### Saved graphs and checkpoints

When loading untrusted serialized computation graphs (in form of a `GraphDef`,
`SavedModel`, or equivalent on-disk format), the set of computation primitives
available to TensorFlow is powerful enough that you should assume that the
TensorFlow process effectively executes arbitrary code.

The risk of loading untrusted checkpoints depends on the code or graph that you

                                                    <td>${f:h(data.token)}</td>
                                                    <td>${f:h(data.reading)}</td>
                                                </tr>
                                            </c:forEach>
                                            </tbody>
                                        </table>

    protected void setUp() throws Exception {
        file1 = File.createTempFile("kuromoji_", ".txt");
        FileUtil.write(
                file1.getAbsolutePath(),
                "token1,seg1,reading1,pos1\ntoken2,seg2,reading2,pos2\ntoken3,seg3,reading3,pos3"
                        .getBytes(Constants.UTF_8));
    }

    @Override
        protected void tearDown(TestInfo testInfo) throws Exception {
        file1.delete();
    }

    "--connect-timeout",
  ).help(
    "Maximum time allowed for connection (seconds)",
  ).int()
    .default(DEFAULT_TIMEOUT)

  val readTimeout: Int by option("--read-timeout")
    .help("Maximum time allowed for reading data (seconds)")
    .int()
    .default(DEFAULT_TIMEOUT)

  val callTimeout: Int by option(
    "--call-timeout",
  ).help(
    "Maximum time allowed for the entire call (seconds)",
  ).int()

    stream.defaultWriteObject();
    stream.writeObject(keyTypeOrObjectUnderJ2cl);
    Serialization.writeMap(this, stream);
  }

  @SuppressWarnings("unchecked") // reading field populated by writeObject
  @GwtIncompatible // java.io.ObjectInputStream
  private void readObject(ObjectInputStream stream) throws IOException, ClassNotFoundException {
    stream.defaultReadObject();

		n2, e2 := io.ReadFull(r2, b2)
		if n1 != n2 {
			return false, fmt.Sprintf("Read %d != %d bytes from the readers", n1, n2)
		}
		if !bytes.Equal(b1[:n1], b2[:n2]) {
			return false, fmt.Sprintf("After reading %d equal buffers (32Kib each), we got the following two strings:\n%v\n%v\n",
				i, b1, b2)
		}
		// Check if stream has ended
		if (e1 == io.ErrUnexpectedEOF && e2 == io.ErrUnexpectedEOF) || (e1 == io.EOF && e2 == io.EOF) {

But normally you won't have to worry about it, it's done automatically, continue reading. 🤓

///

## Use Cases { #use-cases }

You could use this to stream data from an **AI LLM** service, from **logs** or **telemetry**, or from other types of data that can be structured in **JSON** items.

/// tip

	resp := rw.Result()
	if resp.StatusCode != 123 {
		t.Fatalf("unexpected status: %v", resp.StatusCode)
	}
	body, err := io.ReadAll(resp.Body)
	if err != nil {
		t.Fatalf("reading response body failed: %v", err)
	}
	if string(body) != "hello" {
		t.Fatalf("response body incorrect: %v", string(body))
	}

	// Check that Unwrap works
	if trw.Unwrap() != rw {

        }

        @Test
        @DisplayName("Test read string with odd Unicode alignment")
        void testReadStringUnicodeAlignment() {
            testBlock.setUseUnicode(true);
            // Test reading Unicode string with alignment

            byte[] buffer = new byte[100];
            // Write "Test" in UTF-16LE directly at position 2 (even offset)

	r := rand.New(rand.NewSource(time.Now().UnixNano()))
	randInterval := func() time.Duration {
		return time.Duration(r.Float64() * 5 * float64(time.Second))
	}

	// To avoid all MinIO nodes reading the tier config object at the same
	// time.
	t := time.NewTimer(tierCfgRefresh + randInterval())
	defer t.Stop()
	for {
		select {
		case <-ctx.Done():
			return
		case <-t.C: