TF_Operation** control_inputs,
                                 int max_control_inputs) {
  int count = 0;
  for (const auto* edge : oper->node.in_edges()) {
    if (edge->IsControlEdge() && !edge->src()->IsSource()) {
      if (count < max_control_inputs) {
        control_inputs[count] = ToOperation(edge->src());
      }
      ++count;
    }
  }

However, for the vast majority of issues, we aim to empower individuals to first resolve conflicts themselves, asking for help when needed, and only after that fails to escalate further. This approach gives people more control over the outcome of their dispute. 

If you are experiencing or witnessing conflict, we ask you to use the following escalation strategy to address the conflict:

      output_names_vec.push_back(string(output_names[i]));
    }
  }

  // Process control output names.
  std::vector<string> control_output_names_vec;
  if (control_output_names) {
    control_output_names_vec.reserve(ncontrol_outputs);
    for (int i = 0; i < ncontrol_outputs; ++i) {
      control_output_names_vec.push_back(string(control_output_names[i]));
    }
  }

  // Compute body nodes.

// Get the number of control inputs to an operation.
TF_CAPI_EXPORT extern int TF_OperationNumControlInputs(TF_Operation* oper);

// Get list of all control inputs to an operation.  `control_inputs` must
// point to an array of length `max_control_inputs` (ideally set to
// TF_OperationNumControlInputs(oper)).  Returns the number of control
// inputs (should match TF_OperationNumControlInputs(oper)).

                         std::unique_ptr<tensorflow::Graph>* graph,
                         tensorflow::FunctionLibraryDefinition* flib_def,
                         std::vector<std::string>* control_ret_node_names,
                         bool* control_rets_updated) override {
    // Inject failure to function instantiation if finding a node that contains
    // the given node name (error_node_) and requested device (error_device_).

  if (TF_GetCode(status) != TF_OK) return nullptr;
  if (parallel_tensor->num_tensors() == 1) {
    // Copy-off for single-device tensors is allowed to make debugging dynamic
    // control flow easier.
    return TFE_TensorHandleCopySharingTensor(parallel_tensor->tensor(0),
                                             status);
  } else {
    TF_SetStatus(
        status, TF_UNIMPLEMENTED,

      "Legal Entity" shall mean the union of the acting entity and all
      other entities that control, are controlled by, or are under common
      control with that entity. For the purposes of this definition,
      "control" means (i) the power, direct or indirect, to cause the
      direction or management of such entity, whether by contract or
      otherwise, or (ii) ownership of fifty percent (50%) or more of the

// could contain the op type and other attributes.
typedef struct TF_AbstractOp TF_AbstractOp;

// Stores a function representation that can be used for execution or for
// setting functional attributes of other composite ops e.g. control flow.
typedef struct TF_AbstractFunction TF_AbstractFunction;

// This allows the client to swap the implementation of the tracing engine.
// Any future call to TF_CreateFunction will use the implementation defined
// here.

    *   Deprecate `tf.contrib.learn`. Please check contrib/learn/README.md for
        instructions on how to convert existing code.
    *   `tf.contrib.data`
    *   Remove deprecated `tf.contrib.data.Dataset`, `tf.contrib.data.Iterator`,
        `tf.contrib.data.FixedLengthRecordDataset`,
        `tf.contrib.data.TextLineDataset`, and `tf.contrib.data.TFRecordDataset`
        classes.

are skipped, and any checks implemented inside the shape inference code are not
executed.

The security impact of skipping those checks should be low, since the attack
scenario would require a malicious user to be able to control the model which as
stated above is already equivalent to code execution. In any case, the
recommendation is not to serve models using Eager mode since it also has
performance limitations.

## Multi-Tenant environments