StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.addAll(MANY_VALUES);
    Stats stats = accumulator.snapshot();
    accumulator.add(999.999); // should do nothing to the snapshot
    return stats;
  }

  private static Stats buildLongManyValuesStatsSnapshot() {
    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.addAll(LONG_MANY_VALUES);

    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.addAll(MANY_VALUES);
    Stats stats = accumulator.snapshot();
    accumulator.add(999.999); // should do nothing to the snapshot
    return stats;
  }

  private static Stats buildLongManyValuesStatsSnapshot() {
    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.addAll(LONG_MANY_VALUES);

  public void testCountOverflow_doesNotThrow() {
    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.add(ONE_VALUE);
    for (int power = 1; power < Long.SIZE - 1; power++) {
      accumulator.addAll(accumulator.snapshot());
    }
    // Should overflow without throwing.
    accumulator.addAll(accumulator.snapshot());
    assertThat(accumulator.count()).isLessThan(0L);
  }

  public void testMean() {

    PairedStatsAccumulator accumulator = new PairedStatsAccumulator();
    accumulator.add(ONE_VALUE, OTHER_ONE_VALUE);
    for (int power = 1; power < Long.SIZE - 1; power++) {
      accumulator.addAll(accumulator.snapshot());
    }
    // Should overflow without throwing.
    accumulator.addAll(accumulator.snapshot());
    assertThat(accumulator.count()).isLessThan(0L);
  }

    // For datasets of many double values created from an accumulator snapshot, we test many
    // combinations of finite and non-finite values:
    for (ManyValues values : ALL_MANY_VALUES) {
      StatsAccumulator accumulator = new StatsAccumulator();
      accumulator.addAll(values.asIterable());
      double min = accumulator.snapshot().min();
      if (values.hasAnyNaN()) {

  // TODO(srbs): It seems like this is used only for performance optimization
  // and not for correctness. The only downside of keeping this 1 seems to be
  // that the gradient accumulation is unbounded and we will never
  // aggressively aggregate accumulated gradients to recover memory.
  // Revisit and fix.
  return 1;
}

// Consumes references to the tensors in the gradient_tensors list and returns
// a tensor with the result.

        rather than re-using a shared one.
    *   Fix FTRL L2-shrinkage behavior: the gradient from the L2 shrinkage term
        should not end up in the accumulator.
    *   Fix toco compilation/execution on Windows.
    *   GoogleZoneProvider class added to detect which Google Cloud Engine zone
        tensorflow is running in.

 *
 * @author Jared Levy
 * @author Louis Wasserman
 * @since 7.0
 */
@GwtCompatible
public final class Tables {
  private Tables() {}

  /**
   * Returns a {@link Collector} that accumulates elements into a {@code Table} created using the
   * specified supplier, whose cells are generated by applying the provided mapping functions to the

 *
 * @author Jared Levy
 * @author Louis Wasserman
 * @since 7.0
 */
@GwtCompatible
public final class Tables {
  private Tables() {}

  /**
   * Returns a {@link Collector} that accumulates elements into a {@code Table} created using the
   * specified supplier, whose cells are generated by applying the provided mapping functions to the

        File file = cos.getFile();
        assertTrue(file.exists());
        cos.close();
    }

    @Test
    public void testMultipleWrites() throws IOException {
        // Multiple write calls should accumulate
        ContentOutputStream cos = new ContentOutputStream(10, Curl.tmpDir);
        cos.write(new byte[] { 0, 1, 2 });
        assertTrue(cos.isInMemory());
        cos.write(new byte[] { 3, 4 });