// parallel device.
        device_(device),
        executor_(
            TFE_NewExecutor(is_async, /*enable_streaming_enqueue=*/true,
                            /*in_flight_nodes_limit=*/in_flight_nodes_limit)),
        op_(nullptr),
        thread_(tensorflow::Env::Default()->StartThread(
            tensorflow::ThreadOptions(), "parallel_device_execute",
            std::bind(&DeviceThread::Run, this))) {}

        rnd.nextBytes(left);
        byte[] right = left.clone();
        assertThat(comparator.compare(left, right)).isEqualTo(0);
        int i = rnd.nextInt(left.length);
        left[i] ^= (byte) (1 + rnd.nextInt(255));
        assertThat(comparator.compare(left, right)).isNotEqualTo(0);
        assertThat(UnsignedBytes.compare(left[i], right[i]) > 0)
            .isEqualTo(comparator.compare(left, right) > 0);
      }
    }
  }

      @Override
      public int compare(byte[] left, byte[] right) {
        int minLength = Math.min(left.length, right.length);
        for (int i = 0; i < minLength; i++) {
          int result = UnsignedBytes.compare(left[i], right[i]);
          if (result != 0) {
            return result;
          }
        }
        return left.length - right.length;
      }

      @Override

                                </div>
                                <div class="form-group row">
                                    <label for="name" class="col-sm-3 text-sm-right col-form-label"><la:message
                                            key="labels.name"/></label>
                                    <div class="col-sm-9">
                                        <la:errors property="name"/>

                            </div>
                            <div class="card-body">
                                <div class="form-group row">
                                    <span class="font-weight-bold col-sm-3 text-sm-right col-form-label"><la:message
                                            key="labels.replace_aliases"/></span>
                                    <div class="form-inline col-sm-9">

                    <mxGeometry x="-60" y="-540" width="330" height="260" as="geometry"/>
                </mxCell>
                <mxCell id="6" value="" style="rounded=0;whiteSpace=wrap;html=1;fontStyle=1;strokeWidth=4;fillColor=#dae8fc;strokeColor=#6c8ebf;" parent="1" vertex="1">
                    <mxGeometry x="495" y="320" width="355" height="440" as="geometry"/>
                </mxCell>

<div style="text-align: right; margin-right: 10%;">কবির খান - <strong>মাইক্রোসফ্টে</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

---

"_আমরা **FastAPI** লাইব্রেরি গ্রহণ করেছি একটি **REST** সার্ভার তৈরি করতে, যা **ভবিষ্যদ্বাণী** পাওয়ার জন্য কুয়েরি করা যেতে পারে। [লুডউইগের জন্য]_"

<div style="text-align: right; margin-right: 10%;">Kevin Glisson, Marc Vilanova, Forest Monsen - <strong>Netflix</strong> <a href="https://netflixtechblog.com/introducing-dispatch-da4b8a2a8072" target="_blank"><small>(Ref)</small></a></div>

---

„_Ich bin überglücklich mit **FastAPI**. Es macht so viel Spaß!_“

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

---

"_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_"

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

---

"_我們使用 **FastAPI** 來建立產生**預測**結果的 **REST** 伺服器。 [for Ludwig]_"