### Конкурентность + параллелизм: Веб + Машинное обучение { #concurrency-parallelism-web-machine-learning }

С **FastAPI** вы можете использовать преимущества конкурентности, что очень распространено в веб-разработке (это та же основная «фишка» NodeJS).

### Serverspeicher { #server-memory }

### Eşzamanlılık + Paralellik: Web + Makine Öğrenimi { #concurrency-parallelism-web-machine-learning }

**FastAPI** ile web geliştirmede çok yaygın olan eşzamanlılıktan (NodeJS’in başlıca cazibesiyle aynı) yararlanabilirsiniz.

under Section 2) in object code or executable form under the terms of
Sections 1 and 2 above provided that you also do one of the following:

    a) Accompany it with the complete corresponding machine-readable
    source code, which must be distributed under the terms of Sections 1
    and 2 above on a medium customarily used for software interchange; or,

    b) Accompany it with a written offer, valid for at least three

### Concorrência + Paralelismo: Web + Aprendizado de Máquina { #concurrency-parallelism-web-machine-learning }

Com **FastAPI** você pode levar a vantagem da concorrência que é muito comum para desenvolvimento web (o mesmo atrativo de NodeJS).

### Рівночасність + паралелізм: веб + машинне навчання { #concurrency-parallelism-web-machine-learning }

З **FastAPI** ви можете скористатися рівночасністю, що дуже поширена у веброзробці (та ж головна принада NodeJS).

# Description:
# TensorFlow is a computational framework, primarily for use in machine
# learning applications.

load("@rules_cc//cc:cc_import.bzl", "cc_import")

# buildifier: disable=out-of-order-load
# copybara:comment_begin(oss-only)
load("//tensorflow:strict.default.bzl", "py_strict_library")

# copybara:comment_end
# buildifier: enable=out-of-order-load
load("@bazel_skylib//lib:selects.bzl", "selects")

    }
  }


  @J2ktIncompatible // slow enough to cause flakiness
  @GwtIncompatible // far too slow
  public void testSqrtOfPerfectSquareAsDoubleIsPerfect() {
    // This takes just over a minute on my machine.
    for (long n = 0; n <= LongMath.FLOOR_SQRT_MAX_LONG; n++) {
      long actual = (long) Math.sqrt((double) (n * n));
      assertTrue(actual == n);
    }
  }

   *
   * @since 8.0
   */
  public static final byte NUL = 0;

  /**
   * Start of Heading: A communication control character used at the beginning of a sequence of
   * characters which constitute a machine-sensible address or routing information. Such a sequence
   * is referred to as the "heading." An STX character has the effect of terminating a heading.
   *
   * @since 8.0
   */
  public static final byte SOH = 1;

Si tu aplicación es **simple**, probablemente esto **no será un problema**, y puede que no necesites especificar límites de memoria estrictos. Pero si estás **usando mucha memoria** (por ejemplo, con modelos de **Machine Learning**), deberías verificar cuánta memoria estás consumiendo y ajustar el **número de contenedores** que se ejecutan en **cada máquina** (y tal vez agregar más máquinas a tu cluster).