from enum import Enum

from fastapi import FastAPI


class ModelName(str, Enum):
    alexnet = "alexnet"
    resnet = "resnet"
    lenet = "lenet"


app = FastAPI()


@app.get("/models/{model_name}")
async def get_model(model_name: ModelName):
    if model_name is ModelName.alexnet:
        return {"model_name": model_name, "message": "Deep Learning FTW!"}

    if model_name.value == "lenet":

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}


/// tip | Tipp

Falls Sie sich fragen, was „AlexNet“, „ResNet“ und „LeNet“ ist, das sind Namen von <abbr title="Genau genommen, Deep-Learning-Modellarchitekturen">Modellen</abbr> für maschinelles Lernen.

///

### Einen *Pfad-Parameter* deklarieren { #declare-a-path-parameter }

Then create class attributes with fixed values, which will be the available valid values:

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

///

### Declare a *path parameter* { #declare-a-path-parameter }

Luego crea atributos de clase con valores fijos, que serán los valores válidos disponibles:

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}

/// tip | Consejo

Si te estás preguntando, "AlexNet", "ResNet" y "LeNet" son solo nombres de <abbr title="Técnicamente, arquitecturas de modelos de Deep Learning">modelos</abbr> de Machine Learning.

///

### Declarar un *path parameter* { #declare-a-path-parameter }

///

/// tip | İpucu

Merak ediyorsanız söyleyeyim, "AlexNet", "ResNet" ve "LeNet" isimleri Makine Öğrenmesi <abbr title="Teknik olarak, Derin Öğrenme model mimarileri">modellerini</abbr> temsil eder.

///

### Bir *Yol Parametresi* Tanımlayalım

<a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Перелічення (або enums) доступні в Python</a> починаючи з версії 3.4.

///

/// tip | Порада

Якщо вам цікаво, "AlexNet", "ResNet" та "LeNet" — це просто назви ML моделей <abbr title="Технічно, архітектури Deep Learning моделей">Machine Learning</abbr>.

///


### Оголосіть *параметр шляху*

                    throw new SmbException("Account '" + username + "' is locked out until " + account.getLockoutExpiry());
                } else {
                    // Lockout expired, reset
                    account.reset();
                }
            }
        }

        // Check per-IP limit
        if (sourceIp != null) {

        assertEquals(State.OPEN, circuitBreaker.getState(), "Circuit should be OPEN");

        // Manually reset
        circuitBreaker.reset();
        assertEquals(State.CLOSED, circuitBreaker.getState(), "Circuit should be CLOSED after reset");
        assertEquals(0, circuitBreaker.getFailureCount(), "Failure count should be reset");
    }

    @Test
    public void testCustomFailureDetection() throws CIFSException {

    assertEquals("9.999 \u03bcs", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance(1234567);
    assertEquals("1.235 ms", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance(5000000000L);
    assertEquals("5.000 s", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance((long) (1.5 * 60 * 1000000000L));

    var_to_data_type_map_.swap(result.second);
  } else {
    reader_.reset(new TensorSliceReader(filename));
    if (!reader_->status().ok()) {
      tsl::Set_TF_Status_from_Status(status, reader_->status());
      return;
    }
    var_to_shape_map_.reset(
        new TensorSliceReader::VarToShapeMap(reader_->GetVariableToShapeMap()));
    var_to_data_type_map_.reset(new TensorSliceReader::VarToDataTypeMap(