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| import os | |
| import copy | |
| import faiss | |
| from argparse import ArgumentParser | |
| import colbert.utils.distributed as distributed | |
| from colbert.utils.runs import Run | |
| from colbert.utils.utils import print_message, timestamp, create_directory | |
| class Arguments(): | |
| def __init__(self, description): | |
| self.parser = ArgumentParser(description=description) | |
| self.checks = [] | |
| self.add_argument('--root', dest='root', default='experiments') | |
| self.add_argument('--experiment', dest='experiment', default='dirty') | |
| self.add_argument('--run', dest='run', default=Run.name) | |
| self.add_argument('--local_rank', dest='rank', default=-1, type=int) | |
| def add_model_parameters(self): | |
| # Core Arguments | |
| self.add_argument('--similarity', dest='similarity', default='cosine', choices=['cosine', 'l2']) | |
| self.add_argument('--dim', dest='dim', default=128, type=int) | |
| self.add_argument('--query_maxlen', dest='query_maxlen', default=32, type=int) | |
| self.add_argument('--doc_maxlen', dest='doc_maxlen', default=180, type=int) | |
| # Filtering-related Arguments | |
| self.add_argument('--mask-punctuation', dest='mask_punctuation', default=False, action='store_true') | |
| def add_model_training_parameters(self): | |
| # NOTE: Providing a checkpoint is one thing, --resume is another, --resume_optimizer is yet another. | |
| self.add_argument('--resume', dest='resume', default=False, action='store_true') | |
| self.add_argument('--resume_optimizer', dest='resume_optimizer', default=False, action='store_true') | |
| self.add_argument('--checkpoint', dest='checkpoint', default=None, required=False) | |
| self.add_argument('--lr', dest='lr', default=3e-06, type=float) | |
| self.add_argument('--maxsteps', dest='maxsteps', default=400000, type=int) | |
| self.add_argument('--bsize', dest='bsize', default=32, type=int) | |
| self.add_argument('--accum', dest='accumsteps', default=2, type=int) | |
| self.add_argument('--amp', dest='amp', default=False, action='store_true') | |
| def add_model_inference_parameters(self): | |
| self.add_argument('--checkpoint', dest='checkpoint', required=True) | |
| self.add_argument('--bsize', dest='bsize', default=128, type=int) | |
| self.add_argument('--amp', dest='amp', default=False, action='store_true') | |
| def add_training_input(self): | |
| self.add_argument('--triples', dest='triples', required=True) | |
| self.add_argument('--queries', dest='queries', default=None) | |
| self.add_argument('--collection', dest='collection', default=None) | |
| def check_training_input(args): | |
| assert (args.collection is None) == (args.queries is None), \ | |
| "For training, both (or neither) --collection and --queries must be supplied." \ | |
| "If neither is supplied, the --triples file must contain texts (not PIDs)." | |
| self.checks.append(check_training_input) | |
| def add_ranking_input(self): | |
| self.add_argument('--queries', dest='queries', default=None) | |
| self.add_argument('--collection', dest='collection', default=None) | |
| self.add_argument('--qrels', dest='qrels', default=None) | |
| def add_reranking_input(self): | |
| self.add_ranking_input() | |
| self.add_argument('--topk', dest='topK', required=True) | |
| self.add_argument('--shortcircuit', dest='shortcircuit', default=False, action='store_true') | |
| def add_indexing_input(self): | |
| self.add_argument('--collection', dest='collection', required=True) | |
| self.add_argument('--index_root', dest='index_root', required=True) | |
| self.add_argument('--index_name', dest='index_name', required=True) | |
| def add_compressed_index_input(self): | |
| self.add_argument('--compression_level', dest='compression_level', | |
| choices=[1, 2], type=int, default=None) | |
| def add_index_use_input(self): | |
| self.add_argument('--index_root', dest='index_root', required=True) | |
| self.add_argument('--index_name', dest='index_name', required=True) | |
| self.add_argument('--partitions', dest='partitions', default=None, type=int, required=False) | |
| def add_retrieval_input(self): | |
| self.add_index_use_input() | |
| self.add_argument('--nprobe', dest='nprobe', default=10, type=int) | |
| self.add_argument('--retrieve_only', dest='retrieve_only', default=False, action='store_true') | |
| def add_argument(self, *args, **kw_args): | |
| return self.parser.add_argument(*args, **kw_args) | |
| def check_arguments(self, args): | |
| for check in self.checks: | |
| check(args) | |
| def parse(self): | |
| args = self.parser.parse_args() | |
| self.check_arguments(args) | |
| args.input_arguments = copy.deepcopy(args) | |
| args.nranks, args.distributed = distributed.init(args.rank) | |
| args.nthreads = int(max(os.cpu_count(), faiss.omp_get_max_threads()) * 0.8) | |
| args.nthreads = max(1, args.nthreads // args.nranks) | |
| if args.nranks > 1: | |
| print_message(f"#> Restricting number of threads for FAISS to {args.nthreads} per process", | |
| condition=(args.rank == 0)) | |
| faiss.omp_set_num_threads(args.nthreads) | |
| Run.init(args.rank, args.root, args.experiment, args.run) | |
| Run._log_args(args) | |
| Run.info(args.input_arguments.__dict__, '\n') | |
| return args | |