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- Changed how KMS v2 encryption at rest can generate data encryption keys.

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  /**
   * Returns an output {@code Future} to use in place of the given {@code input}. The output {@code
   * Future} need not be {@linkplain Future#isDone done}, making {@code AsyncFunction} suitable for
   * asynchronous derivations.
   *
   * <p>Throwing an exception from this method is equivalent to returning a failing {@code Future}.
   */
  ListenableFuture<O> apply(@ParametricNullness I input) throws Exception;

public interface AsyncCallable<V extends @Nullable Object> {
  /**
   * Computes a result {@code Future}. The output {@code Future} need not be {@linkplain
   * Future#isDone done}, making {@code AsyncCallable} suitable for asynchronous derivations.
   *
   * <p>Throwing an exception from this method is equivalent to returning a failing {@link
   * ListenableFuture}.
   */
  ListenableFuture<V> call() throws Exception;

   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a
   * fraction {@code sqrt(1/(R*R) - 1)} of the population standard deviation of {@code x}. This fit

# V <= U <= V+1
# More info at https://protobuf.dev/support/cross-version-runtime-guarantee/
protobuf >= 5.28.0, < 7.0
# Test dependencies
grpcio >= 1.68.1, < 2.0
portpicker == 1.6.0
# Scipy 15.x and above have misc.derivative removed, but we still use it
scipy >= 1.13.0, < 1.15.0
requests >= 2.31.0
packaging==23.2
setuptools==78.1.1
jax==0.4.7
zstandard==0.23.0
# The dependencies below are needed for TF wheel testing.

   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a
   * fraction {@code sqrt(1/(R*R) - 1)} of the population standard deviation of {@code x}. This fit