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Created with Raphaël 2.2.024Apr14Feb729Oct6Sep23Aug22Jul20Jun614May87614Feb26Sep17Jul611Apr911Feb522Jan21201615Sep543Aug219Jul76512Jun96130May281714Feb111016Jan1411435Dec15Oct5426Sep2315Aug13Jul31May2611Apr54Mar26Feb23Jan22212018Dec161110330Nov261928Aug16Jul151413116Jun22May212018121187624Mar131296543128Feb26241918171110765432131Jan3029282726232219181514131226Dec1511954327Nov21206429Oct2415Sep141242128Aug27222124Jun2327May262322Pickling ISV BaseTemporally add bob.pipelines as dependency [conda]Removed unecessary moduleMaking GMMMachine picklableIncreased latest version to 2.1.6b0 [skip ci]Increased stable version to 2.1.5v2.1.5v2.1.5add debugging messagesbob_em_trainbob_em_trainIncreased latest version to 2.1.5b0 [skip ci]Increased stable version to 2.1.4v2.1.4v2.1.4Merge branch 'issue-31' into 'master'Fixing possible issue with numpy.ndarray.resizeImprovements to the em train scriptFix the import for the moved functionIncreased latest version to 2.1.4b0 [skip ci]Increased stable version to 2.1.3v2.1.3v2.1.3Add a bob em train script which works on SGEMerge branch 'multiprocessing' into 'master'Implemented TV in parallelTurn nitpicky back onbump versionAutomatically create threadpool and allow custom trainersTested kmeans parallelFix error on numpy zero creationFix broken elseMerge branch 'multiprocessing' of gitlab.idiap.ch:bob/bob.learn.em into multiprocessingFixed GIL issueMachines are not thread safe?The data can be GMMStats not just numpy arraysAdd input checks back and enable testsWorking out with GILMerge branch 'multiprocessing' of gitlab.idiap.ch:bob/bob.learn.em into multiprocessingDoing EM with multiprocessingTrial to implement EM with multiprocessing[ci] Update gitlab-ci file (depend on bob/bob.devtools) [ci skip]Disable Sphinx nitpicky and disable Python 2 [skip ci]Increased latest version to 2.1.3b0 [skip ci]Increased stable version to 2.1.2v2.1.2v2.1.2[sphinx] Fixed doctestsIncreased latest version to 2.1.2b0 [skip ci]Increased stable version to 2.1.1v2.1.1v2.1.1