在自定义 Keras 回调中使用 super

Question

我对 python super 的功能和继承不是很熟悉。我尝试复制并使用我找到的 keras 自定义回调示例in this post，但我收到了错误：

    super(EarlyStopping, self).__init__()
TypeError: super(type, obj): obj must be an instance or subtype of type

示例代码如下：

import numpy as np
from tensorflow.keras.callbacks import Callback, EarlyStopping

class OverfitEarlyStopping(Callback):
    def __init__(self, ratio=0.0,
                 patience=0, verbose=0):
        super(EarlyStopping, self).__init__()

        self.ratio = ratio
        self.patience = patience
        self.verbose = verbose
        self.wait = 0
        self.stopped_epoch = 0
        self.monitor_op = np.greater

    def on_train_begin(self, logs=None):
        self.wait = 0  # Allow instances to be re-used

    def on_epoch_end(self, epoch, logs=None):
        current_val = logs.get('val_loss')
        current_train = logs.get('loss')
        if current_val is None:
            warnings.warn('Early stopping requires %s available!' %
                          (self.monitor), RuntimeWarning)

        # If ratio current_loss / current_val_loss > self.ratio
        if self.monitor_op(np.divide(current_train,current_val),self.ratio):
            self.wait = 0
        else:
            if self.wait >= self.patience:
                self.stopped_epoch = epoch
                self.model.stop_training = True
            self.wait += 1

    def on_train_end(self, logs=None):
        if self.stopped_epoch > 0 and self.verbose > 0:
            print('Epoch %05d: early stopping due to overfitting.' % (self.stopped_epoch))

overfit_callback = OverfitEarlyStopping(ratio=0.8, patience=3, verbose=1)

我正在使用 Python 3.5 和 tensorflow.keras。我使用的版本中 super 的使用是否发生了变化，还是这个回调一开始就写错了？

Answer 1

扩展基类keras.callbacks.Callback时不需要初始化super。模型被传递给您选择覆盖的函数。可以看一些例子here

另外，为什么不使用tf.keras.callbacks.EarlyStopping