return this;
    }

    /**
     * Gets the artifact filter that controls traversal of the dependency graph.
     *
     * @return The filter used to determine which of the artifacts in the dependency graph should be traversed or
     *         {@code null} to collect all transitive dependencies.
     */
    public ArtifactFilter getCollectionFilter() {

 * under the License.
 */
package org.apache.maven.repository.metadata;

/**
 * MetadataResolutionRequestTypeEnum
 */
@Deprecated
public enum MetadataResolutionRequestTypeEnum {
    tree(1),
    graph(2),
    classpathCompile(3),
    classpathTest(4),
    classpathRuntime(5),
    versionedGraph(6),
    scopedGraph(7);

    private int id;

    // Constructor

TF_CAPI_EXPORT extern TF_Buffer* TF_CreateRunOptions(
    unsigned char enable_full_trace);

// Returns the graph content in a human-readable format, with length set in
// `len`. The format is subject to change in the future.
// The returned string is heap-allocated, and caller should call free() on it.
TF_CAPI_EXPORT extern const char* TF_GraphDebugString(TF_Graph* graph,
                                                      size_t* len);

    "groups" : [ {
      "testProject" : "excludeRuleMergingBuild",
      "coverage" : {
        "per_commit" : [ "linux" ]
      }
    } ]
  }, {
    "testId" : "org.gradle.performance.regression.corefeature.LargeDependencyGraphPerformanceTest.resolve large dependency graph (parallel = false, locking = true)",
    "groups" : [ {

    have resulted in an error. When this happens, a noop is returned and the
    input tensors are marked non-feedable. In other words, if they are used as
    keys in `feed_dict` argument to `session.run()`, an error will be raised.
    Also, because some assert ops don't make it into the graph, the graph
    structure changes. A different graph can result in different per-op random

### Pydantic v1 y v2 en la misma app { #pydantic-v1-and-v2-on-the-same-app }

No está soportado por Pydantic tener un modelo de Pydantic v2 con sus propios campos definidos como modelos de Pydantic v1 o viceversa.

```mermaid
graph TB
    subgraph "❌ Not Supported"
        direction TB
        subgraph V2["Pydantic v2 Model"]
            V1Field["Pydantic v1 Model"]
        end
        subgraph V1["Pydantic v1 Model"]

    private record Key(MavenProject project, boolean transitive, boolean upstream) {}

    /**
     * Creates a new project dependency graph from the specified graph.
     *
     * @param projectDependencyGraph The project dependency graph to create a sub view from, must not be {@code null}.
     * @param whiteList The projects on which the dependency view should focus, must not be {@code null}.
     */

import org.eclipse.aether.graph.DependencyFilter;
import org.eclipse.aether.graph.DependencyNode;
import org.eclipse.aether.resolution.ArtifactResult;
import org.eclipse.aether.resolution.DependencyRequest;
import org.eclipse.aether.util.artifact.ArtifactIdUtils;
import org.eclipse.aether.util.graph.manager.DependencyManagerUtils;
import org.eclipse.aether.util.graph.visitor.DependencyGraphDumper;
import org.slf4j.Logger;

    private final Plugin plugin;

    public CycleDetectedInPluginGraphException(Plugin plugin, CycleDetectedInComponentGraphException e) {
        super("A cycle was detected in the component graph of the plugin: " + plugin.getArtifactId());

        this.plugin = plugin;
    }

    public Plugin getPlugin() {
        return plugin;
    }

 * resolving the version} and then downloading the file.</p>
 *
 * <p><dfn>Dependency collection</dfn> builds a graph of {@link org.apache.maven.api.Node} objects containing
 * all the dependencies.</p>
 *
 * <p>The <dfn>Dependency graph flattening</dfn> process in Maven reduces a complex,
 * multi-level dependency graph to a map of ordered lists that can be turned into classpaths.