* `--reload`: kod dəyişikliyindən sonra avtomatik olaraq serveri yenidən işə salır. Bu parametrdən yalnız development mərhələsində istifadə etməliyik.

</details>

### İndi yoxlayaq

Bu linki brauzerimizdə açaq <a href="http://127.0.0.1:8000/items/5?q=somequery" class="external-link" target="_blank">http://127.0.0.1:8000/items/5?q=somequery</a>.

Aşağıdakı kimi bir JSON cavabı görəcəksiniz:

        return entries;
      }
      @SuppressWarnings({"rawtypes", "unchecked"})
      Entry<K, V>[] newEntries = new Entry[size - dups.cardinality()];
      for (int inI = 0, outI = 0; inI < size; inI++) {
        if (!dups.get(inI)) {
          newEntries[outI++] = entries[inI];
        }
      }
      return newEntries;
    }
  }

  /**

      for (int inI = 0, outI = 0; inI < size * 2; ) {
        if (dups.get(inI >>> 1)) {
          inI += 2;
        } else {
          newAlternatingKeysAndValues[outI++] =
              requireNonNull(localAlternatingKeysAndValues[inI++]);
          newAlternatingKeysAndValues[outI++] =
              requireNonNull(localAlternatingKeysAndValues[inI++]);
        }
      }

Możesz "dodać gwiazdkę" FastAPI na GitHubie (klikając przycisk gwiazdki w prawym górnym rogu): <a href="https://github.com/tiangolo/fastapi" class="external-link" target="_blank">https://github.com/tiangolo/fastapi</a>. ⭐️

Dodając gwiazdkę, inni użytkownicy będą mogli łatwiej znaleźć projekt i zobaczyć, że był już przydatny dla innych.

## Obserwuj repozytorium GitHub w poszukiwaniu nowych wydań

* Èyí tí àwọn _ipa ọ̀nà_ (i.e. _paths_) méjèèjì gbà àwọn iṣẹ `GET` (a tun mọ si _àwọn ọna_ HTTP).
* Èyí tí _ipa ọ̀nà_  (i.e. _paths_) `/items/{item_id}` ní _àwọn ohun-ini ipa ọ̀nà_ tí ó yẹ kí ó jẹ́ `int` i.e. `ÒǸKÀ`.
* Èyí tí _ipa ọ̀nà_  (i.e. _paths_) `/items/{item_id}` ní àṣàyàn `str` _àwọn ohun-ini_ (i.e. _query parameter_) `q`.

### Ìbáṣepọ̀ àkọsílẹ̀ API

              << session->graph->graph.ToGraphDefDebug().DebugString();
      tensorflow::Tensor internal_tensor;
      if (tensorflow::TF_TensorToTensor(tensor, &internal_tensor).ok()) {
        VLOG(1) << "Enqueu'ing tensor content: "
                << internal_tensor.DebugString();
      }
    }
  }

  TF_Operation* enqueue_op = TF_GraphOperationByName(
      session->graph,

{% endfor %}
{% endif %}

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    }
  }

  // Tell the forward accumulator to watch tensor_id, with a Tensor tangent
  // vector `tangent` of matching shape and dtype. Tangents are the "vector" in
  // "Jacobian-vector product"; `Watch`ing a new Tensor and immediately calling
  // FetchJVP for it would return `tangent`.
  void Watch(int64_t tensor_id, Gradient* tangent);

  // Removes the gradient associated with tensor_id. Should be called when the

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