}

  static final ImmutableSet<Double> INTEGRAL_DOUBLE_CANDIDATES;
  static final ImmutableSet<Double> FRACTIONAL_DOUBLE_CANDIDATES;
  static final Iterable<Double> INFINITIES =
      Doubles.asList(Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY);
  static final Iterable<Double> FINITE_DOUBLE_CANDIDATES;
  static final Iterable<Double> POSITIVE_FINITE_DOUBLE_CANDIDATES;

     * 3a. ...either or both is NaN (so mean != value) then the new mean is NaN.
     * 3b. ...they are both the same infinities (so mean == value) then the mean is unchanged.
     * 3c. ...they are different infinities (so mean != value) then the new mean is NaN.
     */
    if (isFinite(previousMean)) {
      // This is case 1.
      return value;

import static com.google.common.math.MathTesting.FINITE_DOUBLE_CANDIDATES;
import static com.google.common.math.MathTesting.FRACTIONAL_DOUBLE_CANDIDATES;
import static com.google.common.math.MathTesting.INFINITIES;
import static com.google.common.math.MathTesting.INTEGRAL_DOUBLE_CANDIDATES;
import static com.google.common.math.MathTesting.NEGATIVE_INTEGER_CANDIDATES;

import static com.google.common.math.MathTesting.FINITE_DOUBLE_CANDIDATES;
import static com.google.common.math.MathTesting.FRACTIONAL_DOUBLE_CANDIDATES;
import static com.google.common.math.MathTesting.INFINITIES;
import static com.google.common.math.MathTesting.INTEGRAL_DOUBLE_CANDIDATES;
import static com.google.common.math.MathTesting.NEGATIVE_INTEGER_CANDIDATES;

    return Math.copySign(a - b, 1.0) <= tolerance
        // copySign(x, 1.0) is a branch-free version of abs(x), but with different NaN semantics
        || (a == b) // needed to ensure that infinities equal themselves
        || (Double.isNaN(a) && Double.isNaN(b));
  }

  /**
   * Compares {@code a} and {@code b} "fuzzily," with a tolerance for nearly-equal values.
   *

 * you would expect.
 *
 * <p>If required to do a weighted average between an infinity and a finite value, or between an
 * infinite value and itself, the infinite value is returned. If required to do a weighted average
 * between {@link Double#NEGATIVE_INFINITY NEGATIVE_INFINITY} and {@link Double#POSITIVE_INFINITY

* /// check: /// check | Testen
* /// danger: /// danger | Gefahr
* /// info: /// info | Info
* /// note | Technical Details: /// note | Technische Details

*   `tf.debugging`
    *   Add `tf.debugging.enable_check_numerics()` and
        `tf.debugging.disable_check_numerics()` to help debugging the root
        causes of issues involving infinities and `NaN`s.
*   `tf.distribute`
    *   Custom training loop support on TPUs and TPU pods is available through
        `strategy.experimental_distribute_dataset`,

    content: attr(data-ty-prompt);
}

[data-ty-cursor]:after {
    content: attr(data-ty-cursor);
    font-family: monospace;
    margin-left: 0.5em;
    -webkit-animation: blink 1s infinite;
            animation: blink 1s infinite;
}


/* Cursor animation */

@-webkit-keyframes blink {
    50% {
        opacity: 0;
    }
}

@keyframes blink {
    50% {
        opacity: 0;
    }

    PAST(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO),
    FUTURE(Timeout.SMALL, Timeout.MAX),
    SMALL(Timeout.SMALL),
    FINITE(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO, Timeout.SMALL),
    INFINITE(Timeout.LARGE, Timeout.MAX);

    final ImmutableList<Timeout> timeouts;

    TimeoutsToUse(Timeout... timeouts) {
      this.timeouts = ImmutableList.copyOf(timeouts);
    }
  }