Refactor retrieval to make it faster to run in numba mode

[xhluca]

This a work in progress!

This PR will make numba mode faster by rewriting the entire retrieve process into a numba JIT-able function (see _retrieve_internal_numba_parallel)

TODO:

• Cleanup retrieve_numba to make it compatible with retrieve when BM25 object is initiatilized with backend="numba"
• Deprecate selection_backend in retrieve so that it happens at the object init time
• Potentially rename _retrieve_internal_numba_parallel
• Make tqdm work in _retrieve_internal_numba_parallel
• Potentially refactor the behavior of the selection and numba.selection modules
• Create a tokenizer class (perhaps in a separate PR? also should handle On-the-fly stemming #31 at the same time)
• add Tests for numba in numpy-disk mode and with bm25+ (use non-occurrence matrix)

[xhluca]

I wonder if it is possible to do invertex indexing here, by creating an array that tracks start and end:

bm25s/bm25s/scoring.py

Lines 329 to 352 in daf29ce

	def _compute_relevance_from_scores_jit_ready(
	data: np.ndarray,
	indptr: np.ndarray,
	indices: np.ndarray,
	num_docs: int,
	query_tokens_ids: np.ndarray,
	dtype: np.dtype,
	) -> np.ndarray:
	"""
	This internal static function calculates the relevance scores for a given query,
	by using the BM25 scores that have been precomputed in the BM25 eager index.
	This version is ready for JIT compilation with numba, but is slow if not compiled.
	"""
	indptr_starts = indptr[query_tokens_ids]
	indptr_ends = indptr[query_tokens_ids + 1]
	scores = np.zeros(num_docs, dtype=dtype)
	for i in range(len(query_tokens_ids)):
	start, end = indptr_starts[i], indptr_ends[i]
	# The following code is slower with numpy, but faster after JIT compilation
	for j in range(start, end):
	scores[indices[j]] += data[j]
	return scores

[xhluca]

Deprecate selection_backend in retrieve so that it happens at the object init time

In retrospective, it seems that selection_backend remains useful for testing purposes, as well as using the jax backend. Let's not deprecate it in 0.2.0

[xhluca]

Make tqdm work in _retrieve_internal_numba_parallel

Unfortuantely tqdm won't work, so we can't add progress bar to retrieve when backend is set to numba

[xhluca]

Create a tokenizer class (perhaps in a separate PR? also should handle #31 at the same time)

Will do that in a separate PR