custom checkpoint to save model at your timing

customModelCheckpoint.py

from keras.callbacks import Callback
import numpy as np

class CustomModelCheckpoint(Callback):
    """
    Custom Metricsが特定の閾値を超えたときだけモデルを保存するチェックポイント
    thresholdsはkeyがmetrics名、値が閾値となるDictionary
    """
    def __init__(self, filepath, thresholds, inverse=False):
        super(CustomModelCheckpoint, self).__init__()

        self.filepath = filepath
        self.thresholds = thresholds
        self.inverse = inverse

    def on_epoch_end(self, epoch, logs=None):
        """
        logsにmetricsに指定した内容が（validationの方はval_というプレフィックス付きで）入っている。
        """
        logs = logs or {}
        filepath = self.filepath.format(epoch=epoch, **logs)

        save = True
        for k,v in self.thresholds.items():
            if self.inverse:
                if (k in logs and logs[k] > v) or np.isnan(logs[k]):
                    save = False
                    break
            else:
                if (k in logs and logs[k] < v) or np.isnan(logs[k]):
                    save = False
                    break

        if save:
            self.model.save(filepath, overwrite=True)