!!! check
    Dadurch erhalten Sie Editor-Unterstützung innerhalb Ihrer Funktion, mit Fehlerprüfungen, Codevervollständigung, usw.

## Daten-<abbr title="Auch bekannt als: Serialisierung, Parsen, Marshalling">Konversion</abbr>

Wenn Sie dieses Beispiel ausführen und Ihren Browser unter <a href="http://127.0.0.1:8000/items/3" class="external-link" target="_blank">http://127.0.0.1:8000/items/3</a> öffnen, sehen Sie als Response:

```JSON

limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_C_CONVERSION_MACROS_H_
#define TENSORFLOW_C_CONVERSION_MACROS_H_

#define DEFINE_CONVERSION_FUNCTIONS(cpp_impl, wrapper)                         \
  inline cpp_impl *unwrap(wrapper *w) {                                        \

SAM Conversions
---------------

When you use Java APIs from Kotlin you can operate on Java interfaces as if they were Kotlin
lambdas. The [feature][java_sams] is available for interfaces that define a Single Abstract Method
(SAM).

But when you use Kotlin APIs from Kotlin there’s no automatic conversion. Code that used SAM lambdas

client = TestClient(app)


def test_route_converters_int():
    # Test integer conversion
    response = client.get("/int/5")
    assert response.status_code == 200, response.text
    assert response.json() == {"int": 5}
    assert app.url_path_for("int_convertor", param=5) == "/int/5"  # type: ignore


def test_route_converters_float():
    # Test float conversion
    response = client.get("/float/25.5")

}  // namespace tracing

DEFINE_CONVERSION_FUNCTIONS(AbstractContext, TF_ExecutionContext)
DEFINE_CONVERSION_FUNCTIONS(AbstractTensorHandle, TF_AbstractTensor)
DEFINE_CONVERSION_FUNCTIONS(AbstractFunction, TF_AbstractFunction)
DEFINE_CONVERSION_FUNCTIONS(AbstractOperation, TF_AbstractOp)
DEFINE_CONVERSION_FUNCTIONS(OutputList, TF_OutputList)
}  // namespace tensorflow

==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_TFE_CONTEXT_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_CONTEXT_INTERNAL_H_

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/immediate_execution_context.h"

// Wraps a pointer to a context implementation.
//
// WARNING: Since the underlying object could be ref-counted a user of this

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/core/framework/cancellation.h"

struct TFE_CancellationManager;
typedef struct TFE_CancellationManager TFE_CancellationManager;

namespace tensorflow {
DEFINE_CONVERSION_FUNCTIONS(tensorflow::CancellationManager,
                            TFE_CancellationManager);
DEFINE_CONVERSION_FUNCTIONS(tensorflow::CancellationManager*,

  @Override
  public int intValue() {
    return (int) sum();
  }

  /** Returns the {@link #sum} as a {@code float} after a widening primitive conversion. */
  @Override
  public float floatValue() {
    return (float) sum();
  }

  /** Returns the {@link #sum} as a {@code double} after a widening primitive conversion. */
  @Override

!!! note "Remarque"
    `JSONResponse` est elle-même une sous-classe de `Response`.

Et quand vous retournez une `Response`, **FastAPI** la transmet directement.

Elle ne fera aucune conversion de données avec les modèles Pydantic, elle ne convertira pas le contenu en un type quelconque.

```

### 3. Failure after conversion
If the conversion is successful, but the generated model is wrong, then state what is wrong:

- Model produces wrong results and/or has lesser accuracy.
- Model produces correct results, but it is slower than expected.

### 4. (optional) RNN conversion support
If converting TF RNN to TFLite fused RNN ops, please prefix [RNN] in the title.