### Ausgabemodell in der Dokumentation { #model-for-output-in-docs }

Sie können das Ausgabemodell auch in der Dokumentation überprüfen. **Sowohl** `name` **als auch** `description` sind mit einem **roten Sternchen** als **erforderlich** markiert:

<div class="screenshot">
<img src="/img/tutorial/separate-openapi-schemas/image03.png">
</div>

func TestChecksumSerializeDeserializeMultiPart(t *testing.T) {
	// Create dummy data that we'll split into 3 parts
	dummyData := []byte("The quick brown fox jumps over the lazy dog. " +
		"Pack my box with five dozen brown eggs. " +
		"Have another go it will all make sense in the end!")

	// Split data into 3 parts
	partSize := len(dummyData) / 3
	part1Data := dummyData[0:partSize]
	part2Data := dummyData[partSize : 2*partSize]

## Website

[fess.codelibs.org](https://fess.codelibs.org/)

## Probleme/Fragen

[discuss.codelibs.org](https://discuss.codelibs.org/c/FessEN/)

## Erste Schritte

  Please upgrade your code to TensorFlow 2.0:
    * https://www.tensorflow.org/guide/migrate

  Or install the latest stable TensorFlow 1.X release:
    * `pip install -U "tensorflow==1.*"`

  Otherwise your code may be broken by the change.

  """)

# Make sure directory containing top level submodules is in
# the __path__ so that "from tensorflow.foo import bar" works.
# We're using bitwise, but there's nothing special about that.

                // Lost read cache - invalidate directory cache
                entry.invalidate();
            }
        } else {
            // Lease completely broken - invalidate cache
            entry.invalidate();
        }

        if ((newState & Smb2LeaseState.SMB2_LEASE_HANDLE_CACHING) == 0) {
            // Lost handle cache - may need to close directory handle

    OVERREPORTING_SIZE_LIST = unmodifiableList(new MisleadingSizeList<>(collection123, 1));
  }

  /*
   * c.g.c.collect.testing.Helpers.misleadingSizeList has a broken Iterator, so we can't use it. (I
   * mean, ideally we'd fix it....) Also, we specifically need a List so that we trigger the fast
   * path in join(Iterable).
   */

Erstellen Sie dann Klassen-Attribute mit festgelegten Werten, welches die erlaubten Werte sein werden:

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}


/// tip | Tipp

Falls Sie sich fragen, was „AlexNet“, „ResNet“ und „LeNet“ ist, das sind Namen von <abbr title="Genau genommen, Deep-Learning-Modellarchitekturen">Modellen</abbr> für maschinelles Lernen.

///

        // test whether the hash values have different output bits
        diff |= hash1 ^ hash2;

        count++;
        // check whether we've exceeded the probabilistically
        // likely number of trials to have proven no funneling
        if (count > maxCount) {
          Assert.fail(
              "input bit("
                  + i
                  + ") was found not to affect all "
                  + hashBits

        // test whether the hash values have different output bits
        diff |= hash1 ^ hash2;

        count++;
        // check whether we've exceeded the probabilistically
        // likely number of trials to have proven no funneling
        if (count > maxCount) {
          Assert.fail(
              "input bit("
                  + i
                  + ") was found not to affect all "
                  + hashBits

`UploadFile` hat die folgenden `async`hronen Methoden. Sie alle rufen die entsprechenden Methoden des darunterliegenden Datei-Objekts auf (wobei intern `SpooledTemporaryFile` verwendet wird).

* `write(daten)`: Schreibt `daten` (`str` oder `bytes`) in die Datei.