f := fuzz.NewConsumer(data)
	f.AllowUnexportedFields()

	inInstallSpec := &v1alpha1.IstioOperatorSpec{}
	err := f.GenerateStruct(inInstallSpec)
	if err != nil {
		return 0
	}
	inTranslator := &translate.Translator{}
	err = f.GenerateStruct(inTranslator)
	if err != nil {
		return 0
	}
	if inTranslator.APIMapping == nil {
		return 0
	}
	if inTranslator.KubernetesMapping == nil {
		return 0
	}

	}
	if !ok {
		os.Stderr.Write(stderr)
		os.Exit(2)
	}
	return string(stdout), string(stderr)
}

// A typeConv is a translator from dwarf types to Go types
// with equivalent memory layout.
type typeConv struct {
	// Cache of already-translated or in-progress types.
	m map[string]*Type

	// Map from types to incomplete pointers to those types.
	ptrs map[string][]*Type

				if err := util.UnmarshalWithJSONPB(tt.iopString, iop, true); err != nil {
					t.Fatal(err)
				}
			}
			translator := NewTranslator()
			serviceObj, err := object.ParseYAMLToK8sObject([]byte(serviceString))
			assert.NoError(t, err)
			obj, err := translator.fixMergedObjectWithCustomServicePortOverlay(serviceObj,
				iop.Components.IngressGateways[0].GetK8S().GetService(), serviceObj)
			assert.NoError(t, err)

  if (!IsValidTFLiteMlirModule(module)) return std::nullopt;
  auto translator = std::unique_ptr<Translator>(
      new Translator(module, toco_flags, tags, op_or_arg_name_mapper, metadata,
                     custom_option_alignment));
  translator->convert_stablehlo_ = serialize_stablehlo_ops;
  auto ret = translator->TranslateInternal();
  if (translator->require_use_buffer_offset_) {
    ret = std::nullopt;

A. Unique TensorFlower <******@****.***> 1713119208 -0700

A. Unique TensorFlower <******@****.***> 1713119208 -0700

// RUN: tf-mlir-translate -mlir-tf-to-hlo-text %s -tf-input-shapes=10,17:17,19 -tf-xla-emit-use-tuple-args -tf-xla-emit-return-tuple | FileCheck %s
// RUN: tf-mlir-translate -mlir-tf-to-hlo-text %s -tf-input-shapes=10,17:17,19 | FileCheck -check-prefix=NO_TUPLES %s
// RUN: tf-mlir-translate -mlir-tf-to-hlo-text-via-builder %s -tf-input-shapes=10,17:17,19 | FileCheck -check-prefix=NO_TUPLES %s

module attributes {tf.versions = {producer = 179 : i32}} {

// RUN: tf-mlir-translate -mlir-tf-to-hlo-text %s -tf-input-shapes=: -tf-xla-emit-return-tuple | FileCheck %s
// RUN: tf-mlir-translate -mlir-tf-to-hlo-text %s -tf-input-shapes=: -tf-xla-emit-use-tuple-args -tf-xla-emit-return-tuple | FileCheck -check-prefix=TUPLE-ARGS %s
// RUN: tf-mlir-translate -mlir-tf-to-hlo-text %s -tf-input-shapes=: | FileCheck -check-prefix=NO_RET_TUPLE %s

// RUN: tf-mlir-translate -mlir-to-graphdef %s | tf-mlir-translate -graphdef-to-mlir | tf-mlir-translate -mlir-to-graphdef | FileCheck %s

// Verifies that optional symbol ref attributes that aren't optional in TensorFlow are handled by setting the value to an empty string.
module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 458 : i32}} {
  func.func @main() {
    tf_executor.graph {

import org.apache.commons.io.input.BOMInputStream;
import org.apache.commons.text.translate.AggregateTranslator;
import org.apache.commons.text.translate.CharSequenceTranslator;
import org.apache.commons.text.translate.EntityArrays;
import org.apache.commons.text.translate.LookupTranslator;
import org.apache.commons.text.translate.NumericEntityUnescaper;
import org.codelibs.core.io.InputStreamUtil;