// UTF-32LE.
    "ffff0000".decodeHex(),
  )

/**
 * Returns an array containing only elements found in this array and also in [other]. The returned
 * elements are in the same order as in this.
 */
internal fun Array<String>.intersect(
  other: Array<String>,
  comparator: Comparator<in String>,
): Array<String> {
  val result = mutableListOf<String>()
  for (a in this) {
    for (b in other) {

                    <mxGeometry relative="1" as="geometry">
                        <Array as="points">
                            <mxPoint x="800" y="521"/>
                            <mxPoint x="800" y="560"/>
                        </Array>
                        <mxPoint x="803" y="521" as="sourcePoint"/>
                    </mxGeometry>
                </mxCell>

   * unknown.
   */
  abstract fun contentLength(): Long

  fun byteStream(): InputStream = source().inputStream()

  abstract fun source(): BufferedSource

  /**
   * Returns the response as a byte array.
   *
   * This method loads entire response body into memory. If the response body is very large this
   * may trigger an [OutOfMemoryError]. Prefer to stream the response body if this is a
   * possibility for your response.

Pero, todo **simplemente funciona** por defecto.

### Validación

* Validación para la mayoría (¿o todos?) los **tipos de datos** de Python incluyendo:
    * Objetos JSON (`dict`).
    * JSON array (`list`) definiendo tipos de ítem.
    * Campos de texto (`str`) definiendo longitudes mínimas y máximas.
    * Números (`int`, `float`) con valores mínimos y máximos, etc.

* Validación para tipos más exóticos como:

        "//tensorflow/cc:grad_ops",
        "//tensorflow/cc/saved_model:signature_constants",
        "//tensorflow/cc/saved_model:tag_constants",
        "//tensorflow/compiler/jit",
        "//tensorflow/core:array_ops_op_lib",
        "//tensorflow/core:bitwise_ops_op_lib",
        "//tensorflow/core:control_flow_ops_op_lib",
        "//tensorflow/core:core_cpu_internal",
        "//tensorflow/core:direct_session",

                    <mxGeometry relative="1" as="geometry">
                        <Array as="points">
                            <mxPoint x="800" y="521"/>
                            <mxPoint x="800" y="560"/>
                        </Array>
                        <mxPoint x="803" y="521" as="sourcePoint"/>
                    </mxGeometry>
                </mxCell>

    ```bash
    bazel run //tensorflow/tools/docs:tf_doctest
    ```

    or

    ```bash
    bazel run //tensorflow/tools/docs:tf_doctest -- --module=ops.array_ops
    ```

    The `--module` is relative to `tensorflow.python`.

#### Debug builds

When [building Tensorflow](https://www.tensorflow.org/install/source), passing

}

// DEPRECATED 1.9 - This group version of NetworkPolicySpec is deprecated by networking/v1/NetworkPolicySpec.
message NetworkPolicySpec {
  // Selects the pods to which this NetworkPolicy object applies.  The array of ingress rules
  // is applied to any pods selected by this field. Multiple network policies can select the
  // same set of pods.  In this case, the ingress rules for each are combined additively.

    if (analysisContext.builtIns.areSameArrayTypeIgnoringProjections(containingArrayType, constantType)) {
        // If an element in the array has the same type as the containing array, it's a spread component that needs
        // to be expanded here. (It should have the array element type instead.)
        (constantValue as ArrayValue).value.expandArrayAnnotationValue(containingArrayType, analysisContext)
    } else {

    bytesIn.writeByte(0x3F) // Dynamic table size update (size = 55).
    bytesIn.writeByte(0x18)
    hpackReader!!.readHeaders()
    assertThat(hpackReader!!.headerCount).isEqualTo(1)
  }

  /** Header table backing array is initially 8 long, let's ensure it grows.  */
  @Test
  fun dynamicallyGrowsBeyond64Entries() {
    // Lots of headers need more room!
    hpackReader = Hpack.Reader(bytesIn, 16384, 4096)