// stops with no error. A non-nil token delivered with [ErrFinalToken]
// will be the last token, and a nil token with [ErrFinalToken]
// immediately stops the scanning.
//
// Otherwise, the [Scanner] advances the input. If the token is not nil,
// the [Scanner] returns it to the user. If the token is nil, the
// Scanner reads more data and continues scanning; if there is no more

    cat <<EOF
One or more test dependencies are not in the pip package.
If these test dependencies need to be in the TensorFlow pip package, please
add them to //tensorflow/tools/pip_package/BUILD. Otherwise, add the no_pip tag
to the test, or change code_check_full.bats in the SIG Build repository. That's
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/tf_sig_build_dockerfiles/devel.usertools/code_check_full.bats

    }
    throw new AssertionError();
  }

  /**
   * Returns a fresh {@link MapMakerInternalMap} with {@link MapMaker.Dummy} values but otherwise as
   * specified by the given {@code builder}. The returned {@link MapMakerInternalMap} will be
   * optimized to saved memory. Since {@link MapMaker.Dummy} is a singleton, we don't need to store

      "FINE: Q10000 starting              : task one",
      "FINE: Q10000 finished run in   0 µs: task one",
    )
  }

  /**
   * The runner doesn't hold references to its queues! Otherwise we'd need a mechanism to clean them
   * up when they're no longer needed and that's annoying. Instead the task runner only tracks which
   * queues have work scheduled.
   */

          new BinaryPredicate<Double, Double>() {
            @Override
            public boolean apply(@Nullable Double actual, @Nullable Double expected) {
              // Test for equality to allow non-finite values to match; otherwise, use the finite
              // test.
              return actual.equals(expected)
                  || FINITE_QUANTILE_CORRESPONDENCE.compare(actual, expected);
            }
          },

  /**
   * Returns an array containing the same values as {@code array}, but guaranteed to be of a
   * specified minimum length. If {@code array} already has a length of at least {@code minLength},
   * it is returned directly. Otherwise, a new array of size {@code minLength + padding} is
   * returned, containing the values of {@code array}, and zeroes in the remaining places.
   *
   * @param array the source array

          new BinaryPredicate<Double, Double>() {
            @Override
            public boolean apply(@Nullable Double actual, @Nullable Double expected) {
              // Test for equality to allow non-finite values to match; otherwise, use the finite
              // test.
              return actual.equals(expected)
                  || FINITE_QUANTILE_CORRESPONDENCE.compare(actual, expected);
            }
          },

  /**
   * Returns an array containing the same values as {@code array}, but guaranteed to be of a
   * specified minimum length. If {@code array} already has a length of at least {@code minLength},
   * it is returned directly. Otherwise, a new array of size {@code minLength + padding} is
   * returned, containing the values of {@code array}, and zeroes in the remaining places.
   *
   * @param array the source array

// OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
// HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
// LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
// OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
// SUCH DAMAGE.
//

package jcifs.smb1.util;

/**
 * This code is derived from the above source
 * JCIFS API

FastAPI does several things internally with Pydantic to make sure that those same rules of class inheritance are not used for the returned data filtering, otherwise you could end up returning much more data than what you expected.

This way, you can get the best of both worlds: type annotations with **tooling support** and **data filtering**.