segments | Unicode Standard tokenization routines and orthography

You could play with flexible and different cex and adjust with the png parameters. This looks already better. For line-by-line gray shading we can simply use abline with modulo 2.

The problem with your approach is that the cross product value depends on the measurement scale.

Maybe the most intuitive measure of collinearity is the angle between the line segments. Let's calculate it:

The code doesn't work completely properly. Would you please explain my mistakes?

You were quite close. The main problem is that the return keyword in front of the recursive calls terminates the for loop and the entire f function prematurely. This will cause it to visit only the nodes on the first possible branch, not all of them.

The other issue is that branches might be empty at the end of the function, yet you still access [0][0]. Instead return the entire array from f, and access the first tuple on in getResult.

These two small fixes already make the function work¹:

You should use the re package:

The pathInfo function returns all the path segments for a Request. Perhaps we could define a typeclass that, given a Servant API, produced a "parser" for the list of segments, whose result would be a formatted version of the list.

The parser type could be something like:

The current structure of myfixture guarantee cleanup() is called between test_1 and test_2, unless prepare_stuff() is raising an unhandled exception. You will probably notice this, so the most likely issue is that cleanup() dosn't "clean" everything prepare_stuff() did, so prepare_stuff() can't setup something again.

As for your question, there is nothing pytest related that can cause the hang between the tests. You can force cleanup() to be called (even if an exception is being raised) by adding finalizer, it will be called after the teardown part

This is an initial answer (which is incorrect, as I incorrectly understood the question, see edit below for a corrected answer).

A natural way to do it is:

Building on Santiago Squarzon 's helpful comment:

Use a regex-based operation via the -replace operator:

This is not an error but a feature. BERT and other transformers use WordPiece tokenization algorithm that tokenizes strings into either: (1) known words; or (2) "word pieces" for unknown words in the tokenizer vocabulary.

In your examle, words "CTO", "TLR", and "Pty" are not in the tokenizer vocabulary, and thus WordPiece splits them into subwords. E.g. the first subword is "CT" and another part is "##O" where "##" denotes that the subword is connected to the predecessor.

This is a great feature that allows to represent any string.