}

  auto get_full_op_name = [&](const std::string& op_name) {
    const char* kTfPrefix = "tf.";
    return kTfPrefix + op_name;
  };

  std::string op_name = get_full_op_name(node_type_name);
  if (back_edge_node_output_.contains(&node)) {
    op_name = op_name + ".sink";
  }

  mlir::OperationState result(GetLocation(node), op_name);
  for (int i = 0; i < node.num_outputs(); ++i) {

// needs to be updated with the argument length of the input list.
// Returns nullptr if there is any problem like op_name is not found, or the
// argument does not support this attribute type.
TF_CAPI_EXPORT extern const char* TF_GetNumberAttrForOpListInput(
    const char* op_name, int input_index, TF_Status* status);

// Returns 1 if the op is stateful, 0 otherwise. The return value is undefined

		failOnce.Do(func() {
			// (B) Evict two pods and fail this update.
			evict(podNames[1], podNames[2])
			handled = true
			err = errors.NewConflict(a.GetResource().GroupResource(), pdb.Name, fmt.Errorf("conflict"))
		})
		return handled, obj, err
	})

	// (A) Delete one pod
	if err := dc.coreClient.CoreV1().Pods("default").Delete(ctx, podNames[0], metav1.DeleteOptions{}); err != nil {
		t.Fatal(err)
	}

};

TF_KernelBuilder* TF_NewKernelBuilder(
    const char* op_name, const char* device_name,
    void* (*create_func)(TF_OpKernelConstruction*),
    void (*compute_func)(void*, TF_OpKernelContext*),
    void (*delete_func)(void*)) {
  TF_KernelBuilder* result = new TF_KernelBuilder;
  result->cc_builder = new ::tensorflow::KernelDefBuilder(op_name);
  result->cc_builder->Device(device_name);
  result->create_function = create_func;

import java.util.Locale;
import java.util.stream.Stream;

/**
 * OS support
 */
public class Os {

    /**
     * The OS Name.
     */
    public static final String OS_NAME = System.getProperty("os.name").toLowerCase(Locale.ENGLISH);

    /**
     * The OA architecture.
     */
    public static final String OS_ARCH = System.getProperty("os.arch").toLowerCase(Locale.ENGLISH);

    /**

  // START_SKIP_DOXYGEN
  class Impl;
  Impl* impl() { return impl_.get(); }
  const Impl* impl() const { return impl_.get(); }
  // END_SKIP_DOXYGEN

 private:
  Scope WithOpNameImpl(const string& op_name) const;

  friend class InternalScope;
  std::unique_ptr<Impl> impl_;
  explicit Scope(Impl*);
};

/// A helper struct to hold the scopes that would be used by a function
/// constructing a composite op.

				return err
			}
			if labelSelector != "" {
				if podNames, podNamespace, err = getPodNameBySelector(ctx, kubeClient, labelSelector); err != nil {
					return err
				}
			} else {
				if podNames, podNamespace, err = getPodNames(ctx, args[0], ctx.Namespace()); err != nil {
					return err
				}
			}
			for _, pod := range podNames {
				loggerName, err = setupEnvoyLogConfig(kubeClient, "", pod, podNamespace)

      "OptionalHasValue",  // b/173136483
      "OptionalGetValue",  // b/173136483
      "VarHandleOp",       // b/176819198
  };
  for (const char* skip : kOpsToSkip) {
    if (absl::StartsWith(orig_op->op_name(), skip)) return absl::OkStatus();
  }

  tf_core_op_expansion_node_counter->GetCell()->IncrementBy(1);

  LOG_FIRST_N(INFO, 1) << "Run Node Expansion Passes";

    for (StringRef op_name : func_count_map.keys()) {
      const int32_t quantized_count = func_count_map[op_name].num_quant;
      const int32_t total_count =
          quantized_count + func_count_map[op_name].num_float;
      lines.push_back(absl::StrFormat("%s %d/%d",
                                      pad_string(op_name, name_col_width),

    bool ignore_unregistered_attrs) {
  TF_ASSIGN_OR_RETURN(auto node_def, GetOperationNodeDef(inst, name));
  TF_ASSIGN_OR_RETURN(auto op_name,
                      GetTensorFlowOpName(inst->getName().getStringRef()));
  const tensorflow::OpRegistrationData* op_reg_data =
      tensorflow::OpRegistry::Global()->LookUp(op_name.str());
  TF_RETURN_IF_ERROR(GetAttrValuesFromOperation(inst, name, op_reg_data,