if (getContainer().hasComponent(ProjectBuilder.class, "test")) {
            projectBuilder = getContainer().lookup(ProjectBuilder.class, "test");
        } else {
            // default over to the main project builder...
            projectBuilder = getContainer().lookup(ProjectBuilder.class);
        }
    }

    protected ProjectBuilder getProjectBuilder() {
        return projectBuilder;
    }

}

void TF_DeleteAttrBuilder(TF_AttrBuilder* builder) { delete builder; }

void TF_AttrBuilderSetType(TF_AttrBuilder* builder, const char* attr_name,
                           TF_DataType value) {
  auto iter = builder->attr_names.insert(attr_name).first;
  builder->Set(*iter, static_cast<tensorflow::DataType>(value));
}

void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,

 * </ul>
 *
 * The service maintains the mutable state of projects as they progress through
 * their build lifecycle, ensuring thread-safety and proper state management.
 * All implementations must be thread-safe as they may be accessed concurrently
 * during parallel builds.
 *
 * @since 4.0.0
 * @see org.apache.maven.api.services.ProjectBuilder
 * @see Project
 */
@Experimental

     * Gets the actual version string for a SNAPSHOT artifact by parsing the snapshot metadata.
     *
     * @param builder the document builder to use for parsing XML
     * @param pluginUrl the URL of the plugin
     * @param version the snapshot version
     * @return the actual version string with timestamp and build number, or null if not found
     * @throws SAXException if XML parsing fails
     * @throws IOException if I/O error occurs

 * Defines the contract for a component responsible for invoking a Maven application
 * using the information provided in an {@link InvokerRequest}. This interface is central
 * to the construction and invocation of Maven commands and builds, and it fully parses arguments.
 *
 * <p>The Invoker is designed to be flexible, allowing for different implementations
 * that can handle various types of {@link InvokerRequest InvokerRequests}. It also implements

  public void run() throws Exception {
    final PipeBody pipeBody = new PipeBody();

    Request request = new Request.Builder()
        .url("https://api.github.com/markdown/raw")
        .post(pipeBody)
        .build();

    streamPrimesToSinkAsynchronously(pipeBody.sink());

    try (Response response = client.newCall(request).execute()) {

      buffer.writeByte('='.code)
      buffer.writeUtf8(encodedValues[i])
    }

    if (countBytes) {
      byteCount = buffer.size
      buffer.clear()
    }

    return byteCount
  }

  class Builder
    @JvmOverloads
    constructor(
      private val charset: Charset? = null,
    ) {
      private val names = mutableListOf<String>()
      private val values = mutableListOf<String>()

      fun add(

#### Debug builds

When [building Tensorflow](https://www.tensorflow.org/install/source), passing
`--config=dbg` to Bazel will build with debugging information and without
optimizations, allowing you to use GDB or other debuggers to debug C++ code. For
example, you can build the pip package with debugging information by running:

```bash

    abstract Type usedInGenericType(Type type);

    final ImmutableList<Type> usedInGenericType(Type[] types) {
      ImmutableList.Builder<Type> builder = ImmutableList.builder();
      for (Type type : types) {
        builder.add(usedInGenericType(type));
      }
      return builder.build();
    }

    String typeName(Type type) {
      return Types.toString(type);
    }

There is also an **Advanced User Guide** that you can read later after this **Tutorial - User guide**.

The **Advanced User Guide** builds on this one, uses the same concepts, and teaches you some extra features.

But you should first read the **Tutorial - User Guide** (what you are reading right now).