* under the License.
 */
package org.apache.maven.model.v4;

import javax.xml.stream.XMLStreamException;

import java.io.IOException;
import java.io.InputStream;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.List;
import java.util.concurrent.TimeUnit;
import java.util.stream.Collectors;

import org.apache.maven.api.model.InputSource;

 *
 * <h3>Upgrade Strategies</h3>
 * <p>The tool uses a strategy pattern to handle different types of upgrades:</p>
 * <ul>
 *   <li>{@link org.apache.maven.cling.invoker.mvnup.goals.ModelUpgradeStrategy} - Upgrades POM model versions (4.0.0 → 4.1.0)</li>
 *   <li>{@link org.apache.maven.cling.invoker.mvnup.goals.PluginUpgradeStrategy} - Upgrades plugin versions for Maven 4 compatibility</li>

        value: Union[str, Missing] = Missing()

    class Model(BaseModel):
        model_config = ConfigDict(
            arbitrary_types_allowed=True,
        )
        value: Union[str, Missing] = Missing()
        embedded_model: EmbeddedModel = EmbeddedModel()

    @app.post("/")
    def foo(req: Model) -> dict[str, Union[str, None]]:
        return {
            "value": req.value or None,

### Arbeitsspeicher pro Prozess { #memory-per-process }

Wenn das Programm nun Dinge in den Arbeitsspeicher lädt, zum Beispiel ein Modell für maschinelles Lernen in einer Variablen oder den Inhalt einer großen Datei in einer Variablen, verbraucht das alles **einen Teil des Arbeitsspeichers (RAM – Random Access Memory)** des Servers.

       * 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).
   

import org.apache.maven.impl.InternalSession;
import org.apache.maven.impl.cache.DefaultRequestCacheFactory;
import org.apache.maven.internal.impl.DefaultSession;
import org.apache.maven.model.Dependency;
import org.apache.maven.model.Repository;
import org.apache.maven.model.RepositoryPolicy;
import org.apache.maven.plugin.LegacySupport;
import org.apache.maven.project.artifact.DefaultMetadataSource;

				t.Fatalf("errors happened when query: %v", err)
			} else {
				CheckUser(t, newUser, user)
			}
		}
	}
}

func TestCreateFromMap(t *testing.T) {
	if err := DB.Model(&User{}).Create(map[string]interface{}{"Name": "create_from_map", "Age": 18}).Error; err != nil {
		t.Fatalf("failed to create data from map, got error: %v", err)
	}

	var result User

specific language governing permissions and limitations
under the License.
-->

<model xmlns="http://modello.codehaus.org/MODELLO/1.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://modello.codehaus.org/MODELLO/1.0.0 http://modello.codehaus.org/xsd/modello-1.0.0.xsd"
  xml.namespace="http://maven.apache.org/PARAMDOC/${version}"

import io.mockk.mockk
import io.mockk.slot
import jetbrains.buildServer.configs.kotlin.BuildStep
import jetbrains.buildServer.configs.kotlin.BuildSteps
import jetbrains.buildServer.configs.kotlin.DslContext
import model.CIBuildModel
import model.JsonBasedGradleSubprojectProvider
import org.junit.jupiter.api.Assertions.assertEquals
import org.junit.jupiter.api.BeforeEach
import org.junit.jupiter.api.Test
import org.junit.jupiter.api.extension.ExtendWith

import org.gradle.api.tasks.PathSensitivity
import org.gradle.api.tasks.TaskAction
import gradlebuild.docs.dsl.links.ClassLinkMetaData
import gradlebuild.docs.dsl.links.LinkMetaData
import gradlebuild.docs.model.ClassMetaDataRepository
import gradlebuild.docs.model.SimpleClassMetaDataRepository
import org.w3c.dom.Document
import org.w3c.dom.Element
/**
 * Transforms userguide source into docbook, replacing custom XML elements.
 *