integrity sha512-zLHQdI/Qs1UyT5UBdWNqsARasIA+AaF8t+4u2aS2nEpBQh2mWIVb8qAklq0eUENnC5mOItrIB4LiS9xMtph18A==

"@webpack-cli/serve@^2.0.3":
  version "2.0.5"
  resolved "https://registry.yarnpkg.com/@webpack-cli/serve/-/serve-2.0.5.tgz#325db42395cd49fe6c14057f9a900e427df8810e"
  integrity sha512-lqaoKnRYBdo1UgDX8uF24AfGMifWK19TxPmM5FHc2vAGxrJ/qtyUyFBWoY1tISZdelsQ5fBcOusifo5o5wSJxQ==

   * {@code lexicographical(Collections.reverseOrder(comparator))} (consider how each would order
   * {@code [1]} and {@code [1, 1]}).
   */
  // Note: 90% of the time we don't add type parameters or wildcards that serve only to "tweak" the
  // desired return type. However, *nested* generics introduce a special class of problems that we
  // think tip it over into being worthwhile.

scenario would require a malicious user to be able to control the model which as
stated above is already equivalent to code execution. In any case, the
recommendation is not to serve models using Eager mode since it also has
performance limitations.

## Multi-Tenant environments

It is possible to run multiple TensorFlow models in parallel. For example,

    Typically this would cause certain redirects to fail in debug and development configurations.


## Version 4.4.0

_2020-02-17_

 *  New: Support `canceled()` as an event that can be observed by `EventListener`. This should be
    useful for splitting out canceled calls in metrics.

 *  New: Publish a [bill of materials (BOM)][bom] for OkHttp. Depend on this from Gradle or Maven to

func (m *Manager) AddToMux(router *mux.Router, authReq func(r *http.Request) error) {
	router.Handle(m.routePath, m.Handler(authReq))
}

// Handler returns a handler that can be used to serve grid requests.
// This should be connected on RoutePath to the main server.
func (m *Manager) Handler(authReq func(r *http.Request) error) http.HandlerFunc {
	return func(w http.ResponseWriter, req *http.Request) {

E esses modelos estão compartilhando muitos dos dados e duplicando nomes e tipos de atributos.

Nós poderíamos fazer melhor.

Podemos declarar um modelo `UserBase` que serve como base para nossos outros modelos. E então podemos fazer subclasses desse modelo que herdam seus atributos (declarações de tipo, validação, etc.).

Toda conversão de dados, validação, documentação, etc. ainda funcionará normalmente.

```

...desde:

```Python
        ... "item_name": item.name ...
```

...a:

```Python
        ... "item_price": item.price ...
```

...y observa cómo tu editor autocompleta los atributos y conoce sus tipos:

![editor support](https://fastapi.tiangolo.com/img/vscode-completion.png)

        }
      } finally {
        monitor.leave();
      }
    }

    /**
     * Marks the {@link State} as ready to receive transitions. Returns true if no transitions have
     * been observed yet.
     */
    void markReady() {
      monitor.enter();
      try {
        if (!transitioned) {
          // nothing has transitioned since construction, good.
          ready = true;
        } else {

        }
      } finally {
        monitor.leave();
      }
    }

    /**
     * Marks the {@link State} as ready to receive transitions. Returns true if no transitions have
     * been observed yet.
     */
    void markReady() {
      monitor.enter();
      try {
        if (!transitioned) {
          // nothing has transitioned since construction, good.
          ready = true;
        } else {

  return grads;
}

std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def) {
  std::vector<string> names;
  auto functions = graph_def.library().function();
  names.reserve(functions.size());
  for (const tensorflow::FunctionDef& func : functions) {
    names.push_back(func.signature().name());
  }
  std::sort(names.begin(), names.end());
  return names;
}