xpmir/__init__.py,sha256=7YZBGzNyIth1Hr7aE5jmovk5mIFIlMXwoQh99eYxznY,72
xpmir/__main__.py,sha256=6KqEnzHmP023VJE6SlYVhbigNrUxX96N0hMPJvdgfnQ,221
xpmir/_version.py,sha256=CqDGE4B1ZqZ-56mxeOFcXRTmlxrdOh4ayrjbcPjziE4,411
xpmir/compat.py,sha256=iOafmHRTf1fFVgoqnO6hm8xZ50W2Uj5Pw4yLRz1FYZc,193
xpmir/context.py,sha256=11IBZd5SX1p6dEJyN2c5ZCru_TN6jRjJhTESVEzyKqM,1323
xpmir/distributed.py,sha256=xaDchEstJVJ8TvGr3dI48u7wgt8tTFgvr_CSLvJDHUA,3124
xpmir/evaluation.py,sha256=KHvH40-Mwn16eDiQUYXmIIeBG0Tyz6Cehrjar-s4sPo,11124
xpmir/measures.py,sha256=9Ub7JTbiqjJJxsPYi9_WnXOeQSLceyT0xDlZmHKZF0o,1261
xpmir/mkdocs_init.py,sha256=abCRIaZNzRIYm6QTe2Uz9pqc5lu-EcIfuPFlShyGVxA,205
xpmir/models.py,sha256=Ax1D0Zv1-5o4nIUpuAuKUdg6-k4cbi_rBSXoJ3CIv-E,3148
xpmir/configuration/__init__.py,sha256=OHXvRodL-2SBbZa0wf7HFcJ6u6fuzdzhzOwTIa608TY,2002
xpmir/datasets/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/datasets/adapters.py,sha256=ghor-169Awa9HWasFLBiy2MXSiYQgeaWeqQv0zzMv4I,12487
xpmir/dm/__init__.py,sha256=buqtlTmOyRbNxNPeIbKMg_rwgumYpxOLVkFC7i554Kw,137
xpmir/dm/config/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/dm/config/ca/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/dm/config/ca/uwaterloo/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/dm/config/ca/uwaterloo/jimmylin/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/dm/config/ca/uwaterloo/jimmylin/anserini.py,sha256=9QLX8XOvRSGUnMW1ewOu7uefhS4Gj4LqeAcpxF3dHYY,1196
xpmir/dm/config/co/huggingface/datasets/sentence-transformers/msmarco-hard-negatives.py,sha256=I77PIbEa64ulqqkFhrPN032RkBYCgrT8cgqSI98gEwQ,752
xpmir/dm/config/com/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/dm/config/com/github/sebastian-hofstaetter/neural-ranking-kd.py,sha256=e8SQF8Lzt6XMb__c8V5WvjcvgiUdRi5L0_YeADf_guI,2064
xpmir/documents/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/documents/samplers.py,sha256=XDF6k83_hUeYwm-0VsKPi_ykZ3s3uxtquxeXfQ-LyOk,4962
xpmir/index/__init__.py,sha256=CvFPbk8CH-JzAO112BgN3gI2diAK7TMMbHiEbN3Wzjc,57
xpmir/index/anserini.py,sha256=SF230tHYP06zDvD2zI3WsZD_XM41EeUCp6-DU8eBjGg,2238
xpmir/index/faiss.py,sha256=HKXa1jl-UZrkE958OBepjq3rRO1GTw66j-b3LrjtZlg,7723
xpmir/index/sparse.py,sha256=TCTVRCm0zXqbYwuWvqWqOCzu8LKbq-Ln0E7CsgAV2XQ,6832
xpmir/interfaces/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/interfaces/anserini.py,sha256=cdKqOMgfUEYAygcK92OlKcpPTEv-HMlim6QdVmweY70,10689
xpmir/interfaces/apex.py,sha256=DpuzPsUUGcfQG1HMRy8dYuthlDonLURlGAI4qCoAXq0,749
xpmir/interfaces/plaintext.py,sha256=X4h3R_z9rF80P9XCEjC020kpTCgX7GonY6nS4hbtnG8,713
xpmir/learning/__init__.py,sha256=AESHW9jKqK-tSQ2gEPvwNtOBy4RBB9DdgvufJCUIZMA,81
xpmir/learning/base.py,sha256=gkBPOxUm2dgbwfZxN7f3ncJF9zcoEHHX1y0JQMlQBlc,709
xpmir/learning/batchers.py,sha256=iUe37k-v9rRiFi3y-KMc7JlKWlv41UpRLNvYzk24ges,7537
xpmir/learning/context.py,sha256=g9Rv96z6TTtIBvzMFxWlwLZyCY-diVIHRshgOKEfn5Y,8525
xpmir/learning/devices.py,sha256=ry39ue4ne0WqMBjKTBShlPb1WaMavyoTsZEQm1xu7S8,3456
xpmir/learning/hooks.py,sha256=AkyXiv-rr2qiijleqBIqa46XxSS1zLGGoKporktFij4,862
xpmir/learning/learner.py,sha256=4L4RJYhe6MC65OMt5BmFZs3hXWGoSBoi9y5F6dipbHI,12574
xpmir/learning/metrics.py,sha256=F98j8SPutRuZDfU0BFL0rtOOZNH-awsulC04ry_I-fQ,1961
xpmir/learning/optim.py,sha256=XOz-fEb_BrQr_9Jm_1XLfdlfkQOGkzDxn2mGnEQs0Gs,11210
xpmir/learning/parameters.py,sha256=3w2zM5o27XDcifajTCZVbmf88btpTAlPiGGTd1BfH3I,9774
xpmir/learning/schedulers.py,sha256=JWwlk8WBCqhy5cMPGA_GvPzN7nEj7hYKihFeimWEQzg,2126
xpmir/learning/trainers/__init__.py,sha256=WgAszSG9FiBT2yXDq7fXIb47KRRWeKf7L0UH_TO7Ok4,1768
xpmir/learning/trainers/multiple.py,sha256=uh6E011dQRZsFwqIL6FTdp5cf7qGl06Ozj5CiVHiNgM,1426
xpmir/letor/__init__.py,sha256=LxAOM01Ijg0SmpV9qKXOVJ3bVu0c1bWELZ51zedniZc,364
xpmir/letor/learner.py,sha256=_KtJaUBz9kc-LaRAHkQgO_OuzJxhWfegjD501R3oFGw,5787
xpmir/letor/records.py,sha256=8dl3TEichLqlPE7KjmebpVUh3rcarHgbuArEe2z5ee4,12888
xpmir/letor/samplers.py,sha256=cEqQIFYsr1nq7G5O7rrBkQIqlrZeSN5fiG0dskUe4HU,23446
xpmir/letor/distillation/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/letor/distillation/pairwise.py,sha256=aZuSN_7p5JO3DnyjWPp9r9rrcbNmOlP-cnrCn4mSf4I,5113
xpmir/letor/distillation/samplers.py,sha256=U-t7qP5XzTDUNXvEa8jNwO1TEhjOWA4lyhylgdfuG-Y,4788
xpmir/letor/trainers/__init__.py,sha256=mn9ePhS7X9Ml-ogM6J_7AYnQT6lPxy4ioxmVfH7DaHE,2927
xpmir/letor/trainers/batchwise.py,sha256=R2Py4VK9QSYpK-kFUd7hHzaFEeWkswystL1rnDOJCLk,3330
xpmir/letor/trainers/pairwise.py,sha256=1vHq6313hY18L9ewn0LYsq63iBPkwy2cK00iHfs-nas,10300
xpmir/letor/trainers/pointwise.py,sha256=qC6PfSx-r1zp07jDJYRZ35_9XaJfQnj54_R_QUVFTQk,4916
xpmir/metrics/__init__.py,sha256=RbzHFQZGnAOvHkAb5A91YRzffrOi5N-zmhJPWwBmX2M,510
xpmir/mlm/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/mlm/samplers.py,sha256=S3TCvi_KDN6nWSUksm_haiuyhtbtNQHcT3LmaU8mKLE,1975
xpmir/mlm/trainer.py,sha256=4VZ_pyHMjISxNHnhnHQeNMOSth4LVJwKQEjvYLL2R0g,2653
xpmir/neural/__init__.py,sha256=ekGLDnL6Rj970H802PFZiLFUYaktzTBrgTtFGm5jYsk,4020
xpmir/neural/colbert.py,sha256=4CwIlux2zmaQHdbBPHnAixkQvxct_CMUzsGuDA0sLNE,2837
xpmir/neural/common.py,sha256=1EJ0Dvt4pOFY2jcFSxWqtp-NQP6RFcoTmXO9quT_8is,646
xpmir/neural/cross.py,sha256=hlalY3yxYCUv8Ns4DL__Zj1bhjmwHLs8k1_Rlwrpgss,3357
xpmir/neural/dual.py,sha256=RX_XO-KRFfMEvm-01NyzsH8WnyD1U6C98O3S2d62ZEY,7707
xpmir/neural/huggingface.py,sha256=_ZI_OhGFETUZri3zLqg8Mkbos3fP5JFJP06AZPwwrvM,2744
xpmir/neural/jointclassifier.py,sha256=ejBnwZrc1YZ03UDhGeJwv721wpau6G-XFg33tiMwlRA,125
xpmir/neural/splade.py,sha256=zokNa3lnftvZ0r7yVunpmN70hNLpUXIGhY9mb-q1fbI,6262
xpmir/neural/interaction/__init__.py,sha256=yKvXQKxV35TnjiBbEweyZKc6dtwLYTndX7I-PYRyzQc,1920
xpmir/neural/interaction/drmm.py,sha256=EJ_wXIdp8jH4CvJCtMDjnTgJLyvWVvQOX7BcH_kwzvU,5484
xpmir/neural/modules/__init__.py,sha256=ZKxTOA52FNus7wnDGTfOE4SlIUlIoSfPzmbP9j5Rr1Q,249
xpmir/neural/modules/interaction_matrix.py,sha256=iCyTo9bbQwp42xlqq8FiPZJ2_ZETsEdH6yMqIMERg5s,2537
xpmir/neural/modules/rbf_kernels.py,sha256=gTlURc-clVqFq7OjWHby7J1nLsi7L1PDD_bTavLwIsM,1476
xpmir/papers/__init__.py,sha256=iOAdzPCeNcNLPf3zA5i50z41Iqsli4qPnCdJ28nciJY,709
xpmir/papers/cli.py,sha256=iqtdmsn6vWmnZ56Y0Shzi26G1uVY3ge5QYBJa21V5mk,11018
xpmir/papers/results.py,sha256=EAh9Kvs1ZS2PF2bFRJvBC3uDgohk_GxuDLm1KKzvEIo,521
xpmir/papers/duobert/__init__.py,sha256=GaPsU1HSfhmKY0BCB2TaH-8HGfB0Ojwkv99PT-MCNYw,139
xpmir/papers/duobert/configuration.py,sha256=budpFig8xlT8yJTnatyWTnePkL4DnBAiaaK5Q5wNJ88,484
xpmir/papers/duobert/experiment.py,sha256=_U7cv3adWKd5mvTcaFtzV5DeOlum-WoRh6XdOYWdkV0,5277
xpmir/papers/duobert/normal.yaml,sha256=sXqzU9X1sn5VqBwHMY8B-IggQEMMOW-HCk4QTRiLTuc,1244
xpmir/papers/duobert/small.yaml,sha256=mn82rdcfZJSSuthOX3Ezd-GPCnqx1Inr9EA6upIkakY,1078
xpmir/papers/helpers/__init__.py,sha256=Pw3kVIEkXQGHSpMi6zmXtzclXt4DRfdKXK5iSjKTrUo,1376
xpmir/papers/helpers/msmarco.py,sha256=5sbPZaUz00n-Wn02qOl4Hy4QkY0XGtDgT_GR3xGpQ6w,772
xpmir/papers/helpers/optim.py,sha256=Ohv49cfvAplnnFTGw5EbDdeQajnjswGIAx4id9qY56w,2035
xpmir/papers/helpers/samplers.py,sha256=ZIrXQx3Zy_3w_pp8JxrReqElkDqbc2x5gTMujWDwoe8,4770
xpmir/papers/monobert/__init__.py,sha256=upQ3VB0jW2tqQ2p6vVgCzfAOrOH1GHjnHu-c46GfexM,290
xpmir/papers/monobert/configuration.py,sha256=zIvyiaXdwBDUd8GdTZehc7Yv6FNg7nhGocqyaHoK7gY,1464
xpmir/papers/monobert/experiment.py,sha256=bZuBYete81vfNxPF_qg2o3mrrfpaJoRu9DTW9AFhs84,6128
xpmir/papers/monobert/finetune.py,sha256=sdZlDTI231oPElFsUkguFmVYnE7QGT9cLRXfj5FxOaM,6201
xpmir/papers/monobert/normal.yaml,sha256=PFfRrR5F_J8j2xFL2W7Goq_VehL64akwd2pGy6q2Cag,823
xpmir/papers/monobert/small.yaml,sha256=0UHxeFp42hyt5uv5peglPgx1q8sA1q52jSgMf59POU8,899
xpmir/papers/splade/__init__.py,sha256=E5hLeOGS_s9JhvYERBVGah-OUj-y6EUv2EOyPp9f21c,185
xpmir/papers/splade/configuration.py,sha256=33v1JaEQOvHWW7vfEwX2brerGrjnZMOYuKbSuLh8SLQ,2964
xpmir/papers/splade/experiment.py,sha256=xeuy2-B__BMFwyZDPTmyfgkPy0SZPKuBFGEpAV8PFTo,8091
xpmir/papers/splade/normal.yaml,sha256=S38YsFEsbK-yjkf0-VoboA-lACZhBPwzHTlkHP3XrT4,1238
xpmir/papers/splade/normal_DistilMSE.yaml,sha256=nAnrKXEdVnmMnVpajyjpTOABZADX8lyefN6sgkduqJc,1396
xpmir/papers/splade/normal_doc.yaml,sha256=XXM7JPU27OtRKYIDicv6GEi8__LxqYoxzOtt8fewjpc,1118
xpmir/papers/splade/small.yaml,sha256=p1L9ZT7_hHljsrtTSdGJk2Ds--0AcfSyrXbk8ARfP8c,1437
xpmir/rankers/__init__.py,sha256=tagXxiRYBOHMVAhJSGC2dYdn-AvgbdB8Sei8zBc56qg,15319
xpmir/rankers/full.py,sha256=fo_eg5TFGtcZdeWjvi9Qt4-0sfqOqkD9hS-lB7HtyVk,5281
xpmir/rankers/mergers.py,sha256=eY8L4sFkXq-g-jSio3KcXs_ACJ07GSeGx91AugJXfAg,634
xpmir/rankers/standard.py,sha256=7RRgViQUvq_JhiHGJplkpQhF4WFcwekMc88U29YcZgE,348
xpmir/tasks/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/test/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/test/test_documented.py,sha256=g0A6dbw90nA_rEArWUWf2OSuFrt2HXgsTiAQq4Bbn3Y,413
xpmir/test/index/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/test/index/test_faiss.py,sha256=fqh_2m0RUncIz_d2942SN6Cg47KnuX6mUCLzBQ3Pglk,1948
xpmir/test/index/test_sparse.py,sha256=F3X2lTbctckLI8vXizzt7OI9V1PtW7nGTn5PQ_iaR30,4927
xpmir/test/learning/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/test/learning/test_learner.py,sha256=9Gynmb5xd4v9jRHdDRXGaXPPnsYQFes9r2fBKOyAvXM,1384
xpmir/test/learning/test_parameters.py,sha256=uG0wnUpZIXEW-Fesm9hpfugI5A_2BXw37u067mqeCSI,2543
xpmir/test/letor/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/test/letor/test_samplers.py,sha256=yjGFqQhqHY6xu_OCF4D5oH1oPW4xspkreLrDY40HNmI,2388
xpmir/test/letor/test_trainers.py,sha256=kgj2XXhjF_Jbs7h95sZHCM66lxtG7TFhEZfLeEsPxRQ,281
xpmir/test/neural/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/test/neural/test_forward.py,sha256=GlPuKEykyuM9WOXxf0B4OvyiOE0K88VCqJF81962Qig,6254
xpmir/test/rankers/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/test/rankers/test_full.py,sha256=0mtgdOlJmxNG-6EyQ80d408SxQBzOk3hOQmboVTaUhE,3280
xpmir/test/utils/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/test/utils/test_iter.py,sha256=SQvrO64was65Z7237sMtMvjDV1bkmWcIIbu_fQ4AM9c,1397
xpmir/test/utils/utils.py,sha256=mA0Ccct_DR2EuJF6WXq5DsHHRPaVUr_KSXlgBDlJX9g,2941
xpmir/text/__init__.py,sha256=e8yhV1c842mKGlvT2WpqLRx-5gK19vhGwDkp0bZhRSk,50
xpmir/text/encoders.py,sha256=HGEQsBgjHiTz2jQarMUZs2LDFpTBTxIGEsTvKBzguyo,7460
xpmir/text/huggingface.py,sha256=I2UmcyZp8oG1QGBygRPOvdzlWWBhNBdPSmly8QYFavg,19353
xpmir/text/wordvec_vocab.py,sha256=tSKgQ1VNPQQfHyRANDXJeLIQJUHWW8ah4jdgiO5Lx9M,5351
xpmir/tokenization/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/tokenization/align.py,sha256=6FoLQAsOZxjvfNdw0O82h4YrtjK6-iNlyx8muAp_JOI,2139
xpmir/tokenization/tokenizers.py,sha256=pnMOeBO-jWcnovYILa2v5VaEuJvVuzrKfPi7xXP7_KY,218
xpmir/utils/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
xpmir/utils/functools.py,sha256=uWdOsUrQ9ybqBnQH2Z7k8eogxQWMnUXlyE4ZUtTtUdw,370
xpmir/utils/iter.py,sha256=zlaRcWlaaS4yobOD_OO5LgB1erJMSWlVURh7wkHqFfc,8114
xpmir/utils/utils.py,sha256=FqBx8mSjgzj_wybU0PVRql1NAleMwxNKWGRuTbMvDGQ,6403
experimaestro_ir-1.1.0.dist-info/LICENSE,sha256=OXLcl0T2SZ8Pmy2_dmlvKuetivmyPd5m1q-Gyd-zaYY,35149
experimaestro_ir-1.1.0.dist-info/METADATA,sha256=qPD32v36K_b8L-GTfA2Prni-GICkPvLLlcWJya1KXao,4197
experimaestro_ir-1.1.0.dist-info/WHEEL,sha256=Xo9-1PvkuimrydujYJAjF7pCkriuXBpUPEjma1nZyJ0,92
experimaestro_ir-1.1.0.dist-info/entry_points.txt,sha256=MXxYv9eQJb2UkhX0GQXcoOy_8HhfiXo6Wj5y9s4vpbc,96
experimaestro_ir-1.1.0.dist-info/top_level.txt,sha256=U1DgEqzFMrIcWKGUGzOSVvDbOTxqKXFndzf8tOZabjU,6
experimaestro_ir-1.1.0.dist-info/RECORD,,
