d := divisibleSize / cnt
			if d <= prevD {
				prevD = d
				setSize = cnt
			}
		}
	}
	return setSize
}

// possibleSetCountsWithSymmetry returns symmetrical setCounts based on the
// input argument patterns, the symmetry calculation is to ensure that
// we also use uniform number of drives common across all ellipses patterns.
func possibleSetCountsWithSymmetry(setCounts []uint64, argPatterns []ellipses.ArgPattern) []uint64 {

     *
     * @return the message builder factory
     */
    @Nonnull
    MessageBuilderFactory messageBuilderFactory();

    /**
     * Returns the command-line arguments to be parsed.
     *
     * @return a list of argument strings
     */
    @Nonnull
    List<String> args();

    /**
     * Per-request {@link Lookup} for customization.
     *
     * @return a lookup possibly with custom components

Note, since it is still `pip` and `pip-compile` tools used under the hood, so
most of the command line arguments and features supported by those tools will be
acknowledged by the Bazel requirements updater command as well. For example, if
you wish the updater to consider pre-release versions simply pass `--pre`
argument to the bazel command:

```

    TF_AttrBuilder* builder, const char* device_type, TF_Status* status);

// For argument number input_index, fetch the corresponding number_attr that
// needs to be updated with the argument length of the input list.
// Returns nullptr if there is any problem like op_name is not found, or the
// argument does not support this attribute type.
TF_CAPI_EXPORT extern const char* TF_GetNumberAttrForOpListInput(

{!> ../../docs_src/extra_models/tutorial003.py!}
```

////

### `Union` in Python 3.10

In this example we pass `Union[PlaneItem, CarItem]` as the value of the argument `response_model`.

Because we are passing it as a **value to an argument** instead of putting it in a **type annotation**, we have to use `Union` even in Python 3.10.

If it was in a type annotation we could have used the vertical bar, as:

```Python

	aggFnMax   FuncName = "MAX"
	aggFnMin   FuncName = "MIN"
	aggFnSum   FuncName = "SUM"
)

var (
	errNonNumericArg = func(fnStr FuncName) error {
		return fmt.Errorf("%s() requires a numeric argument", fnStr)
	}
	errInvalidAggregation = errors.New("Invalid aggregation seen")
)

type aggVal struct {
	runningSum             *Value
	runningCount           int64
	runningMax, runningMin *Value

  local type="$1"
  local opt="$2"
  local arg="$3"
  if [[ -z "$arg" ]] || [[ "${arg:0:1}" == "-" ]]; then
    die "$opt requires <$type> argument"
  fi
}
is_function_defined() {
  declare -f "$1" > /dev/null
}

# If we're *not* running in a terminal, and we don't have any arguments, then we need to add the 'ui' parameter
detect_terminal_for_ui() {
  [[ ! -t 0 ]] && [[ "${#residual_args}" == "0" ]] && {
    addResidual "ui"

Übergeben Sie der Funktion `*` als ersten Parameter.

   * @return {@link InetAddress} representing the argument
   * @throws IllegalArgumentException if the argument is not a valid IP string literal
   */
  @CanIgnoreReturnValue // TODO(b/219820829): consider removing
  public static InetAddress forString(String ipString) {
    Scope scope = new Scope();
    byte[] addr = ipStringToBytes(ipString, scope);

    // The argument was malformed, i.e. not an IP string literal.

*   Extends `tf.keras.layers.Lambda` layers to support multi-argument lambdas,
    and keyword arguments when calling the layer.
*   Functional models now get constructed if *any* tensor in a layer call's
    arguments/keyword arguments comes from a keras input. Previously the
    functional api would only work if all of the elements in the first argument
    to the layer came from a keras input.