Custom Data Generator for Keras LSTM with TimeSeriesGenerator

It could be because the object type is changed from Sequence which is what a TimeseriesGenerator is to a generic generator. The fit_generator function treats these differently. A cleaner solution would be to inherit the class and override the processing bit:

class CustomGen(TimeseriesGenerator):
  def __getitem__(self, idx):
    x, y = super()[idx]
    # do processing here
    return x, y

And use this class like before as the rest of internal logic will remain the same.

I personally had a problem with the code by nuric. For some reason I had the error saying super not being subscriptable. Here is my possible fix. Let me known if this could possibly work?

class CustomGen(TimeseriesGenerator):
    def __getitem__(self, idx):
        x,y = super().__getitem__(idx)
        return x, y