if m1.IsNarrowerThan(m2) {
		return m1
	}
	return m2
}

func (n *NUMAInfo) Closest(m1 bitmask.BitMask, m2 bitmask.BitMask) bitmask.BitMask {
	// If the length of both bitmasks aren't the same, choose the one that is narrowest.
	if m1.Count() != m2.Count() {
		return n.Narrowest(m1, m2)
	}

	m1Distance := n.NUMADistances.CalculateAverageFor(m1)
	m2Distance := n.NUMADistances.CalculateAverageFor(m2)

    ```

    Zainstaluj też `uvicorn`, który będzie służył jako serwer:

    ```
    pip install "uvicorn[standard]"
    ```

    Tak samo możesz zainstalować wszystkie dodatkowe biblioteki, których chcesz użyć.

## Zaawansowany poradnik

Jest też **Zaawansowany poradnik**, który możesz przeczytać po lekturze tego **Samouczka**.

  /**
   * Returns {@code x}, rounded to a {@code double} with the specified rounding mode. If {@code x}
   * is precisely representable as a {@code double}, its {@code double} value will be returned;
   * otherwise, the rounding will choose between the two nearest representable values with {@code
   * mode}.
   *
   * <p>For the case of {@link RoundingMode#HALF_DOWN}, {@code HALF_UP}, and {@code HALF_EVEN},

	}{
		{
			name:             "matches",
			all:              []string{"one", "two"},
			enabled:          []string{"one", "two"},
			expectedDisabled: []string{},
		},
		{
			name:             "choose one",
			all:              []string{"one", "two"},
			enabled:          []string{"one"},
			expectedDisabled: []string{"two"},
		},
	}

	for _, tc := range tests {
		t.Run(tc.name, func(t *testing.T) {

For this purpose, we chose to use xDS transport protocol due to our expertise and existing infrastructure, and because the protocol is well suited to our needs.

However, while we chose to use the xDS *transport protocol*, we chose to not use the xDS resource types, such as Clusters and Listeners.

     * If a single version can satisfy all of the selectors, the result will reflect this.
     * If not, a minimal set of versions will be provided in the result, and conflict resolution will be required to choose.
     */
    private List<T> buildResolveResults(ModuleSelectors<? extends ResolvableSelectorState> selectors, VersionSelector allRejects) {

	e2 := exp
	if b := bits.Len32(mant); b < 25 {
		mant <<= uint(25 - b)
		e2 += b - 25
	}
	// Choose an exponent such that rounded mant*(2^e2)*(10^q) has
	// at least prec decimal digits, i.e
	//     mant*(2^e2)*(10^q) >= 10^(prec-1)
	// Because mant >= 2^24, it is enough to choose:
	//     2^(e2+24) >= 10^(-q+prec-1)
	// or q = -mulByLog2Log10(e2+24) + prec - 1
	q := -mulByLog2Log10(e2+24) + prec - 1

Assim podendo tentar ajudar a resolver essas questões.

## Faça perguntas

É possível <a href="https://github.com/tiangolo/fastapi/issues/new/choose" class="external-link" target="_blank">criar uma nova pergunta</a> no repositório do GitHub, por exemplo:

* Faça uma **pergunta** ou pergunte sobre um **problema**.
* Sugira novos **recursos**.

    * O Pydantic também permite representá-lo como uma "codificação ISO 8601 diferença de tempo", <a href="https://docs.pydantic.dev/latest/concepts/serialization/" class="external-link" target="_blank">cheque a documentação para mais informações</a>.
* `frozenset`:
    * Em requisições e respostas, será tratado da mesma forma que um `set`:
        * Nas requisições, uma lista será lida, eliminando duplicadas e convertendo-a em um `set`.

// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

package cpu

import "runtime"

// cacheLineSize is used to prevent false sharing of cache lines.
// We choose 128 because Apple Silicon, a.k.a. M1, has 128-byte cache line size.
// It doesn't cost much and is much more future-proof.
const cacheLineSize = 128

func initOptions() {
	options = []option{