def _batchify(self, batch_data, batch_label, start=0):
    'Helper function for batchifying data'
    i = start
    batch_size = self.batch_size
    try:
        while (i < batch_size):
            (label, s) = self.next_sample()
            data = self.imdecode(s)
            try:
                self.check_valid_image(data)
            except RuntimeError as e:
                logging.debug('Invalid image, skipping:  %s', str(e))
                continue
            data = self.augmentation_transform(data)
            assert (i < batch_size), 'Batch size must be multiples of augmenter output length'
            batch_data[i] = self.postprocess_data(data)
            batch_label[i] = label
            i += 1
    except StopIteration:
        if (not i):
            raise StopIteration
    return i
Helper function for batchifying data
def _batchify(self, batch_data, batch_label, start=0):
    
    i = start
    batch_size = self.batch_size
    try:
        while (i < batch_size):
            (label, s) = self.next_sample()
            data = self.imdecode(s)
            try:
                self.check_valid_image(data)
            except RuntimeError as e:
                logging.debug('Invalid image, skipping:  %s', str(e))
                continue
            data = self.augmentation_transform(data)
            assert (i < batch_size), 'Batch size must be multiples of augmenter output length'
            batch_data[i] = self.postprocess_data(data)
            batch_label[i] = label
            i += 1
    except StopIteration:
        if (not i):
            raise StopIteration
    return i