* <li><dfn>Third-Party Repositories</dfn>: Some projects or organizations host their own remote repositories for distributing specific artifacts that are not available in the central repository. These repositories must be explicitly added to the Maven pom.xml...

            Artifact artifact, ArtifactRepository localRepository, List<ArtifactRepository> remoteRepositories)
            throws ArtifactMetadataRetrievalException {
        throw new UnsupportedOperationException("Cannot get available versions in this test case");
    }

    @Override
    public List<ArtifactVersion> retrieveAvailableVersionsFromDeploymentRepository(

      // we could rely solely on #poll, but #drainTo might be more efficient when there are multiple
      // elements already available (e.g. LinkedBlockingQueue#drainTo locks only once)
      added += q.drainTo(buffer, numElements - added);
      if (added < numElements) { // not enough elements immediately available; will have to poll
        E e = q.poll(deadline - System.nanoTime(), NANOSECONDS);
        if (e == null) {

// Even if Read returns n < len(p), it may use all of p as scratch space during the call.
// If some data is available but not len(p) bytes, Read conventionally returns what is available instead of waiting for more.
// When Read encounters an error or end-of-file condition after successfully reading n > 0 bytes, it returns the number of bytes read.

    assertEquals(20, joined.size());
    InputStream in = joined.openStream();
    assertFalse(in.markSupported());
    assertEquals(10, in.available());
    int total = 0;
    while (in.read() != -1) {
      total++;
    }
    assertEquals(0, in.available());
    assertEquals(20, total);
  }

  @SuppressWarnings("CheckReturnValue") // these calls to skip always return 0

Define extra validations for data types using the "default" value of model attributes. This improves editor support, and it was not available in Pydantic before.

This actually inspired updating parts of Pydantic, to support the same validation declaration style (all this functionality is now already available in Pydantic).

///

### <a href="https://github.com/hugapi/hug" class="external-link" target="_blank">Hug</a> { #hug }

	}
	if r.lastErr != nil {
		err = r.lastErr
		return n, err
	}
	b := r.throttle.Burst()  // maximum available tokens
	need := len(buf)         // number of bytes requested by caller
	hdr := r.opts.HeaderSize // remaining header bytes
	var tokens int           // number of tokens to request

	if hdr > 0 { // available tokens go towards header first
		if hdr < b { // all of header can be accommodated
			r.opts.HeaderSize = 0

   */
  open fun callStart(call: Call) {
  }

  /**
   * Invoked for calls that were not executed immediately because resources weren't available. The
   * call will remain in the queue until resources are available.
   *
   * Use [Dispatcher.maxRequests] and [Dispatcher.maxRequestsPerHost] to configure how many calls
   * OkHttp performs concurrently.
   */
  open fun dispatcherQueueStart(

   * {@code InputStream.skip()}.
   */
  private static long skipSafely(InputStream in, long n) throws IOException {
    int available = in.available();
    return available == 0 ? 0 : in.skip(min(available, n));
  }

  /**
   * Process the bytes of the given input stream using the given processor.
   *
   * @param input the input stream to process

WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML