}

  /**
   * Returns a {@code Collector} that accumulates elements into an {@code ImmutableTable}. Each
   * input element is mapped to one cell in the returned table, with the rows, columns, and values
   * generated by applying the specified functions. If multiple inputs are mapped to the same row
   * and column pair, they will be combined with the specified merging function in encounter order.
   *

    List<List<Integer>> input = newArrayList(list1, list2);

    FluentIterable<Integer> result = FluentIterable.concat(input);
    assertEquals(asList(1, 4), newArrayList(result));

    // Now change the inputs and see result dynamically change as well

    list1.add(2);
    List<Integer> list3 = newArrayList(3);
    input.add(1, list3);

  private static class Control extends AbstractNonStreamingHashFunction {
    @Override
    public HashCode hashBytes(byte[] input, int off, int len) {
      return HashCode.fromBytes(Arrays.copyOfRange(input, off, off + len));
    }

    @Override
    public int bits() {
      throw new UnsupportedOperationException();
    }
  }

            // * if single date picker mode, and time picker isn't enabled, apply the selection immediately
            // * if one of the inputs above the calendars was focused, cancel that manual input
            //

            if (this.endDate || date.isBefore(this.startDate, 'day')) { //picking start
                if (this.timePicker) {

   * (key) bits 'affects' a strictly smaller set of output bits. Funneling is bad because it can
   * result in more-than-ideal collisions for a non-uniformly distributed key space. In practice,
   * most key spaces are ANYTHING BUT uniformly distributed. A bit(i) in the input is said to
   * 'affect' a bit(j) in the output if two inputs, identical but for bit(i), will differ at output

            None if separate_input_output_schemas else "validation"
        )
        inputs = [
            (field, override_mode or field.mode, field._type_adapter.core_schema)
            for field in fields
        ]
        field_mapping, definitions = schema_generator.generate_definitions(
            inputs=inputs
        )
        return field_mapping, definitions  # type: ignore[return-value]

  }

  /**
   * Returns a {@code Future} whose result is taken from the given primary {@code input} or, if the
   * primary input fails with the given {@code exceptionType}, from the result provided by the
   * {@code fallback}. {@link AsyncFunction#apply} is not invoked until the primary input has
   * failed, so if the primary input succeeds, it is never invoked. If, during the invocation of

  // existing and given constraints will be performed.
  virtual absl::Status SetDeviceName(const char* name) = 0;

  virtual absl::Status AddInput(AbstractTensorHandle* input) = 0;
  virtual absl::Status AddInputList(
      absl::Span<AbstractTensorHandle* const> inputs) = 0;
  virtual absl::Status Execute(absl::Span<AbstractTensorHandle*> retvals,
                               int* num_retvals) = 0;

flex;\n}\n\n.input-group-prepend .btn,\n.input-group-append .btn {\n  position: relative;\n  z-index: 2;\n}\n\n.input-group-prepend .btn:focus,\n.input-group-append .btn:focus {\n  z-index: 3;\n}\n\n.input-group-prepend .btn + .btn,\n.input-group-prepend .btn + .input-group-text,\n.input-group-prepend .input-group-text + .input-group-text,\n.input-group-prepend .input-group-text + .btn,\n.input-group-append .btn + .btn,\n.input-group-append .btn + .input-group-text,\n.input-group-append .input-group-text...

 * Converter.apply (like Converter.convert) is capable of accepting null inputs. However, a
 * supertype of `Function<A, B>` turns out to be massively more useful to callers in practice: They
 * want their output to be non-null in operations like `stream.map(myConverter)`, and we can
 * guarantee that as long as we also require the input type to be non-null[*] (which is a
 * requirement that existing callers already fulfill).
 *