labels.searchlog_log_type_search_count_day=Número de búsquedas/día
labels.searchlog_log_type_search_user_hour=Número de usuarios/hora
labels.searchlog_log_type_search_user_day=Número de usuarios/día
labels.searchlog_log_type_search_reqtimeavg_hour=Tiempo medio de solicitud/hora
labels.searchlog_log_type_search_reqtimeavg_day=Tiempo medio de solicitud/día
labels.searchlog_log_type_click_count=Número de clics

labels.searchlog_log_type_search_count_day=Número de pesquisas/dia
labels.searchlog_log_type_search_user_hour=Número de usuários/hora
labels.searchlog_log_type_search_user_day=Número de usuários/dia
labels.searchlog_log_type_search_reqtimeavg_hour=Tempo médio de solicitação/hora
labels.searchlog_log_type_search_reqtimeavg_day=Tempo médio de solicitação/dia
labels.searchlog_log_type_click_count=Número de cliques

// Returns the shape of the Tensor referenced by `output` in `graph`
// into `dims`. `dims` must be an array large enough to hold `num_dims`
// entries (e.g., the return value of TF_GraphGetTensorNumDims).
//
// If the number of dimensions in the shape is unknown or the shape is
// a scalar, `dims` will remain untouched. Otherwise, each element of
// `dims` will be set corresponding to the size of the dimension. An

  const int num_dims = 2;
  int64_t* dims = new int64_t[num_dims];
  int64_t num_elements = 1;
  dims[0] = batch_size;
  dims[1] = 1;
  for (int64_t i = 0; i < num_dims; ++i) {
    num_elements *= dims[i];
  }
  TF_Tensor* t = TF_AllocateTensor(TF_STRING, dims, num_dims,
                                   sizeof(TF_TString) * num_elements);
  delete[] dims;

	}

	// Nothing to delete
	if len(foundDirs) == 0 {
		return nil
	}

	// Delete excessive inline entries.
	// Convert to slice.
	dirs = dirs[:0]
	for dir := range foundDirs {
		dirs = append(dirs, dir)
	}
	if xl.data.remove(dirs...) {
		newBuf, err := xl.AppendTo(metaDataPoolGet())
		if err == nil {
			defer metaDataPoolPut(newBuf)

  TFE_DeleteContextOptions(opts);

  std::vector<int64_t> dims(4, 1);
  TFE_Op* op = TFE_NewOp(ctx, "AvgPool", status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  TF_Tensor* tensor =
      TF_AllocateTensor(TF_FLOAT, dims.data(), dims.size(), sizeof(float));
  float tensor_data[] = {1};

  url: https://github.com/hackerneocom
dmas-at-wiris:
  login: dmas-at-wiris
  count: 2
  avatarUrl: https://avatars.githubusercontent.com/u/24917162?u=0df147936a375b4b64232c650de31a227a6b59a0&v=4
  url: https://github.com/dmas-at-wiris
TorhamDev:
  login: TorhamDev
  count: 2

labels.depth=Tiefe
labels.excludedPaths=Ausgeschlossene Pfade für das Crawling
labels.excludedUrls=Ausgeschlossene URLs für das Crawling
labels.excludedDocPaths=Ausgeschlossene Pfade für die Suche
labels.excludedDocUrls=Ausgeschlossene URLs für die Suche
labels.hostname=Hostname
labels.id=ID
labels.includedPaths=Eingeschlossene Pfade für das Crawling
labels.includedUrls=Eingeschlossene URLs für das Crawling

* Increase request timeout based on termination grace period ([#31275](https://github.com/kubernetes/kubernetes/pull/31275), [@dims](https://github.com/dims))
* Skip safe to detach check if node API object no longer exists ([#30737](https://github.com/kubernetes/kubernetes/pull/30737), [@saad-ali](https://github.com/saad-ali))