{% endif %}

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## Opiniones

"_[...] Estoy usando **FastAPI** un montón estos días. [...] De hecho, estoy planeando usarlo para todos los servicios de **ML de mi equipo en Microsoft**. Algunos de ellos se están integrando en el núcleo del producto **Windows** y algunos productos de **Office**._"

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## Opiniões

"*[...] Estou usando **FastAPI** muito esses dias. [...] Estou na verdade planejando utilizar ele em todos os times de **serviços _Machine Learning_ na Microsoft**. Alguns deles estão sendo integrados no _core_ do produto **Windows** e alguns produtos **Office**.*"

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

    std::vector<DimensionHandle> dims;
    const TF_ShapeAndType& input_shape = input_shapes->items[i];
    if (input_shape.num_dims == InferenceContext::kUnknownRank) {
      c.SetInput(i, c.UnknownShape());
      continue;
    }
    dims.reserve(input_shape.num_dims);
    for (int j = 0; j < input_shape.num_dims; ++j) {
      dims.push_back(c.MakeDim(input_shape.dims[j]));
    }
    c.SetInput(i, c.MakeShape(dims));

    int num_dims = output_shapes->items[0].num_dims;
    int64_t* dims = output_shapes->items[0].dims;

    if (!expected_shape.has_value()) {
      EXPECT_EQ(num_dims, -1);
      EXPECT_EQ(dims, nullptr);
      return;
    }

    EXPECT_EQ(num_dims, expected_shape->size());
    for (size_t i = 0; i < num_dims; ++i) {
      EXPECT_EQ(dims[i], (*expected_shape)[i]);
    }

TF_CAPI_EXPORT extern TF_DataType TF_CheckpointReaderGetVariableDataType(
    TF_CheckpointReader* reader, const char* name);
// Read the shape of a variable and write to `dims`
TF_CAPI_EXPORT extern void TF_CheckpointReaderGetVariableShape(
    TF_CheckpointReader* reader, const char* name, int64_t* dims, int num_dims,
    TF_Status* status);
// Get the number of dimension of a variable
TF_CAPI_EXPORT extern int TF_CheckpointReaderGetVariableNumDims(

* `summary`: Kurze Beschreibung für das Beispiel.
* `description`: Eine lange Beschreibung, die Markdown-Text enthalten kann.
* `value`: Dies ist das tatsächlich angezeigte Beispiel, z. B. ein `dict`.
* `externalValue`: Alternative zu `value`, eine URL, die auf das Beispiel verweist. Allerdings wird dies möglicherweise nicht von so vielen Tools unterstützt wie `value`.

Sie können es so verwenden:

* gehe zum übergeordneten Package (das Verzeichnis `app/`) ...
* und finde dort das Modul `dependencies` (die Datei unter `app/dependencies.py`) ...
* und importiere daraus die Funktion `get_token_header`.

Das funktioniert korrekt! 🎉

---

Das Gleiche gilt, wenn wir drei Punkte `...` verwendet hätten, wie in:

            public long purge(long expiry) {
                baseDir = tempDir;
                // Count expired files
                int count = 0;
                File[] dirs = baseDir.listFiles();
                if (dirs != null) {
                    for (File dir : dirs) {
                        if (dir.isDirectory() && dir.getName().startsWith("_")) {
                            count++;
                        }
                    }