ParagraphAggregator

class torchdata.datapipes.iter.ParagraphAggregator(source_datapipe: ~IterDataPipe[~Tuple[str, ~T_co]], joiner: ~Callable = <function _default_line_join>)

Aggregates lines of text from the same file into a single paragraph (functional name: lines_to_paragraphs). Specifically, this accepts a DataPipe consisting of tuples of a file name and a line. For each tuple, it checks if the file name matches the file name from the previous tuple. If yes, it joins the current line with existing paragraph. If the file names do not match, the existing paragraph is yielded and a new paragraph starts.

Parameters:

• source_datapipe – a DataPipe with tuples of a file name and a line

• joiner – a function that joins a list of lines together

Example

>>> from torchdata.datapipes.iter import IterableWrapper
>>> source_dp = IterableWrapper(
>>>                 [("file1", "Line1"), ("file1", "Line2"), ("file2", "Line2,1"), ("file2", "Line2,2"), ("file2", "Line2,3")]
>>>             )
>>> para_agg_dp = source_dp.lines_to_paragraphs(joiner=lambda ls: " ".join(ls))
>>> list(para_agg_dp)
[('file1', 'Line1 Line2'), ('file2', 'Line2,1 Line2,2 Line2,3')]