertiesList(
    TF_GraphProperties* graph_properties, const char* name,
    TF_Buffer** properties, int num_values, TF_Status* status);

// Helper to maintain a map between function names in a given
// FunctionDefLibrary and function definitions.
// Typical use case, is to look up an OpDef by type name.
typedef struct TF_FunctionLibraryDefinition TF_FunctionLibraryDefinition;

TF_CAPI_EXPORT extern void TFE_ContextOptionsSetTfrt(TFE_ContextOptions*,
                                                     bool use_tfrt);

// Returns the context_id from the EagerContext which is used by the
// EagerService to maintain consistency between client and worker. The
// context_id is initialized with a dummy value and is later set when the worker
// is initialized (either locally or remotely). The context_id can change during

//
// `GetID` returns a unique id for the wrapped tensor which is used to maintain
// a map (`tensorflow::eager::TensorTape`) from the wrapped tensor to the id of
// the op that produced it (or -1 if this tensor was watched using
// `GradientTape::Watch`.) The op_id is simply a unique index assigned to each
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,

  // 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.
  virtual Status AsyncWait() = 0;

///
/// All pointers defined in this structure point to memory allocated by the DSO
/// using an allocator provided by core TensorFlow when calling `TF_InitPlugin`.
///
/// IMPORTANT: To maintain binary compatibility, the layout of this structure
/// must not change! In the unlikely case that a new type of file needs to be
/// supported, add the new ops and metadata at the end of the structure.