Spaces:
Runtime error
Runtime error
File size: 5,755 Bytes
d6585f5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 |
#
# Pyserini: Reproducible IR research with sparse and dense representations
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import os
import json
from abc import ABC, abstractmethod
from enum import Enum, unique
from pathlib import Path
from pyserini.search import get_topics, get_topics_with_reader
from pyserini.util import download_url, get_cache_home
from pyserini.external_query_info import KILT_QUERY_INFO
from urllib.error import HTTPError, URLError
@unique
class TopicsFormat(Enum):
DEFAULT = 'default'
KILT = 'kilt'
class QueryIterator(ABC):
PREDEFINED_ORDER = {'msmarco-doc-dev',
'msmarco-doc-test',
'msmarco-passage-dev-subset',
'msmarco-passage-test-subset'}
def __init__(self, topics: dict, order: list = None):
self.order = order if order else sorted(topics.keys())
self.topics = topics
@abstractmethod
def get_query(self, id_):
raise NotImplementedError()
@classmethod
@abstractmethod
def from_topics(cls, topics_path: str):
raise NotImplementedError()
def __iter__(self):
for id_ in self.order:
yield id_, self.get_query(id_)
def __len__(self):
return len(self.topics.keys())
@staticmethod
def get_predefined_order(topics_path: str):
order = None
normalized_path = Path(topics_path).stem # get filename w/o extension
normalized_path = normalized_path.replace('_', '-')
if normalized_path in QueryIterator.PREDEFINED_ORDER:
print(f'Using pre-defined topic order for {normalized_path}')
# Lazy import:
from pyserini.query_iterator_order_info import QUERY_IDS
order = QUERY_IDS[topics_path]
return order
class DefaultQueryIterator(QueryIterator):
def get_query(self, id_):
return self.topics[id_].get('title')
@classmethod
def from_topics(cls, topics_path: str):
if os.path.exists(topics_path):
if topics_path.endswith('.json'):
with open(topics_path, 'r') as f:
topics = json.load(f)
elif "beir" in topics_path:
topics = get_topics_with_reader('io.anserini.search.topicreader.TsvStringTopicReader', topics_path)
elif topics_path.endswith('.tsv') or topics_path.endswith('.tsv.gz'):
try:
topics = get_topics_with_reader('io.anserini.search.topicreader.TsvIntTopicReader', topics_path)
except ValueError as e:
topics = get_topics_with_reader('io.anserini.search.topicreader.TsvStringTopicReader', topics_path)
elif topics_path.endswith('.trec'):
topics = get_topics_with_reader('io.anserini.search.topicreader.TrecTopicReader', topics_path)
elif 'cacm' in topics_path:
topics = get_topics_with_reader('io.anserini.search.topicreader.CacmTopicReader', topics_path)
else:
raise NotImplementedError(f"Not sure how to parse {topics_path}. Please specify the file extension.")
else:
topics = get_topics(topics_path)
if not topics:
raise FileNotFoundError(f'Topic {topics_path} Not Found')
order = QueryIterator.get_predefined_order(topics_path)
return cls(topics, order)
class KiltQueryIterator(QueryIterator):
ENT_START_TOKEN = "[START_ENT]"
ENT_END_TOKEN = "[END_ENT]"
def get_query(self, id_):
datapoint = self.topics[id_]
query = (
datapoint["input"]
.replace(KiltQueryIterator.ENT_START_TOKEN, "")
.replace(KiltQueryIterator.ENT_END_TOKEN, "")
.strip()
)
return query
@classmethod
def from_topics(cls, topics_path: str):
topics = {}
order = []
if not os.path.exists(topics_path):
# Download if necessary:
topics_path = cls.download_kilt_topics(topics_path)
with open(topics_path, 'r') as f:
for line in f:
datapoint = json.loads(line)
topics[datapoint["id"]] = datapoint
order.append(datapoint["id"])
return cls(topics, order)
@classmethod
def download_kilt_topics(cls, task: str, force=False):
if task not in KILT_QUERY_INFO:
raise ValueError(f'Unrecognized query name {task}')
task = KILT_QUERY_INFO[task]
md5 = task['md5']
save_dir = os.path.join(get_cache_home(), 'queries')
if not os.path.exists(save_dir):
os.makedirs(save_dir)
for url in task['urls']:
try:
return download_url(url, save_dir, force=force, md5=md5)
except (HTTPError, URLError) as e:
print(f'Unable to download encoded query at {url}, trying next URL...')
raise ValueError(f'Unable to download encoded query at any known URLs.')
def get_query_iterator(topics_path: str, topics_format: TopicsFormat):
mapping = {
TopicsFormat.DEFAULT: DefaultQueryIterator,
TopicsFormat.KILT: KiltQueryIterator,
}
return mapping[topics_format].from_topics(topics_path)
|