小编Kri*_*dhi的帖子

如何在 debian buster 中安装 mysql workbench?

我尝试了以下命令:

sudo dpkg -i mysql-apt-config_0.3.5-1debian8_all.deb
sudo apt-get update
sudo apt-get install mysql-workbench-community
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但在搜索 mysql-workbench-community

sudo apt-cache search workbench | grep mysql
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什么都不返回。

sudo apt-get install mysql-workbench-community
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Reading package lists... Done
Building dependency tree       
Reading state information... Done
E: Unable to locate package mysql-workbench-community
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该怎么办 ?

mysql debian mysql-workbench

9
推荐指数
2
解决办法
1万
查看次数

使用数据生成器时,Keras 自定义指标 self.validation_data 为 none

我一直在尝试训练模型并在每个时期结束时计算精度和召回率。

自定义指标

class Metrics(keras.callbacks.Callback):
    def on_train_begin(self, logs={}):
        self.precision = []
        self.recall = []

    def on_epoch_end(self, epoch, logs={}):
        print(type(self.validation_data))
        print(self.validation_data)
        predict = np.round(np.asarray(self.model.predict(self.validation_data[0])))
        targ = self.validation_data[1]

        precision_score = sklm.precision_score(targ, predict)
        recall = sklm.recall_score(targ, predict)
        self.precision.append(precision_score)
        self.recall.append(recall)

    def avg_precision_score(self):
        return np.mean(self.precision_score)

    def avg_recall_score(self):
        return np.mean(self.recall)
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在训练时我使用数据生成器。

   training_set = train_datagen.flow_from_directory('train/',
                                                     target_size=(dim_x,dim_y),
                                                     batch_size=8, # 16 32
                                                     class_mode='categorical')

    test_set = test_datagen.flow_from_directory('test/',
                                                 target_size=(dim_x,dim_y),
                                                 batch_size=8, # 16 32
                                                 class_mode='categorical')
    metrics = Metrics()
    history = classifier.fit_generator(
                training_set,
                steps_per_epoch=2,#50,
                epochs=1, # 25
                validation_data=test_set,
                validation_steps=10,
                callbacks=[metrics]
                )
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但这给出了 None 类型的 …

python machine-learning keras tensorflow tf.keras

5
推荐指数
1
解决办法
1712
查看次数