peerRESTDryRun          = "dry-run"
	peerRESTUploadID        = "up-id"

	peerRESTURL         = "url"
	peerRESTSha256Sum   = "sha256sum"
	peerRESTReleaseInfo = "releaseinfo"
	peerRESTExecAt      = "exec-at"

	peerRESTListenBucket = "bucket"
	peerRESTListenPrefix = "prefix"
	peerRESTListenSuffix = "suffix"
	peerRESTListenEvents = "events"
	peerRESTLogMask      = "log-mask"
)

     *
     * @param project The project being summarized, must not be {@code null}.
     * @param wallTime The wall time of the project in milliseconds.
     * @param execTime The exec time of the project in milliseconds.
     */
    public BuildSuccess(MavenProject project, long wallTime, long execTime) {
        super(project, wallTime, execTime);
    }

          fi
          docker container prune -f
          docker image prune -af
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository for nightly (skipped for releases)
        if: ${{ github.event_name == 'schedule' }}
        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2

in{submit:!0,reset:!0})b.pseudos[e]=_(e);function G(){}function Y(e,t){var n,r,i,o,a,s,u,l=c[e+" "];if(l)return t?0:l.slice(0);a=e,s=[],u=b.preFilter;while(a){for(o in n&&!(r=y.exec(a))||(r&&(a=a.slice(r[0].length)||a),s.push(i=[])),n=!1,(r=m.exec(a))&&(n=r.shift(),i.push({value:n,type:r[0].replace(ve," ")}),a=a.slice(n.length)),b.filter)!(r=D[o].exec(a))||u[o]&&!(r=u[o](r))||(n=r.shift(),i.push({value:n,type:o,matches:r}),a=a.slice(n.length));if(!n)break}return t?a.length:a?I.error(e):c(e,s).slice(0)}function...

@app.get("/heroes/", response_model=List[HeroPublic])
def read_heroes(
    session: Session = Depends(get_session),
    offset: int = 0,
    limit: int = Query(default=100, le=100),
):
    heroes = session.exec(select(Hero).offset(offset).limit(limit)).all()
    return heroes


@app.get("/heroes/{hero_id}", response_model=HeroPublic)
def read_hero(hero_id: int, session: Session = Depends(get_session)):

    return db_hero


@app.get("/heroes/", response_model=list[HeroPublic])
def read_heroes(
    session: SessionDep,
    offset: int = 0,
    limit: Annotated[int, Query(le=100)] = 100,
):
    heroes = session.exec(select(Hero).offset(offset).limit(limit)).all()
    return heroes


@app.get("/heroes/{hero_id}", response_model=HeroPublic)
def read_hero(hero_id: int, session: SessionDep):
    hero = session.get(Hero, hero_id)

          fi
          docker container prune -f
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository
        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
      - name: Build binary and run python tests
        shell: bash
        run: |

fi

tfrun bazel build $TFCI_BAZEL_COMMON_ARGS --config=cuda_wheel //tensorflow/tools/pip_package:wheel $TFCI_BUILD_PIP_PACKAGE_ARGS
tfrun find ./bazel-bin/tensorflow/tools/pip_package -iname "*.whl" -exec cp {} $TFCI_OUTPUT_DIR \;
tfrun mkdir ./dist
tfrun cp $TFCI_OUTPUT_DIR/*.whl ./dist
tfrun ./ci/official/utilities/rename_and_verify_wheels.sh

if [[ "$TFCI_ARTIFACT_STAGING_GCS_ENABLE" == 1 ]]; then

                String filename = file.getFileName().toString();
                if (mavenArtifactJar.matcher(filename).matches()) {
                    Process p = Runtime.getRuntime().exec(new String[] {
                        Paths.get(System.getProperty("java.home"), "bin/java").toString(),
                        "-jar",
                        file.toAbsolutePath().toString(),
                        "5.32",

    netsh advfirewall firewall add rule name="Allow Metadata Proxy" dir=in action=allow protocol=TCP localport=80 remoteip="$CONTAINER_IP_ADDR"
  fi

fi