* }
   * }
   *
   * <p>Note that if any input list is empty, the Cartesian product will also be empty. If no lists
   * at all are provided (an empty list), the resulting Cartesian product has one element, an empty
   * list (counter-intuitive, but mathematically consistent).
   *
   * <p><i>Performance notes:</i> while the cartesian product of lists of size {@code m, n, p} is a

      // If it won't fit in a long, then we store off the intermediate product.
      if (normalizedBits + productBits >= Long.SIZE) {
        bignums.add(BigInteger.valueOf(product));
        product = 1;
        productBits = 0;
      }
      product *= normalizedNum;
      productBits = LongMath.log2(product, FLOOR) + 1;
    }
    // Check for leftovers.
    if (product > 1) {
      bignums.add(BigInteger.valueOf(product));
    }

   * }
   * }
   *
   * <p>Note that if any input set is empty, the Cartesian product will also be empty. If no sets at
   * all are provided (an empty list), the resulting Cartesian product has one element, an empty
   * list (counter-intuitive, but mathematically consistent).
   *
   * <p><i>Performance notes:</i> while the cartesian product of sets of size {@code m, n, p} is a

runc

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    checkState(count() > 1);
    return sumOfProductsOfDeltas / (count() - 1);
  }

  /**
   * Returns the <a href="http://mathworld.wolfram.com/CorrelationCoefficient.html">Pearson's or
   * product-moment correlation coefficient</a> of the values. The count must greater than one, and
   * the {@code x} and {@code y} values must both have non-zero population variance (i.e. {@code

    checkState(count() > 1);
    return sumOfProductsOfDeltas / (count() - 1);
  }

  /**
   * Returns the <a href="http://mathworld.wolfram.com/CorrelationCoefficient.html">Pearson's or
   * product-moment correlation coefficient</a> of the values. The count must greater than one, and
   * the {@code x} and {@code y} values must both have non-zero population variance (i.e. {@code

        axesSizeProduct[i] = Math.multiplyExact(axesSizeProduct[i + 1], axes.get(i).size());
      }
    } catch (ArithmeticException e) {
      throw new IllegalArgumentException(
          "Cartesian product too large; must have size at most Integer.MAX_VALUE");
    }
    this.axesSizeProduct = axesSizeProduct;
  }

  private int getAxisIndexForProductIndex(int index, int axis) {

      return BigInteger.valueOf(LongMath.factorial(n));
    } else {
      int k = 20;
      return BigInteger.valueOf(LongMath.factorial(k)).multiply(oldSlowFactorial(k, n));
    }
  }

  /** Returns the product of {@code n1} exclusive through {@code n2} inclusive. */
  @SuppressWarnings("UseCorrectAssertInTests") // TODO(b/345814817): Remove or convert assertion.
  private static BigInteger oldSlowFactorial(int n1, int n2) {

     *
     * @return The minor version number.
     */
    public int getMinorVersion() {
        return minorVersion;
    }

    /**
     * Gets the product version string.
     *
     * @return The product version string.
     */
    public String getProductVersion() {
        return productVersion;
    }

    /**
     * Sets the interval for checking the system CPU load.

      return BigInteger.valueOf(LongMath.factorial(n));
    } else {
      int k = 20;
      return BigInteger.valueOf(LongMath.factorial(k)).multiply(oldSlowFactorial(k, n));
    }
  }

  /** Returns the product of {@code n1} exclusive through {@code n2} inclusive. */
  @SuppressWarnings("UseCorrectAssertInTests") // TODO(b/345814817): Remove or convert assertion.
  private static BigInteger oldSlowFactorial(int n1, int n2) {