Use python read for text dataset
As mentioned in #622 the pandas reader used for text dataset doesn't work properly when there are \r characters in the text file.

Instead I switched to pure python using `open` and `read`.
From my benchmark on a 100MB text file, it's the same speed as the previous pandas reader.
One thing though, could we try to read the files in parallel? We could but I'm not sure this would help a lot since the bottleneck is the drive IO if the files are big enough.
It could make sense for very small files. Looks like windows is not a big fan of this approach
I'm working on a fix I remember issue https://github.com/huggingface/datasets/issues/546 where this was kinda requested (but maybe IO would bottleneck). What do you think? I think it's worth testing multiprocessing. It could also be something we add to our speed benchmarks > I remember issue #546 where this was kinda requested (but maybe IO would bottleneck). What do you think?

It still would be interesting I think, especially in scenarios where IO is less of an issue (SSDs particularly) and where there are many smaller files. Wrapping this function in a `pool.map` is perhaps an easy thing to try.  Merging this one for now for the patch release