}

		sql = newSQL.String()
	} else {
		sql = numericPlaceholder.ReplaceAllString(sql, "$$$1$$")

		sql = numericPlaceholderRe.ReplaceAllStringFunc(sql, func(v string) string {
			num := v[1 : len(v)-1]
			n, _ := strconv.Atoi(num)

			// position var start from 1 ($1, $2)
			n -= 1
			if n >= 0 && n <= len(vars)-1 {
				return vars[n]
			}
			return v
		})
	}

	return sql

        Map<String, Object> searchBody = new HashMap<>();
        searchBody.put("size", NUM * 2);
        String response = checkGetMethod(searchBody, getListEndpointSuffix()).asString();
        List<Map<String, String>> attrList = JsonPath.from(response).getList(getJsonPath() + ".attributes");
        assertEquals(NUM, attrList.size());
        for (Map<String, String> attr : attrList) {

                    int num = Integer.parseInt(expression.substring(2, expression.length() - 1));
                    filters.add(new HighestVersionFilter(num));
                } else if ("l".equals(expression)) {
                    filters.add(new LowestVersionFilter());
                } else if (expression.startsWith("l(") && expression.endsWith(")")) {

    StringBuilder sb2 = new StringBuilder().append('x');
    joiner.appendTo(sb2, partsArray);
    assertEquals("x" + expected, sb2.toString());

    int num = partsArray.length - 2;
    if (num >= 0) {
      Object[] rest = new Integer[num];
      for (int i = 0; i < num; i++) {
        rest[i] = partsArray[i + 2];
      }

      assertEquals(expected, joiner.join(partsArray[0], partsArray[1], rest));

  return new TF_VariableInfo(index, handle.name(), variable);
}

void TF_LockVariableInfos(TF_VariableInfo** vars, int num_vars,
                          TF_Status* status) {
  std::vector<tensorflow::VariableInfo*> variable_ptrs;
  variable_ptrs.reserve(num_vars);
  for (int i = 0; i < num_vars; ++i) {
    variable_ptrs.push_back(&(vars[i]->var_info));
  }

public class ThumbnailForm {

    @Required
    @Size(max = 100)
    public String docId;

    @Required
    public String queryId;

    // for error page

    public String q;

    public String num;

    public String sort;

    public String lang;

    public Map<String, String[]> fields = new HashMap<>();

    public String rt;

    public String hash;

    @Required
    public String queryId;

    public Integer order;

    // for error page

    public String q;

    public String num;

    public String sort;

    public String lang;

    public Map<String, String[]> fields = new HashMap<>();

}

TF_Tensor* TFE_AllocateHostTensor(TFE_Context* ctx, TF_DataType dtype,
                                  const int64_t* dims, int num_dims,
                                  TF_Status* status) {
  std::vector<int64_t> dimvec(num_dims);
  for (int i = 0; i < num_dims; ++i) {
    dimvec[i] = static_cast<int64_t>(dims[i]);
  }

  if (ctx == nullptr) {

            // num of threads
            final CrawlerContext crawlerContext = crawler.getCrawlerContext();
            final int numOfThread =
                    webConfig.getNumOfThread() != null ? webConfig.getNumOfThread() : Constants.DEFAULT_NUM_OF_THREAD_FOR_WEB;
            crawlerContext.setNumOfThread(numOfThread);

            // depth

// 0 for num_options if no options need to be set. You can use
// ConvertToPjRtNamedValueList in
// tensorflow/compiler/xla/pjrt/c/pjrt_c_api_helpers.h to generate the options.
TF_CAPI_EXPORT extern void TF_CreateAndSetPjRtCApiClient(
    const char* device_type, TF_Status* status, PJRT_NamedValue* create_options,
    int num_options);