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Add reproduction script for "End-to-End Retrieval with Learned Dense …
…and Sparse Representations Using Lucene" (#2317)
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| # Anserini: A toolkit for reproducible information retrieval research built on Lucene | ||
| # | ||
| # 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. | ||
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| import yaml | ||
| from typing import Union, Dict, List, Optional, Any | ||
| import os | ||
| import subprocess | ||
| TOPIC_NAMES = ['msmarco-passage-dev-subset', 'dl19-passage', 'dl20-passage'] | ||
| EVAL_CMD_MAP = { | ||
| 'map': '-m map -c -l 2', # AP | ||
| 'ndcg_cut_10': '-m ndcg_cut.10 -c', # nDCG@10 | ||
| 'recall_1000_msmarco': '-c -m recall.1000', # R@1000 for MS MARCO | ||
| 'recall_1000': '-m recall.1000 -c -l 2', # R@1000 | ||
| 'recip_rank': '-c -M 10 -m recip_rank' # RR@10 | ||
| } | ||
| TOPIC_EVAL_MAP = { | ||
| 'msmarco-passage-dev-subset': ['recip_rank', 'recall_1000_msmarco'], | ||
| 'dl19-passage': ['map', 'ndcg_cut_10', 'recall_1000'], | ||
| 'dl20-passage': ['map', 'ndcg_cut_10', 'recall_1000'] | ||
| } | ||
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| def get_output_run_file_name(topic: str, name: str): | ||
| return f'runs/{topic}_{name}.txt' | ||
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| def get_search_command(model_name: str, cmd_template: str, topics: List[str]): | ||
| outputs = [get_output_run_file_name( | ||
| topic_name, model_name) for topic_name in TOPIC_NAMES] | ||
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| for topic, output in zip(topics, outputs): | ||
| cmd = cmd_template.format(topic=topic, output=output) | ||
| yield cmd | ||
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| def get_eval_command(param: str, qrel: str, run_file: str, cmd_template: str): | ||
| cmd = cmd_template.format( | ||
| param=param, qrel=qrel, output=run_file) | ||
| yield cmd | ||
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| def main(config): | ||
| # print all search commands | ||
| for model_name, model_config in config['collections'].items(): | ||
| print("running model: ", model_name) | ||
| # # search | ||
| # for cmd in get_search_command(model_name, model_config['search_command'], model_config['topics']): | ||
| # p = subprocess.Popen( | ||
| # cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) | ||
| # stdout, stderr = p.communicate() | ||
| # if stderr: | ||
| # print(stderr.decode('utf-8')) | ||
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| # eval | ||
| expected_results = model_config['results'] | ||
| run_files = [get_output_run_file_name( | ||
| topic_name, model_name) for topic_name in TOPIC_NAMES] | ||
| eval_cmd = model_config['eval_command'] | ||
| metric_precision = model_config['metric_precision'] | ||
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| for run_file, topic_name, qrel in zip(run_files, TOPIC_NAMES, model_config['qrels']): | ||
| for metric in TOPIC_EVAL_MAP[topic_name]: | ||
| for cmd in get_eval_command(EVAL_CMD_MAP[metric], qrel, run_file, eval_cmd): | ||
| p = subprocess.Popen( | ||
| cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) | ||
| stdout, stderr = p.communicate() | ||
| stdout = [out.strip() | ||
| for out in stdout.decode('utf-8').split('\t')] | ||
| actual_result = round(float(stdout[-1]), metric_precision) | ||
| expected_result = expected_results[topic_name][metric] | ||
| assert actual_result == expected_result, f'{model_name} {topic_name} {metric} {actual_result} != {expected_result}, expected: {expected_results[topic_name]}' | ||
| print( | ||
| f"{topic_name} {metric} {actual_result} == {expected_result}") | ||
| print(f"{model_name} passed!") | ||
| print("="*50) | ||
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| if __name__ == '__main__': | ||
| with open('src/main/resources/e2e_sparse_dense_lucene/pre-encoded.yaml') as f: | ||
| config = yaml.load(f, Loader=yaml.FullLoader) | ||
| main(config) |
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src/main/resources/e2e_sparse_dense_lucene/pre-encoded.yaml
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| --- | ||
| collections: | ||
| bm25: | ||
| name: bm25 | ||
| search_command: target/appassembler/bin/SearchCollection -index msmarco-v1-passage -topicReader TsvInt -topics {topic} -output {output} -bm25 -parallelism 12 | ||
| topics: | ||
| - tools/topics-and-qrels/topics.msmarco-passage.dev-subset.txt | ||
| - tools/topics-and-qrels/topics.dl19-passage.txt | ||
| - tools/topics-and-qrels/topics.dl20.txt | ||
| qrels: | ||
| - tools/topics-and-qrels/qrels.msmarco-passage.dev-subset.txt | ||
| - tools/topics-and-qrels/qrels.dl19-passage.txt | ||
| - tools/topics-and-qrels/qrels.dl20-passage.txt | ||
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| eval_command: tools/eval/trec_eval.9.0.4/trec_eval {param} {qrel} {output} | ||
| results: | ||
| msmarco-passage-dev-subset: | ||
| recip_rank: 0.184 | ||
| recall_1000_msmarco: 0.853 | ||
| dl19-passage: | ||
| map: 0.301 | ||
| ndcg_cut_10: 0.506 | ||
| recall_1000: 0.750 | ||
| dl20-passage: | ||
| map: 0.286 | ||
| ndcg_cut_10: 0.480 | ||
| recall_1000: 0.786 | ||
| metric_precision: 3 | ||
| cosdpr-distil: | ||
| name: cosdpr-distil | ||
| search_command: target/appassembler/bin/SearchHnswDenseVectors -index msmarco-v1-passage-cos-dpr-distil -topicReader TsvInt -topics {topic} -output {output} -generator VectorQueryGenerator -topicField title -threads 12 -hits 1000 -efSearch 1000 -encoder CosDprDistil | ||
| topics: | ||
| - tools/topics-and-qrels/topics.msmarco-passage.dev-subset.txt | ||
| - tools/topics-and-qrels/topics.dl19-passage.txt | ||
| - tools/topics-and-qrels/topics.dl20.txt | ||
| qrels: | ||
| - tools/topics-and-qrels/qrels.msmarco-passage.dev-subset.txt | ||
| - tools/topics-and-qrels/qrels.dl19-passage.txt | ||
| - tools/topics-and-qrels/qrels.dl20-passage.txt | ||
| eval_command: tools/eval/trec_eval.9.0.4/trec_eval {param} {qrel} {output} | ||
| results: | ||
| msmarco-passage-dev-subset: | ||
| recip_rank: 0.389 | ||
| recall_1000_msmarco: 0.975 | ||
| dl19-passage: | ||
| map: 0.466 | ||
| ndcg_cut_10: 0.725 | ||
| recall_1000: 0.822 | ||
| dl20-passage: | ||
| map: 0.487 | ||
| ndcg_cut_10: 0.703 | ||
| recall_1000: 0.852 | ||
| metric_precision: 3 | ||
| splade-pp-ed: | ||
| name: splade-pp-ed | ||
| search_command: target/appassembler/bin/SearchCollection -index msmarco-v1-passage-splade-pp-ed -topicReader TsvInt -topics {topic} -output {output} -impact -pretokenized -parallelism 12 -encoder SpladePlusPlusEnsembleDistil | ||
| topics: | ||
| - tools/topics-and-qrels/topics.msmarco-passage.dev-subset.txt | ||
| - tools/topics-and-qrels/topics.dl19-passage.txt | ||
| - tools/topics-and-qrels/topics.dl20.txt | ||
| qrels: | ||
| - tools/topics-and-qrels/qrels.msmarco-passage.dev-subset.txt | ||
| - tools/topics-and-qrels/qrels.dl19-passage.txt | ||
| - tools/topics-and-qrels/qrels.dl20-passage.txt | ||
| eval_command: tools/eval/trec_eval.9.0.4/trec_eval {param} {qrel} {output} | ||
| results: | ||
| msmarco-passage-dev-subset: | ||
| recip_rank: 0.383 | ||
| recall_1000_msmarco: 0.983 | ||
| dl19-passage: | ||
| map: 0.505 | ||
| ndcg_cut_10: 0.731 | ||
| recall_1000: 0.873 | ||
| dl20-passage: | ||
| map: 0.500 | ||
| ndcg_cut_10: 0.720 | ||
| recall_1000: 0.900 | ||
| metric_precision: 3 |
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