def __init__(self, source, *args, **kwargs):
        """Init."""
        super(IndexBatchIterator, self).__init__(*args, **kwargs)
        self.source = source
        if source is not None:
            # Tack on (SAMPLE_SIZE-1) copies of the first value so that it is
            # easy to grab
            # SAMPLE_SIZE POINTS even from the first location.
            x = source.data
            input_shape = [len(x) + (SAMPLE_SIZE - 1), N_ELECTRODES]
            self.augmented = np.zeros(input_shape, dtype=np.float32)
            self.augmented[1-SAMPLE_SIZE:] = x
            self.augmented[:SAMPLE_SIZE-1] = x[0]
        if filt2Dsize:
            input_shape = [self.batch_size, 1, N_ELECTRODES, TIME_POINTS]
            self.Xbuf = np.zeros(input_shape, np.float32)
        else:
            input_shape = [self.batch_size, N_ELECTRODES, TIME_POINTS]
            self.Xbuf = np.zeros(input_shape, np.float32)
        self.Ybuf = np.zeros([self.batch_size, N_EVENTS], np.float32)
dataset/ETHPy150Open alexandrebarachant/Grasp-and-lift-EEG-challenge/lvl1/genPreds_CNN_Tim.py/IndexBatchIterator.__init__/swapped operands of `-`