void getArtifact(Artifact artifact, ArtifactRepository repository)
            throws TransferFailedException, ResourceDoesNotExistException;

    void getArtifact(Artifact artifact, List<ArtifactRepository> remoteRepositories)
            throws TransferFailedException, ResourceDoesNotExistException;

    ArtifactRepository getMirrorRepository(ArtifactRepository repository);

     * @param finalName the name of the artifact without extension
     * @param artifact the artifact definition
     * @param deploymentRepository the repository to deploy to
     * @param localRepository the local repository to install into
     * @throws ArtifactDeploymentException if an error occurred deploying the artifact
     * @deprecated to be removed before 2.0 after the install/deploy plugins use the alternate

    }

    /**
     * Updates the git repository from the specified remote
     * @param remote the remote to use to update
     */
    public void updateRemote(String remote) {
        runCommand("git", "fetch", Objects.requireNonNull(remote));
    }

    /**
     * Updates the git repository's tags from the specified remote
     * @param remote the remote to use to update
     */

     * @throws ArtifactDeployerException if the deployment failed
     */
    void deploy(@Nonnull ArtifactDeployerRequest request);

    /**
     * @param session the repository session
     * @param repository the repository to deploy to
     * @param artifacts the collection of artifacts to deploy
     * @throws ArtifactDeployerException if the deployment failed

    private List<ArtifactRepository> remoteRepositories;

    /**
     * Creates an empty repository request.
     */
    public DefaultRepositoryRequest() {
        // enables no-arg constructor
    }

    /**
     * Creates a shallow copy of the specified repository request.
     *
     * @param repositoryRequest The repository request to copy from, must not be {@code null}.
     */

# Initialize the TensorFlow repository and all dependencies.
#
# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.
load("@//tensorflow:workspace3.bzl", "tf_workspace3")

import org.apache.maven.internal.impl.DefaultSessionFactory;
import org.apache.maven.plugin.LegacySupport;
import org.apache.maven.repository.internal.artifact.FatArtifactTraverser;
import org.apache.maven.repository.internal.scopes.Maven4ScopeManagerConfiguration;
import org.apache.maven.repository.legacy.repository.ArtifactRepositoryFactory;
import org.apache.maven.rtinfo.RuntimeInformation;
import org.codehaus.plexus.PlexusContainer;

### Creating the Scale-out Backup Repository

- Under the Backup Infrastructure view, click on Scale-out Repositories and click the Add Scale-out Repository button on the ribbon.

- Follow the on screen wizard

 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.repository;

/**
 * Describes a resource being uploaded or downloaded by the repository system.
 *
 */
@Deprecated
public interface ArtifactTransferResource {

    /**
     * The base URL of the repository, e.g. "http://repo1.maven.org/maven2/". Unless the URL is unknown, it will be
     * terminated by a trailing slash.

 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.artifact.repository;

/**
 * Caches auxiliary data used during repository access like already processed metadata. The data in the cache is meant
 * for exclusive consumption by the repository system and is opaque to the cache implementation.
 *
 */
@Deprecated
//