//
  // Arguments provide enough information to reconstruct the original `TFE_Op`,
  // or construct a transformed version, by inspecting the passed `op`.
  //
  // TFE_OpGetDevice(op) records the original placement of the operation. It may
  // be an empty string if no device was explicitly requested, but will
  // otherwise be the name of this custom device. Ops are placed onto a custom

  //
  // This is a no-op if the tensor is already being watched either from an
  // earlier call to `GradientTape::Watch` or being an output of an op with
  // watched inputs.
  void Watch(int64_t tensor_id);

  // Records an operation with inputs `input_tensor_id` and outputs
  // `output_tensors` on the tape and marks all its outputs as watched if at
  // least one input of the op is watched and has trainable dtype.
  //

  absl::StatusOr<core::RefCountPtr<FunctionRecord>> GetFunctionRecord()
      override {
    return func_record_.GetNewRef();
  }

  // For LLVM style RTTI.
  static bool classof(const AbstractFunction* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  core::RefCountPtr<FunctionRecord> func_record_;
};
}  // namespace graph
}  // namespace tracing
}  // namespace tensorflow

    TF_Status* status);

TF_CAPI_EXPORT extern TF_Buffer* TF_CoordinationServiceGetKeyValueWithTimeout(
    const char* key, int64_t key_size, int64_t timeout_seconds,
    TF_CoordinationServiceAgent* agent, TF_Status* status);

TF_CAPI_EXPORT extern TF_Buffer* TF_CoordinationServiceTryGetKeyValue(
    const char* key, int64_t key_size, TF_CoordinationServiceAgent* agent,