new Predicate<Integer>() {
        @Override
        public boolean apply(Integer input) {
          return input % 2 == 0;
        }
      };

  private static final Predicate<Integer> PRIME_DIGIT = Predicates.in(ImmutableSet.of(2, 3, 5, 7));

  private static final ImmutableList<? extends List<Integer>> SAMPLE_INPUTS =
      ImmutableList.of(
          ImmutableList.<Integer>of(),
          ImmutableList.of(1),

      new Predicate<Integer>() {
        @Override
        public boolean apply(Integer input) {
          return input % 2 == 0;
        }
      };

  private static final Predicate<Integer> PRIME_DIGIT = Predicates.in(ImmutableSet.of(2, 3, 5, 7));

  private static final ImmutableList<? extends List<Integer>> SAMPLE_INPUTS =
      ImmutableList.of(
          ImmutableList.<Integer>of(),
          ImmutableList.of(1),

  // Build an abstract input tensor.
  TFE_Context* eager_ctx =
      TF_ExecutionContextGetTFEContext(eager_execution_ctx, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TFE_TensorHandle* input_eager = TestScalarTensorHandle(eager_ctx, 2.0f);
  TF_AbstractTensor* input_t =
      TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get());

    private final String[] inputs;

    private final String output;

    private String[] newInputs;

    private String newOutput;

    public CharMappingItem(final long id, final String[] inputs, final String output) {
        this.id = id;
        this.inputs = inputs;
        this.output = output == null ? null : output.replace("\n", " ");
        Arrays.sort(inputs);

        if (id == 0) {

/**
 * A future whose value is derived from a collection of input futures.
 *
 * @param <InputT> the type of the individual inputs
 * @param <OutputT> the type of the output (i.e. this) future
 */
@GwtCompatible
@ElementTypesAreNonnullByDefault
abstract class AggregateFuture<InputT extends @Nullable Object, OutputT extends @Nullable Object>
    extends AggregateFutureState<OutputT> {

                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    CHECK_EQ(grad_outputs.size(), 1);
    CHECK_EQ(grad_inputs.size(), 1);
    grad_inputs[0] = grad_outputs[0];
    if (grad_inputs[0]) {
      grad_inputs[0]->Ref();
    }
    return absl::OkStatus();
  }
};

// Computes:
//
// @tf.custom_gradient
// def f(input):
//   def grad(grads):
//     return grads[0]

// Creates parameters (placeholders) in the tracing `ctx` using the shape and
// dtype of `inputs`.
Status CreateParamsForInputs(AbstractContext* ctx,
                             absl::Span<AbstractTensorHandle* const> inputs,
                             std::vector<AbstractTensorHandle*>* params);

// A callable that takes tensor inputs and returns zero or more tensor outputs.
using Model = std::function<Status(AbstractContext*,

    absl::Span<AbstractTensorHandle* const> inputs, bool use_function,
    double abs_error) {
  auto num_inputs = inputs.size();
  std::vector<AbstractTensorHandle*> outputs(num_inputs);
  auto s = RunModel(grad_model, ctx, inputs, absl::MakeSpan(outputs),
                    /*use_function=*/use_function);
  ASSERT_EQ(errors::OK, s.code()) << s.message();

  for (int i = 0; i < num_inputs; ++i) {
    if (!outputs[i]) continue;

import java.io.StringWriter;
import java.util.Random;

/** Benchmark for {@code BaseEncoding} performance. */
public class BaseEncodingBenchmark {
  private static final int INPUTS_COUNT = 0x1000;
  private static final int INPUTS_MASK = 0xFFF;

  enum EncodingOption {
    BASE64(BaseEncoding.base64()),
    BASE64_URL(BaseEncoding.base64Url()),
    BASE32(BaseEncoding.base32()),
    BASE32_HEX(BaseEncoding.base32Hex()),

}
Status TapeOperation::AddInput(AbstractTensorHandle* input) {
  TF_RETURN_IF_ERROR(parent_op_->AddInput(input));
  forward_op_.inputs.push_back(input);
  return OkStatus();
}
Status TapeOperation::AddInputList(
    absl::Span<AbstractTensorHandle* const> inputs) {
  TF_RETURN_IF_ERROR(parent_op_->AddInputList(inputs));
  for (auto input : inputs) {
    forward_op_.inputs.push_back(input);
  }
  return OkStatus();
}