"""
Top-level module of TensorFlow. By convention, we refer to this module as
`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
#include "tensorflow/core/common_runtime/graph_constructor.h"
#include "tensorflow/core/common_runtime/shape_refiner.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/graph/node_builder.h"

# Request Parameters

Here's the reference information for the request parameters.

These are the special functions that you can put in *path operation function* parameters or dependency functions with `Annotated` to get data from the request.

It includes:

* `Query()`
* `Path()`
* `Body()`
* `Cookie()`
* `Header()`
* `Form()`
* `File()`

You can import them all directly from `fastapi`:

```python

    }

    @Override
    public Iterable<Entry<String, String>> order(List<Entry<String, String>> insertionOrder) {
      return insertionOrder;
    }

    static final Function<String, String> FUNCTION =
        new Function<String, String>() {
          @Override
          public String apply(String value) {
            return Ascii.toLowerCase(value);
          }
        };

  /**
   * Returns a linear transformation giving the best fit to the data according to <a
   * href="http://mathworld.wolfram.com/LeastSquaresFitting.html">Ordinary Least Squares linear
   * regression</a> of {@code y} as a function of {@code x}. The count must be greater than one, and
   * either the {@code x} or {@code y} data must have a non-zero population variance (i.e. {@code

# Obtener Usuario Actual

En el capítulo anterior, el sistema de seguridad (que se basa en el sistema de inyección de dependencias) le estaba dando a la *path operation function* un `token` como un `str`:

{* ../../docs_src/security/tutorial001_an_py39.py hl[12] *}

Pero eso aún no es tan útil. Vamos a hacer que nos dé el usuario actual.

## Crear un modelo de usuario

Primero, vamos a crear un modelo de usuario con Pydantic.

# `Request` class

You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc.

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

/// tip

 * limitations under the License.
 */

package com.google.common.collect;

import static org.junit.Assert.assertThrows;

import com.google.common.base.Function;
import com.google.common.collect.Interners.InternerImpl;
import com.google.common.collect.MapMakerInternalMap.Strength;
import com.google.common.testing.GcFinalization;
import com.google.common.testing.NullPointerTester;

Pero también puedes declarar el `Response` que quieres usar (por ejemplo, cualquier subclase de `Response`), en el *path operation decorator* usando el parámetro `response_class`.

Los contenidos que devuelvas desde tu *path operation function* se colocarán dentro de esa `Response`.

import java.net.Proxy;
import java.net.URL;
import java.net.URLEncoder;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.ForkJoinPool;
import java.util.function.BiConsumer;
import java.util.function.Consumer;
import java.util.function.Supplier;
import java.util.logging.Logger;
import java.util.zip.GZIPInputStream;

import javax.net.ssl.HttpsURLConnection;
import javax.net.ssl.SSLSocketFactory;