"""
        ),
    ] = _Unset,
    alias: Annotated[
        Optional[str],
        Doc(
            """
            An alternative name for the parameter field.

            This will be used to extract the data and for the generated OpenAPI.
            It is particularly useful when you can't use the name you want because it
            is a Python reserved keyword or similar.
            """
        ),
    ] = None,

		{name: "SBFIZ", argLength: 1, reg: gp11, asm: "SBFIZ", aux: "ARM64BitField"},
		// extract width bits of arg0 starting at bit lsb and insert at low end of result, remaining high bits are set to the high/sign bit of the extracted bitfield
		{name: "SBFX", argLength: 1, reg: gp11, asm: "SBFX", aux: "ARM64BitField"},

    // constant, then the output type can be statically determined.
    RankedTensorType out_ty = mlir::dyn_cast<RankedTensorType>(op.getType());
    if (!out_ty || !out_ty.hasStaticShape()) return failure();

    // Extract out all the constant indices' attributes and verify that data
    // types are static.
    SmallVector<DenseIntElementsAttr, 4> indices;
    indices.reserve(op.getN());

		if err == nil && len(rest) == 0 {
			attributes = append(attributes, attr)
		}
	}
	return attributes
}

// parseCSRExtensions parses the attributes from a CSR and extracts any
// requested extensions.
func parseCSRExtensions(rawAttributes []asn1.RawValue) ([]pkix.Extension, error) {
	// pkcs10Attribute reflects the Attribute structure from RFC 2986, Section 4.1.

For example, you might need to extract different subtrees of the archive into different paths within the destination directory.
The following sample uses the method to extract the files within the archive's `libs` directory into the root destination directory, rather than into a `libs` subdirectory:

====

	set := newStatefulSet(3)
	pod := newStatefulSetPod(set, 1)
	if parent, ordinal := getParentNameAndOrdinal(pod); parent != set.Name {
		t.Errorf("Extracted the wrong parent name expected %s found %s", set.Name, parent)
	} else if ordinal != 1 {
		t.Errorf("Extracted the wrong ordinal expected %d found %d", 1, ordinal)
	}
	pod.Name = "1-bar"
	if parent, ordinal := getParentNameAndOrdinal(pod); parent != "" {

  // TPU). Here, 'parent_func' is the func.FuncOp that owns the ops in 'ops'.
  //
  // Returns in 'caller' a tf.StatefulPartitionedCallOp that calls the function
  // that was extracted..

  // Find the input edges to form the set of operands to the new function call.
  llvm::SetVector<Value> inputs;
  for (Operation* op : ops) {
    for (Value operand : op->getOperands()) {

     */
    abstract E castForTesting(InternalEntry<K, V, ?> entry);

    /** Unsafely extracts the key reference queue used by this segment. */
    ReferenceQueue<K> getKeyReferenceQueueForTesting() {
      throw new AssertionError();
    }

    /** Unsafely extracts the value reference queue used by this segment. */
    ReferenceQueue<V> getValueReferenceQueueForTesting() {

     */
    abstract E castForTesting(InternalEntry<K, V, ?> entry);

    /** Unsafely extracts the key reference queue used by this segment. */
    ReferenceQueue<K> getKeyReferenceQueueForTesting() {
      throw new AssertionError();
    }

    /** Unsafely extracts the value reference queue used by this segment. */
    ReferenceQueue<V> getValueReferenceQueueForTesting() {

  for (auto tensor_index : op.outputs) {
    locations.push_back(TensorLoc(*tensors[tensor_index], builder, base));
  }
  return mlir::FusedLoc::get(builder.getContext(), locations);
}

// Extract the min max information in the tensor and create the quant stats op.
// If the input `tensor` has scale/zero_point, `res` should have quantized
// type, thus none stats op is required and nullptr is returned.