import org.apache.maven.artifact.repository.ArtifactRepository;
import org.apache.maven.artifact.repository.ArtifactRepositoryFactory;
import org.apache.maven.model.DeploymentRepository;
import org.apache.maven.model.Repository;
import org.apache.maven.plugin.LegacySupport;
import org.apache.maven.repository.RepositorySystem;
import org.codehaus.plexus.PlexusContainer;

    // ----------------------------------------------------------------------
    //
    // p1 inherits from p0
    // p0 inherits from super model
    //
    // or we can show it graphically as:
    //
    // p1 ---> p0 --> super model
    //
    // ----------------------------------------------------------------------

    @Test
    void testDependencyManagement() throws Exception {

    // ----------------------------------------------------------------------
    //
    // p1 inherits from p0
    // p0 inherits from super model
    //
    // or we can show it graphically as:
    //
    // p1 ---> p0 --> super model
    //
    // ----------------------------------------------------------------------

    @Test

    /**
     * Convert a model profile to a settings profile.
     */
    @Nonnull
    org.apache.maven.api.settings.Profile convert(@Nonnull org.apache.maven.api.model.Profile profile);

    /**
     * Convert a settings profile to a model profile.
     */
    @Nonnull
    org.apache.maven.api.model.Profile convert(@Nonnull org.apache.maven.api.settings.Profile profile);

 * from a Project Object Model (POM).</p>
 *
 * <p><dfn>Project Object Model</dfn> or <dfn>POM</dfn> refers to the information describing
 * all the information needed to build or consume a project. Those are usually loaded from
 * a file named {@code pom.xml} and loaded into a {@link org.apache.maven.api.model.Model Model}
 * instances.</p>
 *

       * Refer [linux setup guide](https://www.tensorflow.org/install/gpu#linux_setup).
     * If error still persists then, apparently your CPU model does not support AVX instruction sets.
       * Refer [hardware requirements](https://www.tensorflow.org/install/pip#hardware-requirements).
   

			}
		},
	}
	session := DB.Session(&gorm.Session{Logger: tracer})

	DB.Migrator().DropTable(model1)
	var modifySql []string
	if err := session.AutoMigrate(model1); err != nil {
		t.Fatalf("failed to auto migrate, got error: %v", err)
	}
	if err := session.AutoMigrate(model1); err != nil {
		t.Fatalf("failed to auto migrate, got error: %v", err)
	}
	tracer2 := Tracer{

import javax.annotation.processing.SupportedAnnotationTypes;
import javax.annotation.processing.SupportedSourceVersion;
import javax.lang.model.SourceVersion;
import javax.lang.model.element.Element;
import javax.lang.model.element.PackageElement;
import javax.lang.model.element.TypeElement;
import javax.tools.Diagnostic;
import javax.tools.FileObject;
import javax.tools.StandardLocation;

import java.io.BufferedReader;

                public org.apache.maven.api.Toolchain createToolchain(
                        @Nonnull org.apache.maven.api.toolchain.ToolchainModel model) throws ToolchainFactoryException {
                    try {
                        return getToolchainV4(v3Factory.createToolchain(new ToolchainModel(model)));
                    } catch (MisconfiguredToolchainException e) {
                        throw new RuntimeException(e);
                    }

		AssertObjEqual(t, results[idx], expect, "Name", "Age")
	}

	var count int64
	if err := DB.Model(&User{}).Where("name like ?", "distinct%").Count(&count).Error; err != nil || count != 5 {
		t.Errorf("failed to query users count, got error: %v, count: %v", err, count)
	}

	if err := DB.Model(&User{}).Distinct("name").Where("name like ?", "distinct%").Count(&count).Error; err != nil || count != 3 {