The functions for the Streaming Dataset to generate stream of segments

GenerateStreams.py

def segments_generator(self, segment_list: _Segment) -> None:
        """
        Generates original and augmented segments from a track.
        """
        if self.config.get('get_shifts'):
            segment_list = create_new_segments_from_splits(segment_list, nsplits=self.config['shift_segment'])
        else:
            segment_list = create_new_segments_from_splits(segment_list, nsplits=32)

        if self.config.get('get_vertical_flip'):
            flips = create_flipped_segments(segment_list, flip_type='vertical')
            segment_list.extend(flips)
        if self.config.get('get_horizontal_flip'):
            flips = create_flipped_segments(segment_list, flip_type='horizontal')
            segment_list.extend(flips)

        for segment in segment_list:
            if self.config['output_data_type'] == 'scalogram':
                segment.assert_valid_scalogram()
            else:
                segment.assert_valid_spectrogram()
                
        self.segment_blocks.extend(segment_list)
        random.shuffle(self.segment_blocks)
     
    def process_tracks_shuffle(self):
        for i, track in enumerate(self.data):
            self.segments_generator(track)
            if i % self.config.get('tracks_in_memory', 100) == self.config.get('tracks_in_memory', 100):
                segment_blocks = self.segment_blocks
                self.segment_blocks = []
                random.shuffle(segment_blocks)
                yield segment_blocks
        segment_blocks = self.segment_blocks
        self.segment_blocks = []
        random.shuffle(segment_blocks)
        yield segment_blocks

    def shuffle_stream(self):
        return chain(self.process_tracks_shuffle())

#     def linear_stream(self):
#         return chain(self.segments_generator(track) for track in self.data)

    def __iter__(self):
        for segments in chain(self.shuffle_stream()):
            yield from segments