private static final DenseImmutableTable<Character, Integer, String> DENSE =
      new DenseImmutableTable<>(CELLS.asList(), ROW_SPACE, COLUMN_SPACE);

  @Override
  Iterable<ImmutableTable<Character, Integer, String>> getTestInstances() {
    return ImmutableList.<ImmutableTable<Character, Integer, String>>of(SPARSE, DENSE);
  }

  public void testCellSet() {

		}
	}

	n = len(b0) - len(b)
	switch {
	case err == io.EOF:
		return n, errMissData // Less data in dense file than sparse file
	case err != nil:
		return n, err
	case sr.logicalRemaining() == 0 && sr.physicalRemaining() > 0:
		return n, errUnrefData // More data in dense file than sparse file
	case finished:
		return n, io.EOF
	default:
		return n, nil
	}
}

  static <R, C, V> RegularImmutableTable<R, C, V> forOrderedComponents(
      ImmutableList<Cell<R, C, V>> cellList,
      ImmutableSet<R> rowSpace,
      ImmutableSet<C> columnSpace) {
    // use a dense table if more than half of the cells have values
    // TODO(gak): tune this condition based on empirical evidence
    return (cellList.size() > (((long) rowSpace.size() * columnSpace.size()) / 2))

We are going to start from where we left in the previous chapter and increment it.

## About JWT { #about-jwt }

JWT means "JSON Web Tokens".

It's a standard to codify a JSON object in a long dense string without spaces. It looks like this:

```
eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiaWF0IjoxNTE2MjM5MDIyfQ.SflKxwRJSMeKKF2QT4fwpMeJf36POk6yJV_adQssw5c
```

 * Second, it is always backed by an array large enough to hold a value for every possible
 * combination of row and column keys. (This is rarely optimal unless the table is extremely dense.)
 * Finally, every possible combination of row and column keys is always considered to have a value
 * associated with it: It is not possible to "remove" a value, only to replace it with {@code null},

    *   Added `sparse_gradient` option (default=false) that makes the gradient of these functions/ops sparse (`IndexedSlices`) instead of dense (`Tensor`), using new `SparseSegmentSum/Mean/SqrtNGradV2` ops.

*   `tf.nn.embedding_lookup_sparse`

    *   Optimized this function for some cases by fusing internal operations.

*   `tf.saved_model.SaveOptions`

ud
sin
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dette
mit
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have
dig
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alt
meget
sit
sine
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disse
hvis
din
nogle
hos
blive
mange
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bliver
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været

eller
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blei
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   * data written to it to the underlying {@link OutputStream}.
   *
   * <p>The {@link OutputStream} should not be written to before or after the hand-off.
   */
  // TODO(user): Evaluate whether it makes sense to always piggyback the computation of a
  // HashCode on an existing OutputStream, compared to creating a separate OutputStream that could
  // be (optionally) be combined with another if needed (with something like

Swagger UI lidará com isso nos bastidores para você, mas ele precisa desse auxiliar de "redirecionamento".

///

### Criar uma *operação de rota* para testar

Agora, para poder testar se tudo funciona, crie uma *operação de rota*: