t.Fatalf("unexpected CreateHeader error: %v", err)
	}
	if err := w.Close(); err != nil {
		t.Fatalf("unexpected Close error: %v", err)
	}

	want, err := os.ReadFile("testdata/time-go.zip")
	if err != nil {
		t.Fatalf("unexpected ReadFile error: %v", err)
	}
	if got := buf.Bytes(); !bytes.Equal(got, want) {
		fmt.Printf("%x\n%x\n", got, want)
		t.Error("contents of time-go.zip differ")

			},
		},
	}

	for i, testCase := range testTable {
		t.Run(fmt.Sprint(i), func(t *testing.T) {
			testdataFile := "testdata/testdata.parquet"
			file, err := os.Open(testdataFile)
			if err != nil {
				t.Fatal(err)
			}

			s3Select, err := NewS3Select(bytes.NewReader(testCase.requestXML))
			if err != nil {

	}
}

func TestReadAfterLines(t *testing.T) {
	line1 := "this is line1"
	restData := "this is line2\nthis is line 3\n"
	inbuf := bytes.NewReader([]byte(line1 + "\n" + restData))
	outbuf := new(strings.Builder)
	maxLineLength := len(line1) + len(restData)/2
	l := NewReaderSize(inbuf, maxLineLength)
	line, isPrefix, err := l.ReadLine()

	}
	// set of inputs for uploading the objects before tests for downloading is done.
	putObjectInputs := []struct {
		bucketName    string
		objectName    string
		contentLength int64
		textData      []byte
		metaData      map[string]string
	}{
		{bucketName, objectName, int64(len(bytesData[0].byteData)), bytesData[0].byteData, make(map[string]string)},
	}

flow/core/runtime_fallback/test/saved_model,tensorflow/core/runtime_fallback/test/testdata,tensorflow/core/tfrt/stubs,tensorflow/core/tfrt/tfrt_session,tensorflow/core/tfrt/mlrt,tensorflow/core/tfrt/mlrt/attribute,tensorflow/core/tfrt/mlrt/kernel,tensorflow/core/tfrt/mlrt/bytecode,tensorflow/core/tfrt/mlrt/interpreter,tensorflow/compiler/mlir/tfrt/translate/mlrt,tensorflow/compiler/mlir/tfrt/translate/mlrt/testdata,tensorflow/core/tfrt/gpu,tensorflow/core/tfrt/run_handler_thread_pool,tensorflow/...

    }

    @Test
    void testDfsInfo1_EncodeDecode() throws NdrException {
        netdfs.DfsInfo1 info1 = new netdfs.DfsInfo1();
        info1.entry_path = "test_path";

        ByteArrayOutputStream bos = new ByteArrayOutputStream();
        // Create buffer for encoding - initially allocate some space
        byte[] encodeBuffer = new byte[1024];

}

TEST(CAPI, SavedModel) {
  // Load the saved model.
  const std::string saved_model_dir = tensorflow::GetDataDependencyFilepath(
      tensorflow::io::JoinPath("tensorflow", "cc", "saved_model", "testdata",
                               "half_plus_two", "00000123"));
  TF_SessionOptions* opt = TF_NewSessionOptions();
  TF_Buffer* run_options = TF_NewBufferFromString("", 0);
  TF_Buffer* metagraph = TF_NewBuffer();

	// Create a testbucket
	err = objLayer.MakeBucket(ctx, "testbucket", MakeBucketOptions{})
	if err != nil {
		t.Fatal(err)
	}

	// Unzip sample object data to the existing disks
	err = unzipArchive("testdata/xl-meta-inline-notinline.zip", path)
	if err != nil {
		t.Fatal(err)
	}

	// Try to read the object and check its md5sum

	// create xlStorage test setup
	xlStorage, _, err := newXLStorageTestSetup(t)
	if err != nil {
		t.Fatalf("Unable to cfgreate xlStorage test setup, %s", err)
	}

	xlMeta, _ := os.ReadFile("testdata/xl.meta")
	fi, _ := getFileInfo(xlMeta, "exists", "as-file", "", fileInfoOpts{Data: false})

	// Create files for the test cases.
	if err = xlStorage.MakeVol(t.Context(), "exists"); err != nil {

		}
		rec = httptest.NewRecorder()
		apiRouter.ServeHTTP(rec, reqC)
		checkRespErr(rec, http.StatusOK)
	}
}

// unzip a file into a specific target dir - used to unzip sample data in cmd/testdata/
func unzipArchive(zipFilePath, targetDir string) error {
	zipReader, err := zip.OpenReader(zipFilePath)
	if err != nil {
		return err
	}
	for _, file := range zipReader.File {