"""Test cases for quantize_model python wrappers."""

  def test_quantize_model_fails_when_invalid_quant_options_serialization(self):
    src_saved_model_path = self.create_tempdir().full_path
    dst_saved_model_path = self.create_tempdir().full_path
    signature_def_keys = ['serving_default']
    quant_opts_serialized = 'invalid proto serialization string'.encode('utf-8')

class FileSizeTestCase(test.TestCase):

  def setUp(self):
    super().setUp()

    self.path_a = self.create_tempdir('dir_a').full_path
    self.create_tempfile(file_path='dir_a/w.txt', content='abcd')

    self.path_b = self.create_tempdir('dir_b').full_path
    self.create_tempfile(file_path='dir_b/x.txt', content='1234')
    self.create_tempfile(file_path='dir_b/y.txt', content='56')

    self._input_saved_model_path = self.create_tempdir('input').full_path
    self._output_saved_model_path = self.create_tempdir('output').full_path
    # Extra output path occasionally used for comparing two different
    # quantized models.
    self._output_saved_model_path_2 = self.create_tempdir('output2').full_path

  def _extract_first_xla_call_module_op(

    self._input_saved_model_path = self.create_tempdir('input').full_path
    self._output_saved_model_path = self.create_tempdir('output').full_path
    # Extra output path occasionally used for comparing two different
    # quantized models.
    self._output_saved_model_path_2 = self.create_tempdir('output2').full_path

  def _get_dir_size(self, path: str = '.'):

    path_map = {'serving_default': dataset_path}
    repr_dataset.TfRecordRepresentativeDatasetSaver(path_map).save(
        {'serving_default': data_gen()}
    )

    calibration_data_dir = self.create_tempdir('calibration_data').full_path
    config = qc.QuantizationConfig(
        static_range_ptq_preset=qc.StaticRangePtqPreset(
            representative_datasets=[
                qc.RepresentativeDatasetConfig(

  ):
    input_type = dtypes.int64
    model = self._create_gather_model(input_type, use_variable)
    input_saved_model_path = self.create_tempdir('input').full_path
    saved_model_save.save(model, input_saved_model_path)

    tags = {tag_constants.SERVING}
    output_directory = self.create_tempdir().full_path

    quantization_options = quant_opts_pb2.QuantizationOptions(

#include "tsl/platform/status_matchers.h"

namespace tensorflow {
namespace {

using ::stablehlo::quantization::QuantizationConfig;
using ::stablehlo::quantization::io::CreateTmpDir;
using ::testing::HasSubstr;
using ::tsl::testing::IsOk;
using ::tsl::testing::StatusIs;

// Test cases for `RunQuantization` mainly tests for error cases because testing

  absl::StatusOr<std::string> tmp_dir = CreateTmpDir();

  ASSERT_THAT(tmp_dir, IsOk());

  auto* const env = tsl::Env::Default();
  EXPECT_THAT(env->FileExists(*tmp_dir), IsOk());
}

TEST(IoTest, CreateTmpDirWhenInvalidPathReturnsInternalError) {
  TestEnvBrokenFileSystem test_env{};
  absl::StatusOr<std::string> tmp_dir = CreateTmpDir(&test_env);

}

absl::StatusOr<std::string> CreateTmpDir(tsl::Env* const env) {
  TF_ASSIGN_OR_RETURN(std::string tmp_dir, GetLocalTmpFileName(env));

  if (!env->RecursivelyCreateDir(tmp_dir).ok()) {
    return absl::InternalError(
        absl::StrFormat("Failed to create tmp dir: '%s'", tmp_dir));
  }

  return tmp_dir;
}

absl::StatusOr<std::string> CreateTmpDir() {
  // The overloaded function uses the default env.

      }
    }

    if (testDir == null) {
      // testdata resources aren't file:// urls, so create a directory to store them in and then
      // copy the resources to the filesystem as needed
      testDir = createTempDir();
    }

    return testDir;
  }

  /** Returns the file with the given name under the testdata directory. */
  protected final @Nullable File getTestFile(String name) throws IOException {