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Created with Raphaël 2.2.027Jul7224Jun23191817161512329May27262215141211108765432130Apr26242031Mar3029272625242321201918171610227Feb262422171073Jan13Nov29Oct1612Sep7Aug21Jun7614Feb9Oct26Sep31Aug2719Jul13121097328Jun2726222120765430May232218171615129743130Apr26252423201918161312111096526Mar20161211109127Feb2522212015119524Jan16103222Dec5428Nov27171413109876326Oct25242320191611109528Sep26228730Aug292825242330Jul2827262120191817147623Jun13127652129May282422181512119828Apr2445327Feb2523209876126Jan23Created the function is_checkpointedUsed the new DelayedSampleSetAdded vanilla-biometrics baselinescheckpointing scores using joblib[black]Implemented a mechanism to get the partition_sizeChanged checkpointing of the scoresFixed major issue with the ZTNorm checkpointingImproved the checkpointingPossible split between bioalgorithm_dir and transform dirMerge branch 'redoing-baselines' into 'dask-pipelines'Finished the app compare samplesAdded tabulate as dependencyChanged the default behaviour forComparison appCleaning up vanilla biometricsCleaning up ZTNormCleaning up vanilla biometricsCreated a wrapper that wraps vanilla biometrics pipelines to checkpointin.Created a getter and a setter for the BioAlgorithmLegacy.base_dir and fixed an issue during the scoringCreated checkpoint wrapper[black]Merge branch 's-norm' into 'dask-pipelines'Merge branch '134-check_existence-flag-incorrectly-handled-in-filelistdatabase-query' into 'master'Correctly handled check_existence flag in original_file_nameAdded method .fit in the legacy preprocessorImplemented the top-norm score normalizationSegmenting the scores and biometric references checkpoints by group to avoid too many files in one directoryImplemented S-Norm score normalizationMerge branch 'score-normalizations' into 'dask-pipelines'Polishing score serialization. It's impossible to do it in HDF5Polishing ZT-NormChaged the post-processing mechanism[py] Added missing argument in preprocess wrapperfix-annotationsfix-annotationsChanged the standard deviation function to get the same output as bob.learn.em.ztnormMerge branch 'vstack_features' into 'dask-pipelines'Finished ZTNormalizationImplemented ZTNorm for the CheckpointWrapperReturned all scores in the ZNorm __call__Got it right the paralellization of ZT-Norm computation
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