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from datasets import load_dataset
from dataclasses import dataclass, field
import logging
from transformers import HfArgumentParser
from tqdm import tqdm
from typing import Dict, List
import json
logger = logging.getLogger()
logger.setLevel(logging.INFO)
console_handler = logging.StreamHandler()
console_handler.setFormatter(
logging.Formatter("[%(asctime)s %(levelname)s] %(message)s")
)
logger.handlers = [console_handler]
@dataclass
class ConversionAgruments:
path: str = field(metadata={"help": "Path to the MAMARCO dataset"})
out: str = field(metadata={"help": "Output path"})
@dataclass
class QRel:
doc: int
score: int
def load_json(path: str, split: str = "train") -> List[str]:
dataset = load_dataset("json", data_files=path, split=split)
cache: List[str] = []
for row in tqdm(dataset, desc=f"loading {path}"):
index = int(row["_id"])
if index >= len(cache):
cache.extend([""] * (1 + 2 * max(index, len(cache))))
cache[index] = row["text"]
return cache
def load_qrel(path: str) -> Dict[int, List[QRel]]:
dataset = load_dataset("csv", data_files=path, split="train", delimiter="\t")
print(dataset.features)
cache: Dict[int, List[QRel]] = {}
for row in tqdm(dataset, desc=f"loading {path}"):
qid = int(row["query-id"])
qrel = QRel(int(row["corpus-id"]), int(row["score"]))
if qid in cache:
cache[qid].append(qrel)
else:
cache[qid] = [qrel]
return cache
def process(
qrels: Dict[int, List[QRel]], queries: List[str], corpus: List[str]
) -> List[Dict]:
result = []
for query, rels in tqdm(qrels.items(), desc="processing split"):
pos = [
{"doc": corpus[rel.doc], "score": rel.score}
for rel in rels
if rel.doc < len(corpus) and rel.score > 0 and corpus[rel.doc] != ""
]
neg = [
{"doc": corpus[rel.doc], "score": rel.score}
for rel in rels
if rel.doc < len(corpus) and rel.score == 0 and corpus[rel.doc] != ""
]
group = {"query": queries[query], "pos": pos}
if len(neg) > 0:
group["neg"] = neg
result.append(group)
return result
def main():
parser = HfArgumentParser((ConversionAgruments))
(args,) = parser.parse_args_into_dataclasses()
print(f"Args: {args}")
corpus = load_json(f"{args.path}/corpus.jsonl", split="train")
queries = load_json(f"{args.path}/queries.jsonl")
qrels = {
"dev": process(load_qrel(f"{args.path}/qrels/dev.tsv"), queries, corpus),
"test": process(load_qrel(f"{args.path}/qrels/test.tsv"), queries, corpus),
"train": process(load_qrel(f"{args.path}/qrels/train.tsv"), queries, corpus),
}
print("processing done")
for split, data in qrels.items():
with open(f"{args.out}/{split}.jsonl", "w") as out:
for item in data:
json.dump(item, out)
out.write("\n")
print("done")
if __name__ == "__main__":
main()
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