keras_cnn.py 文件源码

def train_model(self):
        if self.verbose:
            print 'training model ... '
            start_time = time.time()

        self.checkpointer = ModelCheckpoint(filepath=self.weights_filename, verbose=1, save_best_only=True)
        self.history = History()

        self.model.fit_generator(self.datagen.flow(self.xs_train, self.ys_train, batch_size=32),
                    samples_per_epoch=len(self.xs_train), nb_epoch=self.num_training_epochs, 
                    validation_data=(self.xs_val, self.ys_val),
                    callbacks=[self.checkpointer, self.history])

        if self.verbose:
            end_time = time.time()
            self.print_time(start_time, end_time,'training model')