int start = di, ch;
        int strlen = str.length();

        for ( int i = 0; di < dlim && i < strlen; i++ ) {
            ch = str.charAt(i);
            if ( ( ch >= 0x0001 ) && ( ch <= 0x007F ) ) {
                dst[ di++ ] = (byte) ch;
            }
            else if ( ch > 0x07FF ) {
                if ( ( dlim - di ) < 3 ) {
                    break;

        int start = di, ch;
        int strlen = str.length();

        for( int i = 0; di < dlim && i < strlen; i++ ) {
            ch = str.charAt( i );
            if ((ch >= 0x0001) && (ch <= 0x007F)) {
                dst[di++] = (byte)ch;
            } else if (ch > 0x07FF) {
                if((dlim - di) < 3 ) {
                    break;

// [Reader.ReadBytes] or ReadString instead.
// ReadSlice returns err != nil if and only if line does not end in delim.
func (b *Reader) ReadSlice(delim byte) (line []byte, err error) {
	s := 0 // search start index
	for {
		// Search buffer.
		if i := bytes.IndexByte(b.buf[b.r+s:b.w], delim); i >= 0 {
			i += s
			line = b.buf[b.r : b.r+i+1]
			b.r += i + 1
			break
		}

		// Pending error?

// ReadBytes reads until the first occurrence of delim in the input,
// returning a slice containing the data up to and including the delimiter.
// If ReadBytes encounters an error before finding a delimiter,
// it returns the data read before the error and the error itself (often [io.EOF]).
// ReadBytes returns err != nil if and only if the returned data does not end in
// delim.
func (b *Buffer) ReadBytes(delim byte) (line []byte, err error) {

     * value containting a <tt>delim</tt> separated list of hostnames and/or
     * ipaddresses.
     */

    public static InetAddress[] getInetAddressArray( String key, String delim, InetAddress[] def ) {
        String p = getProperty( key );
        if( p != null ) {
            StringTokenizer tok = new StringTokenizer( p, delim );
            int len = tok.countTokens();

  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return -1;
  }

  int64_t dim = -1;
  status->status = tensorflow::unwrap(h)->Dim(dim_index, &dim);
  return dim;
}

const char* TFE_TensorHandleDeviceName(TFE_TensorHandle* h, TF_Status* status) {
  if (h == nullptr) {

	lim := event.NewerNoncurrentVersions
	if lim == 0 || len(fivs) <= lim+1 { // fewer than lim _noncurrent_ versions
		for _, fi := range fivs {
			objectInfos = append(objectInfos, fi.ToObjectInfo(i.bucket, i.objectPath(), versioned))
		}
		return objectInfos, nil
	}

	overflowVersions := fivs[lim+1:]

     *            文字列
     * @param delim
     *            分割するためのデリミタ
     * @return 分割された文字列の配列
     */
    public static String[] split(final String str, final String delim) {
        if (isEmpty(str)) {
            return EMPTY_STRINGS;
        }
        final List<String> list = newArrayList();
        final StringTokenizer st = new StringTokenizer(str, delim);
        while (st.hasMoreElements()) {

`,
			totalFields: 308*2 + 1,
		}, {
			file:            "nyc-taxi-data-100k-single-delim.csv",
			recordDelimiter: "^",
			fieldDelimiter:  ",",
			header:          true,

      0;  // TF doesn't handle the strides and byte_offsets here
  return static_cast<void*>(dlm_tensor);
}

TFE_TensorHandle* TFE_HandleFromDLPack(void* dlm, TF_Status* status,
                                       TFE_Context* ctx) {
  DLManagedTensor* dlmt = static_cast<DLManagedTensor*>(dlm);
  DLTensor* dl_tensor = &dlmt->dl_tensor;
  absl::optional<std::string> device_name =
      DeviceNameFromDlContext(dl_tensor->device, status);