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# | |
# 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 argparse | |
import math | |
import os | |
import subprocess | |
import time | |
from collections import defaultdict | |
from string import Template | |
import yaml | |
from scripts.repro_matrix.defs_miracl import models, languages, trec_eval_metric_definitions | |
from scripts.repro_matrix.utils import run_eval_and_return_metric, ok_str, okish_str, fail_str | |
def print_results(metric, split): | |
print(f'Metric = {metric}, Split = {split}') | |
print(' ' * 35, end='') | |
for lang in languages: | |
print(f'{lang[0]:3} ', end='') | |
print('') | |
for model in models: | |
print(f'{model:33}', end='') | |
for lang in languages: | |
key = f'{model}.{lang[0]}' | |
print(f'{table[key][split][metric]:7.3f}', end='') | |
print('') | |
print('') | |
def extract_topic_fn_from_cmd(cmd): | |
cmd = cmd.split() | |
topic_idx = cmd.index('--topics') | |
return cmd[topic_idx + 1] | |
if __name__ == '__main__': | |
parser = argparse.ArgumentParser(description='Generate regression matrix for MIRACL.') | |
parser.add_argument('--skip-eval', action='store_true', default=False, help='Skip running trec_eval.') | |
args = parser.parse_args() | |
start = time.time() | |
table = defaultdict(lambda: defaultdict(lambda: defaultdict(lambda: 0.0))) | |
with open('pyserini/resources/miracl.yaml') as f: | |
yaml_data = yaml.safe_load(f) | |
for condition in yaml_data['conditions']: | |
name = condition['name'] | |
eval_key = condition['eval_key'] | |
cmd_template = condition['command'] | |
cmd_lst = cmd_template.split() | |
print(f'condition {name}:') | |
lang = name.split('.')[-1] | |
is_hybrid_run = 'hybrid' in name | |
for splits in condition['splits']: | |
split = splits['split'] | |
if is_hybrid_run: | |
hits = int(cmd_lst[cmd_lst.index('--k') + 1]) | |
else: | |
hits = int(cmd_lst[cmd_lst.index('--hits') + 1]) | |
print(f' - split: {split}') | |
runfile = f'runs/run.miracl.{name}.{split}.top{hits}.txt' | |
if is_hybrid_run: | |
bm25_output = f'runs/run.miracl.bm25.{lang}.{split}.top{hits}.txt' | |
mdpr_output = f'runs/run.miracl.mdpr-tied-pft-msmarco.{lang}.{split}.top{hits}.txt' | |
if not os.path.exists(bm25_output): | |
print(f'Missing BM25 file: {bm25_output}') | |
continue | |
if not os.path.exists(mdpr_output): | |
print(f'Missing mDPR file: {mdpr_output}') | |
continue | |
cmd = Template(cmd_template).substitute(split=split, output=runfile, bm25_output=bm25_output, mdpr_output=mdpr_output) | |
else: | |
cmd = Template(cmd_template).substitute(split=split, output=runfile) | |
# In the yaml file, the topics are written as something like '--topics miracl-v1.0-ar-${split}' | |
# This works for the dev split because the topics are directly included in Anserini/Pyserini. | |
# For this training split, we have to map the symbol into a file in tools/topics-and-qrels/ | |
# Here, we assume that the developer has cloned the miracl repo and placed the topics there. | |
if split == 'train': | |
cmd = cmd.replace(f'--topics miracl-v1.0-{lang}-{split}', | |
f'--topics tools/topics-and-qrels/topics.miracl-v1.0-{lang}-{split}.tsv') | |
if not os.path.exists(runfile): | |
print(f' Running: {cmd}') | |
rtn = subprocess.run(cmd.split(), capture_output=True) | |
stderr = rtn.stderr.decode() | |
if '--topics' in cmd: | |
topic_fn = extract_topic_fn_from_cmd(cmd) | |
if f'ValueError: Topic {topic_fn} Not Found' in stderr: | |
print(f'Skipping {topic_fn}: file not found.') | |
continue | |
for expected in splits['scores']: | |
for metric in expected: | |
if not args.skip_eval: | |
# We have the translate the training qrels into a file located in tools/topics-and-qrels/ | |
# because they are not included with Anserini/Pyserini by default. | |
# Here, we assume that the developer has cloned the miracl repo and placed the qrels there. | |
if split == 'train': | |
qrels = f'tools/topics-and-qrels/qrels.{eval_key}-train.tsv' | |
else: | |
qrels = f'{eval_key}-{split}' | |
score = float(run_eval_and_return_metric(metric, qrels, | |
trec_eval_metric_definitions[metric], runfile)) | |
if math.isclose(score, float(expected[metric])): | |
result_str = ok_str | |
# Flaky tests | |
elif (name == 'mdpr-tied-pft-msmarco.hi' and split == 'train' | |
and math.isclose(score, float(expected[metric]), abs_tol=2e-4)) or \ | |
(name == 'mdpr-tied-pft-msmarco-ft-all.ru' | |
and split == 'dev' and metric == 'nDCG@10' | |
and math.isclose(score, float(expected[metric]), abs_tol=2e-4)) or \ | |
(name == 'bm25-mdpr-tied-pft-msmarco-hybrid.te' | |
and split == 'train' and metric == 'nDCG@10' | |
and math.isclose(score, float(expected[metric]), abs_tol=2e-4)) or \ | |
(name == 'bm25-mdpr-tied-pft-msmarco-hybrid.zh' | |
and split == 'dev' and metric == 'nDCG@10' | |
and math.isclose(score, float(expected[metric]), abs_tol=2e-4)): | |
result_str = okish_str | |
else: | |
result_str = fail_str + f' expected {expected[metric]:.4f}' | |
print(f' {metric:7}: {score:.4f} {result_str}') | |
table[name][split][metric] = score | |
else: | |
table[name][split][metric] = expected[metric] | |
print('') | |
for metric in ['nDCG@10', 'R@100']: | |
for split in ['dev', 'train']: | |
print_results(metric, split) | |
end = time.time() | |
print(f'Total elapsed time: {end - start:.0f}s') | |