labels.crawling_info_delete_all_link=Elimina tutto
labels.crawling_info_delete_all_confirmation=Sei sicuro di voler eliminare tutto?
labels.crawling_info_delete_all_cancel=Annulla
labels.crawling_info_thread_dump=Dump thread
labels.crawling_info_CrawlerStartTime=Ora di inizio crawler
labels.crawling_info_CrawlerEndTime=Ora di fine crawler
labels.crawling_info_CrawlerExecTime=Tempo di esecuzione crawler

success.started_data_update=Datenaktualisierungsprozess gestartet.
success.reindex_started=Neuindizierung gestartet.
success.bulk_process_started=Massenprozess gestartet.
success.print_thread_dump=Thread-Dump in eine Protokolldatei gedruckt.
success.install_plugin=Plugin {0} wird installiert.
success.delete_plugin=Plugin {0} wird gelöscht.
success.upload_file_to_storage={0} hochgeladen.
success.sso_logout=Sie wurden abgemeldet.

      output_tensors, output_names_vec, control_output_nodes,
      control_output_names_vec, description, &fdef);
  if (TF_GetCode(status) != TF_OK) {
    return nullptr;
  }

  // Dump the op creation stacktraces for debugging purpose.
  DEBUG_DATA_DUMPER()->DumpOpCreationStackTraces(
      fn_name, kDebugGroupOpStacktrace, "initial", &fn_body->graph);

  tensorflow::StackTracesMap stack_traces;

      new Murmur3_32HashFunction(0, /* supplementaryPlaneFix= */ false);
  static final HashFunction MURMUR3_32_FIXED =
      new Murmur3_32HashFunction(0, /* supplementaryPlaneFix= */ true);

  // We can include the non-BMP fix here because Hashing.goodFastHash stresses that the hash is a
  // temporary-use one. Therefore it shouldn't be persisted.
  static final HashFunction GOOD_FAST_HASH_32 =

        if (mimeType == null) {
            return true;
        }

        return switch (mimeType) {
        case "image/png", "image/gif", "image/jpeg", "image/bmp" -> true;
        default -> false;
        };
    }

    /**
     * Processes and saves an image from the input stream to the output file as a thumbnail.
     *

	}
	if err != nil {
		return osErrToFileErr(err)
	}

	var bufp *[]byte
	switch {
	case fileSize <= xioutil.SmallBlock:
		bufp = xioutil.ODirectPoolSmall.Get()
		defer xioutil.ODirectPoolSmall.Put(bufp)
	default:
		bufp = xioutil.ODirectPoolLarge.Get()
		defer xioutil.ODirectPoolLarge.Put(bufp)
	}

	var written int64
	if odirectEnabled {

func waitForHTTPStream(respBody io.ReadCloser, w io.Writer) error {
	var tmp [1]byte
	// 8K copy buffer, reused for less allocs...
	bufp := poolBuf8k.Get()
	buf := *bufp
	defer poolBuf8k.Put(bufp)

	for {
		_, err := io.ReadFull(respBody, tmp[:])
		if err != nil {
			return err
		}
		// Check if we have a response ready or a filler byte.
		switch tmp[0] {

### Bug or Regression

have different security properties and provide different levels of confidence
when dealing with untrusted data. Based on the security history of these
libraries we consider that it is safe to work with untrusted inputs for PNG,
BMP, GIF, WAV, RAW, RAW\_PADDED, CSV and PROTO formats. All other input formats,
including tensorflow-io should be sandboxed if used to process untrusted data.

For example, if an attacker were to upload a malicious video file, they could

  /* image types */
  /**
   * <a href="https://en.wikipedia.org/wiki/BMP_file_format">Bitmap file format</a> ({@code bmp}
   * files).
   *
   * @since 13.0
   */
  public static final MediaType BMP = createConstant(IMAGE_TYPE, "bmp");

  /**
   * The <a href="https://en.wikipedia.org/wiki/Camera_Image_File_Format">Canon Image File