labels.dictId=사전 ID
labels.docId=문서 ID
labels.endTime=종료 시간
labels.hq=hq
labels.inputs=변환 원본
labels.jobLogging=로깅
labels.jobName=이름
labels.jobStatus=상태
labels.labelTypeIds=라벨
labels.lang=언어
labels.outputs=대상
labels.pos=품사
labels.purgeJobLogDay=이전 작업 로그 삭제
labels.purgeUserInfoDay=이전 이용자 로그 삭제
labels.reading=읽기
labels.roleTypeIds=역할 ID
labels.scriptData=스크립트
labels.scriptResult=결과
labels.scriptType=실행 방법

				"application/vnd.3gpp.pic-bw-var",
				"application/vnd.3gpp.sms",
				"application/vnd.3gpp2.bcmcsinfo+xml",
				"application/vnd.3gpp2.sms",
				"application/vnd.3gpp2.tcap",
				"application/vnd.3m.post-it-notes",
				"application/vnd.accpac.simply.aso",
				"application/vnd.accpac.simply.imp",
				"application/vnd.acucobol",
				"application/vnd.acucorp",

labels.endTime=Hora de término
labels.hq=hq
labels.inputs=Entradas
labels.jobLogging=Logging
labels.jobName=Nome
labels.jobStatus=Estado
labels.labelTypeIds=Rótulos
labels.lang=Idioma
labels.outputs=Saídas
labels.pos=Parte da fala
labels.purgeJobLogDay=Excluir logs de trabalho anteriores
labels.purgeUserInfoDay=Excluir logs de usuário anteriores
labels.reading=Leitura
labels.roleTypeIds=ID da função
labels.scriptData=Script

  // Test iterating through the nodes of a graph.
  found_placeholder = false;
  found_scalar_const = false;
  found_add = false;
  bool found_neg = false;
  size_t pos = 0;
  TF_Operation* oper;
  while ((oper = TF_GraphNextOperation(graph, &pos)) != nullptr) {
    if (oper == feed) {
      EXPECT_FALSE(found_placeholder);
      found_placeholder = true;
    } else if (oper == three) {

labels.endTime=Heure de fin
labels.hq=hq
labels.inputs=Entrées
labels.jobLogging=Journalisation
labels.jobName=Nom
labels.jobStatus=Statut
labels.labelTypeIds=Étiquettes
labels.lang=Langue
labels.outputs=Sorties
labels.pos=Partie du discours
labels.purgeJobLogDay=Supprimer les anciens journaux de tâches
labels.purgeUserInfoDay=Supprimer les anciens journaux utilisateur
labels.reading=Lecture
labels.roleTypeIds=ID de rôle

labels.endTime=Ora di fine
labels.hq=hq
labels.inputs=Input
labels.jobLogging=Registrazione
labels.jobName=Nome
labels.jobStatus=Stato
labels.labelTypeIds=Etichette
labels.lang=Lingua
labels.outputs=Output
labels.pos=Parte del discorso
labels.purgeJobLogDay=Elimina log di lavoro precedenti
labels.purgeUserInfoDay=Elimina log utente precedenti
labels.reading=Lettura
labels.roleTypeIds=ID ruolo
labels.scriptData=Script

		err:  ErrHeader,
	}, {
		file: "testdata/pax-bad-hdr-large.tar.bz2",
		err:  ErrFieldTooLong,
	}, {
		file: "testdata/pax-bad-mtime-file.tar",
		err:  ErrHeader,
	}, {
		file: "testdata/pax-pos-size-file.tar",
		headers: []*Header{{
			Name:     "foo",
			Mode:     0640,
			Uid:      319973,
			Gid:      5000,
			Size:     999,
			ModTime:  time.Unix(1442282516, 0),
			Typeflag: '0',

	public fun headers (Lokhttp3/Headers;)Lokhttp3/Request$Builder;
	public fun method (Ljava/lang/String;Lokhttp3/RequestBody;)Lokhttp3/Request$Builder;
	public fun patch (Lokhttp3/RequestBody;)Lokhttp3/Request$Builder;
	public fun post (Lokhttp3/RequestBody;)Lokhttp3/Request$Builder;
	public fun put (Lokhttp3/RequestBody;)Lokhttp3/Request$Builder;
	public fun query (Lokhttp3/RequestBody;)Lokhttp3/Request$Builder;

        `DynamicUpdateSlice`.
    *   Enabled a new MLIR-based dynamic range quantization backend by default
        *   The new backend is used for post-training int8 dynamic range
            quantization and post-training float16 quantization.
        *   Set `experimental_new_dynamic_range_quantizer` in
            tf.lite.TFLiteConverter to False to disable this change

* bootstrap: Start hostNetwork pods even if network plugin not ready ([#33347](https://github.com/kubernetes/kubernetes/pull/33347), [@justinsb](https://github.com/justinsb))
* Factor out post-init swagger and OpenAPI routes ([#32590](https://github.com/kubernetes/kubernetes/pull/32590), [@sttts](https://github.com/sttts))