* mentioned in the method Javadoc does in fact compile.
   */

  @SuppressWarnings("unused") // compilation test
  public void testSampleCodeError1() {
    Optional<Integer> optionalInt = getSomeOptionalInt();
    // Number value = optionalInt.or(0.5); // error
  }

  @SuppressWarnings("unused") // compilation test
  public void testSampleCodeError2() {
    FluentIterable<? extends Number> numbers = getSomeNumbers();

 *
 * @since 4.0.0
 */
@Experimental
public enum JavaPathType implements PathType {
    /**
     * The path identified by the Java {@code --class-path} option.
     * Used for compilation, execution and Javadoc among others.
     *
     * <p><b>Context-sensitive interpretation:</b>
     * A dependency with this path type will not necessarily be placed on the class-path.

      TFE_NewContextOptions(), TFE_DeleteContextOptions);
  std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> config(
      TF_CreateConfig(
          /*enable_xla_compilation=*/false,
          /*gpu_memory_allow_growth=*/true, /*num_cpu_devices=*/2),
      TF_DeleteBuffer);
  TFE_ContextOptionsSetConfig(opts.get(), config->data, config->length,
                              status.get());

   * mentioned in the method Javadoc does in fact compile.
   */

  @SuppressWarnings("unused") // compilation test
  public void testSampleCodeError1() {
    Optional<Integer> optionalInt = getSomeOptionalInt();
    // Number value = optionalInt.or(0.5); // error
  }

  @SuppressWarnings("unused") // compilation test
  public void testSampleCodeError2() {
    FluentIterable<? extends Number> numbers = getSomeNumbers();

//
// a) ConfigProto.optimizer_options.global_jit_level is set to ON_1 if
// `enable_xla_compilation` is non-zero, and OFF otherwise.
// b) ConfigProto.gpu_options.allow_growth is set to `gpu_memory_allow_growth`.
// c) ConfigProto.device_count is set to `num_cpu_devices`.
TF_CAPI_EXPORT extern TF_Buffer* TF_CreateConfig(
    unsigned char enable_xla_compilation, unsigned char gpu_memory_allow_growth,
    unsigned int num_cpu_devices);

unsigned char TF_SetXlaEnableLazyCompilation(unsigned char enable) {
  tensorflow::BuildXlaOpsPassFlags* flags =
      tensorflow::GetBuildXlaOpsPassFlags();
  bool original = flags->tf_xla_enable_lazy_compilation;
  flags->tf_xla_enable_lazy_compilation = enable;
  return original;
}

unsigned char TF_SetTfXlaCpuGlobalJit(unsigned char enable) {
  tensorflow::MarkForCompilationPassFlags* flags =
      tensorflow::GetMarkForCompilationPassFlags();

    work need not make them do so.

  A compilation of a covered work with other separate and independent
works, which are not by their nature extensions of the covered work,
and which are not combined with it such as to form a larger program,
in or on a volume of a storage or distribution medium, is called an
"aggregate" if the compilation and its resulting copyright are not

- plugin dependency metadata missing
- plugin dependency metadata retrieval problem
- plugin configuration problem
- plugin execution failure due to something that is know to possibly go wrong (like compilation failure)
- plugin execution error due to something that is not expected to go wrong (the compiler executable missing)
- asking to use a plugin for which you do not have a version defined - tools to easily select versions

      TFE_NewContextOptions(), TFE_DeleteContextOptions);
  std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> config(
      TF_CreateConfig(
          /*enable_xla_compilation=*/false,
          /*gpu_memory_allow_growth=*/true, /*num_cpu_devices=*/2),
      TF_DeleteBuffer);
  TFE_ContextOptionsSetConfig(opts.get(), config->data, config->length,
                              status.get());

    nums.add(3);
    Predicate<Integer> isThree = Predicates.in(nums);
    assertFalse(isThree.apply(3));
  }

  /*
   * Tests that compilation will work when applying explicit types.
   */
  @SuppressWarnings("unused") // compilation test
  public void testIn_compilesWithExplicitSupertype() {
    Collection<Number> nums = ImmutableSet.of();
    Predicate<Number> p1 = Predicates.in(nums);