needs: initial-build
    runs-on: ${{ matrix.os }}
    strategy:
      fail-fast: false
      matrix:
        os: [ubuntu-latest, macos-latest, windows-latest]
        java: ['17', '21', '25']
    steps:
      - name: Set up JDK ${{ matrix.java }}
        uses: actions/setup-java@f2beeb24e141e01a676f977032f5a29d81c9e27e # v5.1.0
        with:
          java-version: ${{ matrix.java }}
          distribution: 'temurin'

        with:
          api-level: ${{ matrix.api-level }}
          arch: ${{ matrix.api-level == '34' && 'x86_64' || 'x86' }}
          script: ./gradlew :android-test:connectedCheck
        env:
          API_LEVEL: ${{ matrix.api-level }}

      - name: Run Release Tests
        uses: reactivecircus/android-emulator-runner@v2
        with:
          api-level: ${{ matrix.api-level }}

/**
 * Evaluator for plugin parameters expressions. Content surrounded by <code>${</code> and <code>}</code> is evaluated.
 * Recognized values are:
 * <table border="1">
 * <caption>Expression matrix</caption>
 * <tr><th>expression</th>                     <th></th>               <th>evaluation result</th></tr>
 * <tr><td><code>session</code></td>           <td></td>               <td>the actual {@link MavenSession}</td></tr>

* **Maschinelles Lernen**: Normalerweise sind viele „Matrix“- und „Vektor“-Multiplikationen erforderlich. Stellen Sie sich eine riesige Tabelle mit Zahlen vor, in der Sie alle Zahlen gleichzeitig multiplizieren.

* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.

8.271Z\",\"max\":\"2019-07-30T10:40:08.271Z\"}},\"aggType\":\"date_histogram\"},\"y\":[{\"accessor\":1,\"format\":{\"id\":\"number\"},\"params\":{},\"aggType\":\"count\"}]}},\"aggs\":[{\"id\":\"1\",\"enabled\":true,\"type\":\"count\",\"schema\":\"metric\",\"params\":{\"customLabel\":\"Query Count\"}},{\"id\":\"2\",\"enabled\":true,\"type\":\"date_histogram\",\"schema\":\"segment\",\"params\":{\"field\":\"requestedAt\",\"timeRange\":{\"from\":\"now-2d\",\"to\":\"now\"},\"useNormalizedEsInterval\"...

  /**
   * Returns the number of bytes required to encode these headers using HTTP/1.1. This is also the
   * approximate size of HTTP/2 headers before they are compressed with HPACK. This value is
   * intended to be used as a metric: smaller headers are more efficient to encode and transmit.
   */
  fun byteCount(): Long {
    // Each header name has 2 bytes of overhead for ': ' and every header value has 2 bytes of
    // overhead for '\r\n'.

 *
 * <p>This class only provides testing utilities. It is not designed for direct use in production or
 * for benchmarking.
 *
 * @author mike nonemacher
 * @author Martin Buchholz
 * @since 11.0
 */
@GwtIncompatible
@J2ktIncompatible
@J2ObjCIncompatible // gc
@NullMarked
public final class GcFinalization {
  private GcFinalization() {}

  /**

 *   long xBits = Double.doubleToRawLongBits(x);
 *   long yBits = Double.doubleToRawLongBits(y);
 *   return xBits == yBits;
 * }
 * }
 *
 * @author Doug Lea
 * @author Martin Buchholz
 * @since 11.0
 */
@GwtIncompatible
@J2ktIncompatible
public class AtomicDoubleArray implements Serializable {
  private static final long serialVersionUID = 0L;

  stars: 4202
  owner_login: dynaconf
  owner_html_url: https://github.com/dynaconf
- name: atrilabs-engine
  html_url: https://github.com/Atri-Labs/atrilabs-engine
  stars: 4093
  owner_login: Atri-Labs
  owner_html_url: https://github.com/Atri-Labs
- name: Kokoro-FastAPI
  html_url: https://github.com/remsky/Kokoro-FastAPI
  stars: 4019
  owner_login: remsky
  owner_html_url: https://github.com/remsky