//// tab | Pydantic v2

У версії Pydantic 2 використовується атрибут `model_config`, який приймає `dict`, як описано в <a href="https://docs.pydantic.dev/latest/api/config/" class="external-link" target="_blank">документації Pydantic: Конфігурація</a>.

Ви можете встановити `"json_schema_extra"` як `dict`, що містить будь-які додаткові дані, які Ви хочете відобразити у згенерованій JSON-схемі, включаючи `examples`.

)

# To avoid duplication, check that the C++ or python library does not depend on
# the stream executor cuda plugins. Targets that want to use cuda APIs should
# instead depend on the dummy plugins in //tensorflow/compiler/xla/tsl/platform/default/build_config
# and use header only targets.
# TODO(ddunleavy): This seems completely broken. :tensorflow_cc depends on

	Flags      BatchJobReplicateFlags  `yaml:"flags" json:"flags"`
	Target     BatchJobReplicateTarget `yaml:"target" json:"target"`
	Source     BatchJobReplicateSource `yaml:"source" json:"source"`

	clnt *miniogo.Core `msg:"-"`
}

// RemoteToLocal returns true if source is remote and target is local
func (r BatchJobReplicateV1) RemoteToLocal() bool {
	return !r.Source.Creds.Empty()

  void SetOutputs(std::initializer_list<TF_Operation*> outputs);
  void SetOutputs(const std::vector<TF_Output>& outputs);
  void SetTargets(std::initializer_list<TF_Operation*> targets);

  void Run(TF_Status* s);

  void CloseAndDelete(TF_Status* s);

  TF_Tensor* output_tensor(int i) { return output_values_[i]; }

  TF_Session* mutable_session() { return session_; }

        assertEquals("0xFFFFFFFF", message, "Should return hex string for code smaller than any known.");
    }

    /**
     * Test getMessageByDcerpcError() with an error code larger than any known.
     * The binary search implementation has a bug where it accesses array out of bounds.
     */
    @Test
    void testGetMessageByDcerpcError_largerThanAny() {

    }

    // Helper method to set DfsEnumArray using reflection
    private void setDfsEnumArray(MsrpcDfsRootEnum target, netdfs.DfsEnumArray200 array) throws Exception {
        Field eField = netdfs.DfsEnumStruct.class.getDeclaredField("e");
        eField.setAccessible(true);
        eField.set(target.info, array);
    }

You can achieve that using <a href="https://docs.pydantic.dev/latest/concepts/validators/#field-after-validator" class="external-link" target="_blank">Pydantic's `AfterValidator`</a> inside of `Annotated`.

/// tip

Pydantic also has <a href="https://docs.pydantic.dev/latest/concepts/validators/#field-before-validator" class="external-link" target="_blank">`BeforeValidator`</a> and others. 🤓

///

   * i, i + target.length)} contains exactly the same elements as {@code target}.
   *
   * @param array the array to search for the sequence {@code target}
   * @param target the array to search for as a sub-sequence of {@code array}
   */
  public static int indexOf(char[] array, char[] target) {
    checkNotNull(array, "array");
    checkNotNull(target, "target");
    if (target.length == 0) {

// A chunk has the following format:
//
//	<chunk-size-as-hex> + ";chunk-signature=" + <signature-as-hex> + "\r\n" + <payload> + "\r\n"
//
// First, we read the chunk size but fail if it is larger
// than 16 MiB. We must not accept arbitrary large chunks.
// One 16 MiB is a reasonable max limit.
//
// Then we read the signature and payload data. We compute the SHA256 checksum

/// info | Información

Puedes leer más sobre los manejadores `lifespan` de Starlette en <a href="https://www.starlette.dev/lifespan/" class="external-link" target="_blank">la documentación de `Lifespan` de Starlette</a>.