Question

我编写了以下代码：

class PredictionSerializer(serializers.HyperlinkedModelSerializer):
    class Meta:
        model = Prediction
        fields = ["id", "market"]
        depth = 1

class FixtureSerializer(serializers.HyperlinkedModelSerializer):
    predictions = PredictionSerializer()
    class Meta:
        model = Fixture
        fields = ["sofascore_id", "home", "away", "league", "round", "date", "predictions"]
        depth = 1 

class FixtureViewSet(viewsets.ReadOnlyModelViewSet):
    """
    API endpoint that allows fixture to be viewed or edited.
    """
    serializer_class = FixtureSerializer
    permission_classes = [permissions.IsAuthenticated]
    filter_backends = [django_filters.rest_framework.DjangoFilterBackend]
    filterset_fields = ("home", "away", "sofascore_id", "statistics")

    def get_queryset(self):
        date = self.request.query_params.get('date')       
        queryset = Fixture.objects.all().order_by('-date')

        if(date):
            queryset = Fixture.objects.filter(date__date=date).order_by('date')
        return queryset

对应于以下模型：

class Market(models.Model):
    name = models.CharField(max_length=200)

class Fixture(models.Model):
    sofascore_id = models.CharField(max_length=200)

    home = models.ForeignKey(Team, on_delete=models.CASCADE, related_name="home")
    away = models.ForeignKey(Team, on_delete=models.CASCADE, related_name="away")

    league = models.ForeignKey(League, on_delete=models.CASCADE, blank=True)
    round = models.CharField(max_length=200, default=None, blank=True, null=True)
    date = models.DateTimeField()

    statistics = models.ForeignKey(Statistics, on_delete=models.CASCADE, default=None, blank=True, null=True)

    updated_at = models.DateTimeField(auto_now=True)
    created_at = models.DateTimeField(auto_now_add=True)

    def __str__(self):
        return u'{0} - {1}'.format(self.home.name, self.away.name)

class Prediction(models.Model):
    market = models.ForeignKey(Market, on_delete=models.CASCADE, blank=True)
    fixture = models.ForeignKey(to=Fixture, on_delete=models.CASCADE, related_name="predictions", null=True, blank=True)

当我向/ fixtures请求时，“预测”字典始终为空，但是当我使用以下语句运行一些测试代码时：

f = Fixture.objects.get(sofascore_id=match).predictions.all()

我得到以下作为返回值：

<QuerySet [<Prediction: Prediction object (23)>, <Prediction: Prediction object (24)>, <Prediction: Prediction object (25)>, <Prediction: Prediction object (26)>, <Prediction: Prediction object (27)>, <Prediction: Prediction object (28)>]>

这是什么问题，为什么我无法使用书面代码来检索我的预测？

Answer 1

您需要在序列化程序中指定属性def build_regressor(timesteps,units,optimizer): X_train = [] y_train = [] for i in range(timesteps, np.ma.size(training_set_scaled)): X_train.append(training_set_scaled[i-timesteps:i, 0]) y_train.append(training_set_scaled[i, 0]) X_train, y_train = np.array(X_train), np.array(y_train) X_train = np.reshape(X_train, (X_train.shape[0], X_train.shape[1], 1)) regressor = Sequential() regressor.add(LSTM(units = units, return_sequences = True, input_shape = (X_train.shape[1], X_train.shape[2]))) regressor.add(Dropout(rate=0.2)) regressor.add(LSTM(units = units, return_sequences = True)) regressor.add(Dropout(rate=0.2)) regressor.add(LSTM(units = units, return_sequences = True)) regressor.add(Dropout(rate=0.2)) regressor.add(LSTM(units = units)) regressor.add(Dropout(rate=0.2)) regressor.add(Dense(units = 1)) regressor.compile(optimizer = optimizer, loss = 'mean_squared_error') return regressor, X_train, y_train regressor = KerasRegressor(build_fn = build_regressor) parameters = {'batch_size': [25, 32], 'epochs': [100, 200], 'optimizer': ['adam', 'rmsprop'], 'units': [50,75], 'timesteps': [60,120]} grid_search = GridSearchCV(estimator = regressor, param_grid = parameters, scoring = 'neg_mean_squared_error', cv = 10) grid_search = grid_search.fit(X_train, y_train) best_parameters = grid_search.best_params_ best_accuracy = grid_search.best_score_：

many

嵌套关系返回空字典DRF

1 个答案: