ColBERT: Model stuck in Loading decompress_residuals_cpp extension

@okhat Hi, I am running colbert with following configuration on a single GPU.

Following is the script I am using. I just wanted to see if I could run a quick indexing end to end.

import os
import sys
sys.path.insert(0, '../')

from colbert.infra import Run, RunConfig, ColBERTConfig
from colbert.data import Queries, Collection
from colbert import Indexer, Searcher


if __name__ == '__main__':
    dataroot = 'downloads/lotte'
    dataset = 'lifestyle'
    datasplit = 'dev'

    queries = os.path.join(dataroot, dataset, datasplit, 'questions.search.tsv')
    collection = os.path.join(dataroot, dataset, datasplit, 'collection.tsv')

    queries = Queries(path=queries)
    collection = Collection(path=collection)

    f'Loaded {len(queries)} queries and {len(collection):,} passages'

    print(queries[24])
    print()
    print(collection[89852])
    print()

    nbits = 2   # encode each dimension with 2 bits
    doc_maxlen = 300   # truncate passages at 300 tokens

    checkpoint = 'downloads/colbertv2.0'
    index_name = f'{dataset}.{datasplit}.{nbits}bits'

    with Run().context(RunConfig(nranks=1, experiment='msmarco')):  # nranks specifies the number of GPUs to use.
        config = ColBERTConfig(doc_maxlen=doc_maxlen, nbits=nbits)

        indexer = Indexer(checkpoint=checkpoint, config=config)
        indexer.index(name=index_name, collection=collection[:20], overwrite=True)

    print(indexer.get_index()) # You can get the absolute path of the index, if needed.

However the indexing seems to be stuck at this point.

WARNING clustering 2687 points to 512 centroids: please provide at least 19968 training points
Clustering 2687 points in 128D to 512 clusters, redo 1 times, 20 iterations
  Preprocessing in 0.00 s
  Iteration 19 (1.10 s, search 0.23 s): objective=463.491 imbalance=1.616 nsplit=0
[Apr 22, 02:32:04] Loading decompress_residuals_cpp extension (set COLBERT_LOAD_TORCH_EXTENSION_VERBOSE=True for more info)...

I am running on a Quadro RTX 8000 (49GB) and 128GB RAM machine.