}
        }
    }

    // ===================================================================================
    //                                                                           Query Set
    //                                                                           =========
    public void setId_Equal(String id) {
        setId_Term(id, null);
    }

        }
      }
    }
  }

  @GwtIncompatible // java.math.BigInteger
  public void testIsPowerOfTwo() {
    for (int x : ALL_INTEGER_CANDIDATES) {
      // Checks for a single bit set.
      BigInteger bigX = BigInteger.valueOf(x);
      boolean expected = (bigX.signum() > 0) && (bigX.bitCount() == 1);
      assertEquals(expected, IntMath.isPowerOfTwo(x));
    }
  }

     *
     * @return lmhosts file to use
     */
    String getLmHostsFileName();

    /**
     *
     * Property {@code jcifs.netbios.scope} (string)
     *
     * @return default netbios scope to set in requests
     */
    String getNetbiosScope();

    /**
     *
     * Property {@code jcifs.netbios.snd_buf_size} (int, default 576)
     *
     * @return netbios send buffer size
     */

		value := line[idx+1:]
		if _, ok := wantTrailers[key]; !ok {
			if cr.debug {
				fmt.Printf("%q not found in %q\n", key, cr.trailers)
			}
			return errMalformedEncoding
		}
		cr.trailers.Set(key, value)
		delete(wantTrailers, key)
	}

	// Check if we got all we want.
	if len(wantTrailers) > 0 {
		return io.ErrUnexpectedEOF
	}
	return nil
}

	// The first AutoMigrate to make table with field with correct type
	if err := DB.AutoMigrate(&MigrateInt{}); err != nil {
		t.Fatalf("Failed to auto migrate: error: %v", err)
	}

	// make new session to set custom logger tracer
	session := DB.Session(&gorm.Session{Logger: tracer})

	// The second AutoMigrate to catch an error
	if err := session.AutoMigrate(&MigrateInt{}); err != nil {

    // ===================================================================================
    //                                                                     Aggregation Set
    //                                                                           =========

    public void filter(String name, EsAbstractConditionQuery.OperatorCall<BsPathMappingCQ> queryLambda,

    // ===================================================================================
    //                                                                     Aggregation Set
    //                                                                           =========

    public void filter(String name, EsAbstractConditionQuery.OperatorCall<BsAccessTokenCQ> queryLambda,

    // ===================================================================================
    //                                                                     Aggregation Set
    //                                                                           =========

    public void filter(String name, EsAbstractConditionQuery.OperatorCall<BsJobLogCQ> queryLambda,

* **Deep Learning**: this is a sub-field of Machine Learning, so, the same applies. It's just that there is not a single spreadsheet of numbers to multiply, but a huge set of them, and in many cases, you use a special processor to build and / or use those models.

### Concurrency + Parallelism: Web + Machine Learning { #concurrency-parallelism-web-machine-learning }

**Itaniji gẹ́gẹ́ bí isọ'ye**: ìdánilẹ́kọ̀ọ́ - itọsọna olùmúlò pẹ̀lú:

* Ìkéde àṣàyàn **pàrámítà** láti àwọn oriṣiriṣi ibòmíràn gẹ́gẹ́ bíi: àwọn **àkọlé èsì API**, **kúkì**, **ààyè fọọmu**, àti **fáìlì**.
* Bíi ó ṣe lé ṣètò **àwọn ìdíwọ́ ìfọwọ́sí** bí `maximum_length` tàbí `regex`.
* Ó lágbára púpọ̀ ó sì rọrùn láti lo ètò **<abbr title="a tún mọ̀ sí ìrìnṣẹ́, àwọn ohun àmúlò iṣẹ́, olupese, àwọn ohun àfikún ">Àfikún Ìgbẹ́kẹ̀lé Kóòdù</abbr>**.