TF_Status* status);

void RecordMutation(TF_Graph* graph, const TF_Operation& op,
                    const char* mutation_type)
    TF_EXCLUSIVE_LOCKS_REQUIRED(graph->mu);

bool ExtendSessionGraphHelper(TF_Session* session, TF_Status* status)
    TF_LOCKS_EXCLUDED(session->graph->mu, session->mu);

std::string getTF_OutputDebugString(TF_Output node);

      the original version of the Work and any modifications or additions
      to that Work or Derivative Works thereof, that is intentionally
      submitted to Licensor for inclusion in the Work by the copyright owner
      or by an individual or Legal Entity authorized to submit on behalf of
      the copyright owner. For the purposes of this definition, "submitted"

extern "C" {

TF_OperationDescription* TF_NewOperationLocked(TF_Graph* graph,
                                               const char* op_type,
                                               const char* oper_name)
    TF_EXCLUSIVE_LOCKS_REQUIRED(graph->mu) {
  return new TF_OperationDescription(graph, op_type, oper_name);
}

TF_OperationDescription* TF_NewOperation(TF_Graph* graph, const char* op_type,

    *   Select and scatter in reference util and evaluator now use
        lexicographical order to break ties.
*   TensorFlow Debugger (tfdbg) CLI:
    *   During tensor-filter operations, allow exclusion of nodes by regular
        expressions.
    *   Fix spurious background colors in some text terminals.
*   `tf.contrib`:
    *   Add meta-distribution BatchReshape which reshapes batch dimensions.

  # ROCm / CUDA are mutually exclusive.
  # At most 1 GPU platform can be configured.
  gpu_platform_count = 0
  if environ_cp.get('TF_NEED_ROCM') == '1':
    gpu_platform_count += 1
  if environ_cp.get('TF_NEED_CUDA') == '1':
    gpu_platform_count += 1
  if gpu_platform_count >= 2:
    raise UserInputError('CUDA / ROCm are mututally exclusive. '

Status ProcessInputs(
    const TF_Graph* fn_body, const char* fn_name, int ninputs,
    const TF_Output* inputs, std::vector<OutputTensor>* input_tensors,
    std::unordered_map<const Node*, std::vector<int>>* input_nodes)
    TF_EXCLUSIVE_LOCKS_REQUIRED(fn_body->mu) {
  input_tensors->reserve(ninputs);
  for (int i = 0; i < ninputs; ++i) {
    Node* node = inputs[i].oper ? &inputs[i].oper->node : nullptr;
    int idx = inputs[i].index;

               std::vector<TFE_TensorHandle*> inputs,
               const TFE_OpAttrs* attributes, int expected_max_outputs,
               std::vector<TensorHandlePtr>* outputs, TF_Status* status) const
      TF_EXCLUSIVE_LOCKS_REQUIRED(execution_mutex_);

  enum class ExecutionState {
    kReadyToExecute,
    kHasResult,
    kIdle,
    kShuttingDown,
  };

  tensorflow::mutex execution_mutex_;