// registering traced functions.
// Operations creation within a context can only be executed in that context
// (for now at least).
// Implementations of the context may contain some state e.g. an execution
// environment, a traced representation etc.
class AbstractContext {
 protected:
  enum AbstractContextKind { kGraph, kMlir, kEager, kTfrt, kTape, kOpHandler };

                                 const tensorflow::string& variable_name);

TFE_Context* CreateContext(const std::string& serialized_server_def,
                           bool isolate_session_state,
                           int64_t init_timeout_in_ms);

tensorflow::ServerDef ReplaceTaskInServerDef(
    const tensorflow::ServerDef& server_def, int task_index);

      new GradientTape<Gradient, BackwardFunction, TapeTensor>(false));
  AccumulatorCallState& call_state = call_state_.top();
  call_state.backward_tape = tape.get();
  auto pop_backward_tape =
      gtl::MakeCleanup([&call_state] { call_state.backward_tape = nullptr; });
  std::vector<Gradient*> forwardprop_aids;
  std::vector<int64_t> sources;
  std::unordered_set<int64_t> sources_set;

  // Set up distributed execution environment on local and remote tasks.
  // When `reset_context` is true, initialize new cluster context state based
  // on cluster configurations provided in `server_def`; otherwise, update
  // existing context state with the provided `server_def`. Contexts created
  // on remote tasks will be considered stale and garbage collected after
  // `keep_alive_secs` of inactivity.

                                                TF_Status* status);

// This function creates a new TF_Session (which is created on success) using
// `session_options`, and then initializes state (restoring tensors and other
// assets) using `run_options`.
//
// Any NULL and non-NULL value combinations for (`run_options, `meta_graph_def`)
// are valid.
//

// context. The provided `ctx` is consumed by this API call and deleted.
// The returned TF_AbstractFunction must be deleted by the client,
// TODO(aminim): clarify the contract on the state of the context after this
// call.
TF_AbstractFunction* TF_FinalizeFunction(TF_ExecutionContext* ctx,
                                         TF_OutputList*, TF_Status*);

//    }

#define GO_MAJOR 0
#define GO_MINOR 0
#define GO_PATCH 1

#ifdef __cplusplus
extern "C" {
#endif

// TF_TriState is the C API typedef for tri-state.
typedef enum TF_TriState {
  TF_TriState_Default = 0,
  TF_TriState_Off,
  TF_TriState_On,
} TF_TriState;

// TF_GrapplerItem represents a combination of a graph, one of more fetch nodes,

// When an error happens, any pending operations are discarded, and newly issued
// ops return an error. This call clears the error state and re-enables
// execution of newly issued ops.
//
// Note that outputs of discarded ops remain in a corrupt state and should not
// be used for future calls.
// TODO(agarwal): mark the affected handles and raise errors if they are used.

  typedef std::pair<std::string, size_t> Key;

  /// \brief The state of a block.
  ///
  /// A block begins in the CREATED stage. The first thread will attempt to read
  /// the block from the filesystem, transitioning the state of the block to
  /// FETCHING. After completing, if the read was successful the state should
  /// be FINISHED. Otherwise the state should be ERROR. A subsequent read can

 public:
  using GradientTape<AbstractTensorHandle, GradientFunction,
                     TapeTensor>::GradientTape;
  // Returns whether the tape is persistent, i.e., whether the tape will hold
  // onto its internal state after a call to `ComputeGradient`.
  using GradientTape<AbstractTensorHandle, GradientFunction,
                     TapeTensor>::IsPersistent;

  // Adds this tensor to the list of watched tensors.
  //