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Merge pull request #46 from DelaramRajaei/main
Merging ReQue and RePair Projects
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| name: repair | ||
| name: Repair | ||
| channels: | ||
| - conda-forge | ||
| - pytorch | ||
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output/toy.msmarco.passage/t5.small.local.docs.query.passage/refiner_param.py
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| import random, os, numpy as np, platform | ||
| import torch | ||
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| random.seed(0) | ||
| torch.manual_seed(0) | ||
| torch.cuda.manual_seed_all(0) | ||
| np.random.seed(0) | ||
| extension = '.exe' if platform.system() == 'Windows' else "" | ||
| os.environ['CUDA_VISIBLE_DEVICES'] = '-1' | ||
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| settings = { | ||
| 'query_refinement': True, | ||
| 'cmd': ['search', 'eval','agg', 'box'], # steps of pipeline, ['pair', 'finetune', 'predict', 'search', 'eval','agg', 'box','dense_retrieve', 'stats] | ||
| 'ncore': 1, | ||
| 't5model': 'small.local', # 'base.gc' on google cloud tpu, 'small.local' on local machine | ||
| 'iter': 5, # number of finetuning iteration for t5 | ||
| 'nchanges': 5, # number of changes to a query | ||
| 'ranker': 'bm25', # 'qld', 'bm25', 'tct_colbert' | ||
| 'batch': None, # search per batch of queries for IR search using pyserini, if None, search per query | ||
| 'topk': 100, # number of retrieved documents for a query | ||
| 'metric': 'map', # any valid trec_eval.9.0.4 metric like map, ndcg, recip_rank, ... | ||
| 'large_ds': False, | ||
| 'treclib': f'"./trec_eval.9.0.4/trec_eval{extension}"', # in non-windows, remove .exe, also for pytrec_eval, 'pytrec' | ||
| 'box': {'gold': 'refined_q_metric >= original_q_metric and refined_q_metric > 0', | ||
| 'platinum': 'refined_q_metric > original_q_metric', | ||
| 'diamond': 'refined_q_metric > original_q_metric and refined_q_metric == 1'} | ||
| } | ||
|
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||
| corpora = { | ||
| 'msmarco.passage': { | ||
| 'index_item': ['passage'], | ||
| 'index': '../data/raw/msmarco.passage/lucene-index.msmarco-v1-passage.20220131.9ea315/', | ||
| 'dense_encoder': 'castorini/tct_colbert-msmarco', | ||
| 'dense_index': 'msmarco-passage-tct_colbert-hnsw', | ||
| 'extcorpus': 'orcas', | ||
| 'pairing': [None, 'docs', 'query'], # [context={msmarco does not have userinfo}, input={query, doc, doc(s)}, output={query, doc, doc(s)}], s means concat of docs | ||
| 'lseq': {"inputs": 32, "targets": 256}, # query length and doc length for t5 model, | ||
| }, | ||
| 'aol-ia': { | ||
| 'index_item': ['title'], # ['url'], ['title', 'url'], ['title', 'url', 'text'] | ||
| 'index': '../data/raw/aol-ia/lucene-index/title/', # change based on index_item | ||
| 'dense_index': '../data/raw/aol-ia/dense-index/tct_colbert.title/', # change based on index_item | ||
| 'dense_encoder':'../data/raw/aol-ia/dense-encoder/tct_colbert.title/', # change based on index_item | ||
| 'pairing': [None, 'docs', 'query'], # [context={2 scenarios, one with userID and one without userID). input={'userid','query','doc(s)'} output={'query','doc(s)'} | ||
| 'extcorpus': 'msmarco.passage', | ||
| 'lseq': {"inputs": 32, "targets": 256}, # query length and doc length for t5 model, | ||
| 'filter': {'minql': 1, 'mindocl': 10} # [min query length, min doc length], after merge queries with relevant 'index_item', if |query| <= minql drop the row, if |'index_item'| < mindocl, drop row | ||
| }, | ||
| 'robust04': { | ||
| 'index': '../data/raw/robust04/lucene-index.robust04.pos+docvectors+rawdocs', | ||
| 'dense_index': '../data/raw/robust04/faiss_index_robust04', | ||
| 'encoded': '../data/raw/robust04/encoded_robust04', | ||
| 'size': 528155, | ||
| 'topics': '../data/raw/robust04/topics.robust04.txt', | ||
| 'prels': '', # this will be generated after a retrieval {bm25, qld} | ||
| 'w_t': 2.25, # OnFields | ||
| 'w_a': 1, # OnFields | ||
| 'tokens': 148000000, | ||
| 'qrels': '../data/raw/robust04/qrels.robust04.txt', | ||
| 'extcorpus': 'gov2', # AdaptOnFields | ||
| 'pairing': [None, None, None], | ||
| 'index_item': [], | ||
| }, | ||
| 'gov2': { | ||
| 'index': '../data/raw/gov2/lucene-index.gov2.pos+docvectors+rawdocs', | ||
| 'size': 25000000, | ||
| 'topics': '../data/raw/gov2/topics.terabyte0{}.txt', # {} is a placeholder for subtopics in main.py -> run() | ||
| 'trec': ['4.701-750', '5.751-800', '6.801-850'], | ||
| 'prels': '', # this will be generated after a retrieval {bm25, qld} | ||
| 'w_t': 4, # OnFields | ||
| 'w_a': 0.25, # OnFields | ||
| 'tokens': 17000000000, | ||
| 'qrels': '../data/raw/gov2/qrels.terabyte0{}.txt', # {} is a placeholder for subtopics in main.py -> run() | ||
| 'extcorpus': 'robust04', # AdaptOnFields | ||
| 'pairing': [None, None, None], | ||
| 'index_item': [], | ||
| }, | ||
| 'clueweb09b': { | ||
| 'index': '../data/raw/clueweb09b/lucene-index.cw09b.pos+docvectors+rawdocs', | ||
| 'size': 50000000, | ||
| 'topics': '../data/raw/clueweb09b/topics.web.{}.txt', # {} is a placeholder for subtopics in main.py -> run() | ||
| 'trec': ['1-50', '51-100', '101-150', '151-200'], | ||
| 'prels': '', # this will be generated after a retrieval {bm25, qld} | ||
| 'w_t': 1, # OnFields | ||
| 'w_a': 0, # OnFields | ||
| 'tokens': 31000000000, | ||
| 'qrels': '../data/raw/clueweb09b/qrels.web.{}.txt', # {} is a placeholder for subtopics in main.py -> run() | ||
| 'extcorpus': 'gov2', # AdaptOnFields | ||
| 'pairing': [None, None, None], | ||
| 'index_item': [], | ||
| }, | ||
| 'clueweb12b13': { | ||
| 'index': '../data/raw/clueweb12b13/lucene-index.cw12b13.pos+docvectors+rawdocs', | ||
| 'size': 50000000, | ||
| 'topics': '../data/raw/clueweb12b13/topics.web.{}.txt', # {} is a placeholder for subtopics in main.py -> run() | ||
| 'trec': ['201-250', '251-300'], | ||
| 'prels': '', # this will be generated after a retrieval {bm25, qld} | ||
| 'w_t': 4, # OnFields | ||
| 'w_a': 0, # OnFields | ||
| 'tokens': 31000000000, | ||
| 'qrels': '../data/raw/clueweb12b13/qrels.web.{}.txt', # {} is a placeholder for subtopics in main.py -> run() | ||
| 'extcorpus': 'gov2', # AdaptOnFields | ||
| 'pairing': [None, None, None], | ||
| 'index_item': [], | ||
| }, | ||
| 'antique': { | ||
| 'index': '../data/raw/antique/lucene-index-antique', | ||
| 'size': 403000, | ||
| 'topics': '../data/raw/antique/topics.antique.txt', | ||
| 'prels': '', # this will be generated after a retrieval {bm25, qld} | ||
| 'w_t': 2.25, # OnFields # to be tuned | ||
| 'w_a': 1, # OnFields # to be tuned | ||
| 'tokens': 16000000, | ||
| 'qrels': '../data/raw/antique/qrels.antique.txt', | ||
| 'extcorpus': 'gov2', # AdaptOnFields | ||
| 'pairing': [None, None, None], | ||
| 'index_item': [], | ||
| }, | ||
| 'trec09mq': { | ||
| 'index': '/data/raw/clueweb09b/lucene-index.cw09b.pos+docvectors+rawdocs', | ||
| 'size': 50000000, | ||
| # 'topics': '../ds/trec2009mq/prep/09.mq.topics.20001-60000.prep.tsv', | ||
| 'topics': '../data/raw/trec09mq/09.mq.topics.20001-60000.prep', | ||
| 'prels': '', # this will be generated after a retrieval {bm25, qld} | ||
| 'w_t': 2.25, # OnFields # to be tuned | ||
| 'w_a': 1, # OnFields # to be tuned | ||
| 'tokens': 16000000, | ||
| 'qrels': '../data/raw/trec09mq/prels.20001-60000.prep', | ||
| 'extcorpus': 'gov2', # AdaptOnFields | ||
| 'pairing': [None, None, None], | ||
| 'index_item': [], | ||
| }, | ||
| 'dbpedia': { | ||
| 'index': '../data/raw/dbpedia/lucene-index-dbpedia-collection', | ||
| 'size': 4632359, | ||
| 'topics': '../data/raw/dbpedia/topics.dbpedia.txt', | ||
| 'prels': '', # this will be generated after a retrieval {bm25, qld} | ||
| 'w_t': 1, # OnFields # to be tuned | ||
| 'w_a': 1, # OnFields # to be tuned | ||
| 'tokens': 200000000, | ||
| 'qrels': '../data/raw/dbpedia/qrels.dbpedia.txt', | ||
| 'extcorpus': 'gov2', # AdaptOnFields | ||
| 'pairing': [None, None, None], | ||
| 'index_item': [], | ||
| }, | ||
| 'orcas': { | ||
| 'index': '../data/raw/orcas/lucene-index.msmarco-v1-doc.20220131.9ea315', | ||
| 'size': 50000000, | ||
| # 'topics': '../data/raw/trec2009mq/prep/09.mq.topics.20001-60000.prep.tsv', | ||
| 'topics': '../data/raw/orcas/preprocess/orcas-I-2M_topics.prep', | ||
| 'prels': '', # this will be generated after a retrieval {bm25, qld} | ||
| 'w_t': 2.25, # OnFields # to be tuned | ||
| 'w_a': 1, # OnFields # to be tuned | ||
| 'tokens': 16000000, | ||
| 'qrels': '../data/raw/orcas/preprocess/orcas-doctrain-qrels.prep', | ||
| 'extcorpus': 'gov2', # AdaptOnFields | ||
| 'pairing': [None, None, None], | ||
| 'index_item': [], | ||
| }, | ||
| } | ||
|
|
||
| # Only for sparse indexing | ||
| anserini = { | ||
| 'path': '../anserini/', | ||
| 'trec_eval': '../anserini/eval/trec_eval.9.0.4/trec_eval' | ||
| } | ||
|
|
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