DB.Find(&user2, "id = ?", user.ID)
	DB.Model(&user2).Association("Pets").Find(&user2.Pets)
	CheckUser(t, user2, user)

	var pets []Pet
	DB.Model(&user).Where("name = ?", user.Pets[0].Name).Association("Pets").Find(&pets)

	if len(pets) != 1 {
		t.Fatalf("should only find one pets, but got %v", len(pets))
	}

	CheckPet(t, pets[0], *user.Pets[0])

### Memória por Processo

Agora, quando o programa carrega coisas na memória, por exemplo, um modelo de aprendizado de máquina em uma variável, ou o conteúdo de um arquivo grande em uma variável, tudo isso **consome um pouco da memória (RAM)** do servidor.

 * under the License.
 */
package org.apache.maven.model.inheritance;

import java.io.File;
import java.io.IOException;

import org.apache.maven.api.model.Model;
import org.apache.maven.model.building.SimpleProblemCollector;
import org.apache.maven.model.io.DefaultModelReader;
import org.apache.maven.model.io.DefaultModelWriter;
import org.apache.maven.model.io.ModelWriter;
import org.junit.jupiter.api.BeforeEach;

            model.buildTypes.map { it.name }
        )
    }

    @Test
    fun `promotion project has expected build types for other branches`() {
        val model = setupModelFor("release")

        assertEquals("Promotion", model.name)
        assertEquals(11, model.buildTypes.size)
        assertEquals(

    }

    public MaxCodePoint(String userFriendly) {
      value = decode(userFriendly);
    }
  }

  /**
   * The default values of maxCodePoint below provide pretty good performance models of different
   * kinds of common human text.
   *
   * @see MaxCodePoint#decode
   */
  @Param({"0x80", "0x90", "0x100", "0x800", "0x10000", "0x10ffff"})
  MaxCodePoint maxCodePoint;

  @Param({"16384"})

    }

    public MaxCodePoint(String userFriendly) {
      value = decode(userFriendly);
    }
  }

  /**
   * The default values of maxCodePoint below provide pretty good performance models of different
   * kinds of common human text.
   *
   * @see MaxCodePoint#decode
   */
  @Param({"0x80", "0x90", "0x100", "0x800", "0x10000", "0x10ffff"})
  MaxCodePoint maxCodePoint;

  @Param({"16384"})

public interface ModelUrlNormalizer {

    /**
     * Normalizes the well-known URLs of the specified model.
     *
     * @param model The model whose URLs should be normalized, may be {@code null}.
     * @param request The model building request that holds further settings, must not be {@code null}.
     */
    void normalize(Model model, ModelBuildingRequest request);

1)  Reference [TensorFlow Model Colab](https://colab.research.google.com/gist/ymodak/e96a4270b953201d5362c61c1e8b78aa/tensorflow-datasets.ipynb?authuser=1): Demonstrate how to build your TF model.

		{Name: "ID", DBName: "id", BindNames: []string{"Model", "ID"}, DataType: schema.Uint, PrimaryKey: true, Tag: `gorm:"primarykey"`, TagSettings: map[string]string{"PRIMARYKEY": "PRIMARYKEY"}, Size: 64, HasDefaultValue: true, AutoIncrement: true},
		{Name: "CreatedAt", DBName: "created_at", BindNames: []string{"Model", "CreatedAt"}, DataType: schema.Time},
		{Name: "UpdatedAt", DBName: "updated_at", BindNames: []string{"Model", "UpdatedAt"}, DataType: schema.Time},

import java.util.List;

import org.apache.maven.api.model.InputLocation;
import org.apache.maven.api.model.Model;

/**
 * Collects problems that are encountered during model building. The primary purpose of this component is to account for
 * the fact that the problem reporter has/should not have information about the calling context and hence cannot provide