keras UserWarning: The input 1303 could not be retrieved. It could be because a worker has died I am trying to train an autoencoder CNN on Google Colab using keras. I have mounted my Google Drive which contains all training data. The training uses six workers and the data is loaded by the following custom generator class:

class ImageDataGenerator(keras.utils.Sequence):

    def __init__(self, filepaths, batch_size, shape, shuffle=True):
        self.shape = shape
        self.batch_size = batch_size
        self.filepaths = filepaths
        self.shuffle = shuffle
        self.on_epoch_end()

    def __len__(self):
        return int(np.ceil(len(self.filepaths) / self.batch_size))

    def __getitem__(self, index):
        from_index = index * self.batch_size
        to_index = min(len(self.filepaths), (index + 1) * self.batch_size)

        filepaths_temp = self.filepaths[from_index : to_index]

        images = load_images(filepaths_temp) / 255.0

        return images, images

    def on_epoch_end(self):
        if self.shuffle:
            np.random.shuffle(self.filepaths)


My problem: Sometimes when I start training I get this:

Epoch 1/100
/usr/local/lib/python3.6/dist-packages/keras/utils/data_utils.py:610: UserWarning: The input 1303 could not be retrieved. It could be because a worker has died.
  UserWarning)
1599/1599 [==============================] - 2461s 2s/step - loss: 0.0239 - val_loss: 0.0251

Epoch 00001: val_loss improved from inf to 0.02512, saving model to /content/drive/...
Epoch 2/100


Apart from the warning epoch 1 seems to finish successfully. But after the last line is printed, nothing happens anymore. Epoch 2 never starts.

I suspect the mounted Google Drive filesystem is the problem, because I had problems with Google Drive timeouts in the past. My Question is: Is there something I did wrong? Did one of the six workers die? Is there something I can do to restore the workers after the first epoch? After all, it seemed to work fine for the first epoch.
The solution for me was to copy all training data from the mounted Google Drive file system to the Google Colab file system. I didn't realize before that the mounted Drive file systems has a comparatively bad performance that leads to this error.