Construisez ensuite la valeur par défaut de votre paramètre avec `Query`, en choisissant 50 comme `max_length` :

```Python hl_lines="9"
{!../../../docs_src/query_params_str_validations/tutorial002.py!}
```

Comme nous devons remplacer la valeur par défaut `None` dans la fonction par `Query()`, nous pouvons maintenant définir la valeur par défaut avec le paramètre `Query(default=None)`, il sert le même objectif qui est de définir cette valeur par défaut.

Donc :

      for (int i = 0; i < num_values; ++i) {
        op_->colocation_constraints.emplace(static_cast<const char*>(values[i]),
                                            lengths[i]);
      }
    } else {
      std::vector<tensorflow::StringPiece> v;
      v.reserve(num_values);
      for (int i = 0; i < num_values; ++i) {
        v.emplace_back(static_cast<const char*>(values[i]), lengths[i]);
      }

# figure out all the tools you need in your environment to make that work.
export BUILD_WITH_CONTAINER ?= 0

ifeq ($(BUILD_WITH_CONTAINER),1)

# An export free of arguments in a Makefile places all variables in the Makefile into the
# environment. This is needed to allow overrides from Makefile.overrides.mk.
export

RUN = ./common/scripts/run.sh

    PartialTensorShape shape;
    TF_RETURN_IF_ERROR(input->Shape(&shape));
    TF_RETURN_IF_ERROR(dyn_cast<tracing::TracingContext>(ctx)->AddParameter(
        input->DataType(), shape, &handle));
    params->emplace_back(handle);
  }
  return absl::OkStatus();
}

// Runs `model` maybe wrapped in a function.
Status RunModel(Model model, AbstractContext* ctx,
                absl::Span<AbstractTensorHandle* const> inputs,

                        &arrived, &executed, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  // Create a variable handle placed on the custom device.
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> op(
      TFE_NewOp(context.get(), "VarHandleOp", status.get()), TFE_DeleteOp);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  // ForwardAccumulator.
  explicit ForwardAccumulator(
      const VSpace<Gradient, BackwardFunction, TapeTensor>& vspace,
      bool use_batch)
      : vspace_(vspace), use_batch_(use_batch) {
    call_state_.emplace(nullptr, false);
  }

  virtual ~ForwardAccumulator() {
    for (auto accumulated : accumulated_gradients_) {
      vspace_.DeleteGradient(accumulated.second);
    }
  }

     *            context to use
     * @param chlng
     *            The server challenge.
     * @param dest
     *            The destination array in which the user session key will be
     *            placed.
     * @param offset
     *            The offset in the destination array at which the
     *            session key will start.
     * @throws SmbException
     */

# Bugs and Feature Requests

You can report bugs and feature requests to the Istio team in one of three places:

- [Product Bugs and Feature Requests](https://github.com/istio/istio/issues)
- [Documentation Bugs and Feature Requests](https://github.com/istio/istio.io/issues)
- [Community and Governance Issues](https://github.com/istio/community/issues)

For security vulnerabilities, please don't report a bug (which is public) and instead follow

        }
        msg += ")";
        logger.debug(msg);
    }

    public void manageArtifactVersion(Artifact artifact, Artifact replacement) {
        // only show msg if a change is actually taking place
        if (!replacement.getVersion().equals(artifact.getVersion())) {
            String msg = indent + artifact + " (applying version: " + replacement.getVersion() + ")";
            logger.debug(msg);
        }
    }

 * provide much stronger guarantees.
 *
 * <h3>Comparison to a map of collections</h3>
 *
 * <p>Multimaps are commonly used in places where a {@code Map<K, Collection<V>>} would otherwise
 * have appeared. The differences include:
 *
 * <ul>
 *   <li>There is no need to populate an empty collection before adding an entry with {@link #put
 *       put}.