[opengm] annotated tag debian/2.3.6+20160814-1 created (now be14bec)

Ghislain Vaillant ghisvail-guest at moszumanska.debian.org
Thu Sep 1 09:19:42 UTC 2016


This is an automated email from the git hooks/post-receive script.

ghisvail-guest pushed a change to annotated tag debian/2.3.6+20160814-1
in repository opengm.

        at  be14bec   (tag)
   tagging  4e9c1d97d92f9a48aa7debb52f9792cfee3890b5 (commit)
  replaces  debian/2.3.6+20160131-2
 tagged by  Ghislain Antony Vaillant
        on  Wed Aug 31 09:34:01 2016 +0100

- Log -----------------------------------------------------------------
opengm Debian release 2.3.6+20160814-1
-----BEGIN PGP SIGNATURE-----
Version: GnuPG v1

iQIcBAABAgAGBQJXxpZ5AAoJENaAXmdHcqR4UP0QAJmja/50JKtDAyepB0Fnej5m
FmfBZVHl2ldXj6CDukPq4Tg748wh+GGwiWkHWuqn9qayi4+2n6okuni93DQxiK1K
YaYSVchmFQ8vuC8dJMtRWfww7vEnS+qCNF5LOJ8l2ZNYfQRRtqCQTrrwW2mUd/yk
NP/ywjIQsnpgUyYrf5gyBvgWFPB7EqT3q6NsrwtQnAI6bkkPz+j6ZuJaJeiSDcPt
MMULUS34VA4VRlwurui08KEX2r2fKnVaQGOBPw0jy4XPupDqHNOR+4LjiqaizJdM
/oR9yLNg+rrSjcK/QOgxG+MP5w/EZJnku1Nul9QQ5ths1qa67eee/yQDTlL33rq8
4VVkeuPUCcmFurg9v9SpXMkwxzzdKnFTSH6kHw2kvZxS88yM3dy6j0rOvFX88ZMK
PjjeAu0IZwewAr27KhpHMN0OR11G6bY1tOsqkgQl1xcVQMCglNGL9T7V+RXy+XCW
AdHEFOkE3CjG8yKB1uP+JxsNt3V2pKYvoGENHtAOTwW9a6PO2F+CfL67OBhhsrAr
DuSNHtt2tP8B7+rM2yaGRu6tepSTT74kLLhxTQjz1bwH2o/TahpWNSbR43zFHn7O
0HWfGoNKoFcyn7hNe6MMxyeOV7RN5UsgJRSrSe+oOTT2oKz6QEU5QbMH8lmE1jq5
rDM7Z5ZBgyZgAGSW5BVF
=4hk2
-----END PGP SIGNATURE-----

Carsten Haubold (33):
      Fix gurobi library dependency include for tests
      Rename opengm::Parameters (aka ModelParameters) for learning to opengm::learning::Weights, and graphicalmodel/parameters.hxx to graphicalmodel/weights.hxx
      Fix header include guard for weights
      fix learnablefunction renaming, method was called "paramaterGradient"...
      Add generalized hamming loss with small test
      Add cplex backend for quadratic solver. Compile learning test if cplex or gurobi is available.
      Merge commit '4c4667669a21f362e693c66fd2bfe38a7f303771'
      Introducing loss parameters
      Fix call operator of sum of experts which did not use the mapping of local to global weight indices yet.
      Remove unnecessary write to labelOffset_ in LUnary constructor
      Make sumOfExperts available from Python
      Remove Loss from StructMaxMargin template parameters. Update parameter object, and actually pass it to the optimizer. Use infParameter in Oracle. Use Gurobi OR Cplex as INF in test.
      bring StructMaxMargin learner to python. needed inlining of all bundle optimizer methods.
      use #ifdef instead of #if in test_learning.cxx
      Add visitor that defines the learn methods for each Learner and all Inference methods.
      Update real world example, add Cplex to available inference methods for solvers.
      Link opengm python learning module against CPLEX and/or Gurobi
      Fix tests after learnablefunction.hxx and l_potts.hxx were removed (but probably still present in installation destination of some developers)
      Update dataset constructor on python side to set up the weights vector as well
      Store best weight vector in dataset when done.
      Adapt python wrapper to changes in struct max margin learner
      Update structure of maxLikelihood. Export to python, run from real example 2
      Embarassingly simple example: one-variable model, with max likelihood learning
      Only build SelfFusion if QPBO is enabled
      Find package OpenMP and build the subgradient ssvm test with those flags set
      Allow to build SubrgradientSSVM without OpenMP, and link the learning python module against openmp
      Merge branch 'master' of bitbucket.org:jkappes/opengm-learning
      some learning python tests
      Add RebindGM to LPCplex2 so that it can be used for structured learning
      Fix an #elif statement to find the cplex backend for the struct-max-margin solver
      Add LpGurobi2::RebindGm to allow learning with Gurobi solver
      Use IndexType instead of UInt16 in LearnableUnary, to allow large numbers of features
      Also install header files with extension .h -- needed for structured learning solvers

Constantin Pape (1):
      Intersection Based and 3-cycles

DerThorsten (122):
      learnable functions in python seems to work
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      learnable functions in python seems to work
      setting initial values from numpy array works
      added lunary to python
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      new learning module
      mychanges
      merged
      added const to param ref in grid search learner
      inital version of grid search learner in python
      BAZINGA bitches, its working
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      added py helper function
      improved python learning
      improved python learning
      fudwefrew
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      python
      python loss param object
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      i am so lazy, i do not write proper commit messages
      bla
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      improved lunary to remove number of parameters
      improved lunary
      changed loss interface
      removed wrapped functions which will not work anyway...
      removed unused header
      changed loss interface (+2 squashed commits)
      lunary
      lunary
      fubar
      new example
      more learners can be used
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      mychanges
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      changes
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      fixed bug in gridesearchlearning
      batch function gen for lpotts
      batch function gen for lpotts
      batch function gen for lpotts
      -impmeneted batch adding of python learnable functions, NICE AS FUCK!
      started to add rebing to all inference methods
      fixed class vs struct bug
      implemnted rebind for for almost all inference methods
      implemented structured perceptron
      loss graphical model type can now be specified in the dataset but has a meaningfull default templatization
      better struct. perceptron
      better struct. perceptron
      implemented subgradient ssvm
      fixed bugs...
      new dataset, way
      fixed minor bugs in examples
      fixed minor bugs in examples
      fixed stupid bugs
      fixed stupid bugs
      new stuff
      fixed major bug in editabledataset.hxx
      fixed bug i introduced
      my local changes:
      merged
      added new dataset to python
      minor stuff
      added missing file
      bazinga
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning
      bazinga
      added isPotts overload to potts function
      minor changes
      bazinga
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning
      implemented py wrapper for maxlh-learning
      fubar
      added weight constraints and weight regularizer to dataset
      superpixel dataset creator
      minor improvements
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning
      temp. disabled learn method from ml-learning in python binding
      temp. disabled learn method from ml-learning in python binding
      temp. disabled learn method from ml-learning in python binding
      removed weight regularzier from ds (stupid idead of me to put it there)
      made pyMh-learn build again
      fixed h5 bugs
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning
      minor changes
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning
      learning changes
      seems to be working
      minor fix
      removed deprecated function
      most certainly fixed bugs
      max. lh learning test less time consuming
      outsmarting travis
      outsmarting travis
      update struct. perceptron
      update struct. perceptron
      update struct. perceptron
      fixed that shit
      fixed that shit
      fixed that shit
      defined CI to detect travis
      give travis another shot
      udpated readme
      changed travis script
      updated travis
      updated travis
      removed learning
      removed lfunctions
      removed py learning
      removed learning wip
      fixed fusion for cc
      fixed include guards and WITH_*** problems for intersection based
      fixing travis wip
      fixing travis wip
      trying hdf5 serial version
      added different boost sources in travis
      chaged find hdf5 script

Francesco Biscani (2):
      Tentative fix for a memory leak in fast_sequence.hxx.
      Disable a check in the test that results in an out-of-bounds access.

Ghislain Antony Vaillant (7):
      Merge tag 'v2.3.6+20160814' into debian/master
      Update patch queue.
      Bump standards version to 3.9.8, no changes required.
      Drop build of examples.
      Skip usage of RPATH with CMake.
      Assorted enhancements to rules file:
      Release to unstable.

Jan Funke (27):
      replaced REDME.md content with TODO list
      added test-learning, added scaffolds for bundle-optimizer and struct-max-margin, fixed compile errors in hammingloss and testdataset
      checkin of linear and quadratic solver and Gurobi backend for learning
      bundle-optimizer: added setup of QP
      added Oracle stub to opengm/learning
      fixed operator[] for opengm::Weights
      finished bundle method implementation
      added *.swp to .gitignore
      renamed opengm::{Paramters -> Weights} in bundle method
      finished implementation (not testing) of StructMaxMargin
      fixed gradient computation in struct-max-margin, re-enabled test
      use trws in test-learning
      embarrassing bug fix in bundle method
      Merge remote-tracking branch 'opengm/master'
      bugfix: iterator was not dereferenced in sum_of_experts
      bugfix: gradient-accumulator needs to pass local configuration to function
      added embarrassingly simple dataset
      updated test_learning
      fixed testdatasets
      removed debug code from gradient-accumulator
      fixed test_gridsearch_learner
      re-enabled all testdatasets in test_learning
      bugfix: GradientAccumulator is not supposed to initialize gradient with zero
      use multiple models in test_learning
      struct-max-margin: set data-weights only once for all models
      added debug output to bundle-optimizer
      added EpsStrategy parameter to bundle method

Janez Ales (26):
      maximum likelihood files
      New version for review
      With likelihood function.
      Change in eta.
      Latest test.
      No boundaries on the parameter, start at origin.
      renamed file: pyMaxLikelihoodLearner.cxx
      WeightGradientFunctor global weight indexing (error) changed to local weight indexing.
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning into maximum_likelihood
      Belief Propagation parameters added to learner.
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning into maximum_likelihood
      All parameters added.
      isActive added to the belief propagation parameters
      RebindGm added to LPCplex2
      lweighted sum of functions calls operator() on Marray with proper indices for dimension =2 (and 1)
      corrects indexing call from a learnable function.weightGradient to a multidimensional marray (*begin ---> begin)
      add model print out in struct-max-margin iteration
      lweightedsum_of_functions OPENGM_ASSERT corrected
      adding normalized weights print output (only for check of convergence - not to be used in calculation)
      paralellization added to struct-max-margin (triggered by WITH_OPENMP)
      removed redundant print info
      Merge branch 'learning-experimental' of https://github.com/ilastikdev/opengm-1 into structured_learning_2
      verbose=false implemented in more detail
      Merge branch 'learning-experimental' of https://github.com/opengm/opengm into structured_learning_2
      Merge branch 'master' of https://github.com/opengm/opengm into structured_learning_2
      commented out code removed

Jeffrey Yunes (2):
      Added logsumexp op for log semiring (to work in log space for sum product alg)
      Python bindings for log semiring

Joerg Kappes (57):
      bugfixes and empty test for learnable functions
      add test and learnable potts function
      Merge branch 'master' of https://github.com/joergkappes/opengm-learning
      start refactoring dataset
      Merge branch 'master' of https://github.com/joergkappes/opengm-learning
      Merge branch 'master' of https://github.com/joergkappes/opengm-learning
      now models with loss are created too
      Merge branch 'master' of https://github.com/joergkappes/opengm-learning
      start refactoring datasets
      reduce default testset size
      change sign of loss in lossargumented model
      adopt test to change in addloss
      move test
      modify cmakefiles after move
      add missing resize
      bugfix datasets
      Merge branch 'master' of https://github.com/joergkappes/opengm-learning
      add new  acyclic testdataset
      Update lweightedsum_of_functions.hxx
      Merge pull request #374 from chaubold/fix-lpcplex2-rebindgm
      Merge pull request #375 from chaubold/fix-solver-check-SSVM
      Merge pull request #376 from chaubold/fix-lpgurobi-rebindgm
      Merge pull request #378 from chaubold/fix-lunary-uint16
      Update README.md
      Update README.md
      Update README.md
      Merge pull request #400 from ilastikdev/structured_learning_2
      Merge pull request #104 from opengm/master
      fix problems with VS 2010
      Merge pull request #422 from ilastikdev/structured_learning_2
      Merge pull request #425 from chaubold/fix-header-patterns-when-installing
      Merge pull request #442 from svenpeter42/master
      disable mem-logging by default, because it might not work on all systems
      Merge pull request #438 from bluescarni/partitions_test_fix
      add libhdf5 to travis
      Merge branch 'master' of https://github.com/opengm/opengm
      add libhdf5-serial-dev to travis
      add hdf5 for osx to travis
      add hdf5 for osx to travis
      add hdf5 for osx to travis (next try)
      fix wrong namespace
      Merge pull request #105 from opengm/master
      Merge pull request #450 from joergkappes/master
      disable python on osx for travis
      Merge pull request #436 from bluescarni/memory_leak_fix
      Update README.md
      Merge pull request #106 from opengm/master
      merge changes on inference methods from learning branch
      merge changes on inference methods from learning branch
      some python fixes
      Merge pull request #467 from joergkappes/master
      merge changes for functions and graphical model from the learning branch
      merge changes for functions and graphical model from the learning branch
      Merge pull request #470 from joergkappes/master
      merging changes from learning-branch into master
      Merge pull request #471 from joergkappes/master
      Merge pull request #469 from yunesj/log_semiring

Steffen-Wolf (15):
      add: unit test for dataset structure
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      add: test for max margin learning that reproduces
      make arguments of pushBackInstance in EditableDataset const
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      fixed: resize count_ and isCached_ vector for EditableDataset
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      add: new test to test_learning
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      fix: added lossParams_ to  editabletestdataset constructor
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      fix: change SumOfExperts to LSumOfExperts

Sven Peter (2):
      undo dirty pull request revert hack
      Revert "Merge pull request #423 from opengm/learning-experimental"

Thorsten B (11):
      Merge pull request #9 from opengm/master
      Merge pull request #419 from consti123/master
      Merge pull request #423 from opengm/learning-experimental
      Merge pull request #10 from opengm/master
      Merge pull request #413 from DerThorsten/master
      Merge pull request #426 from DerThorsten/master
      Merge pull request #427 from DerThorsten/master
      Merge pull request #428 from DerThorsten/master
      Merge pull request #429 from DerThorsten/master
      Merge pull request #430 from DerThorsten/master
      Merge pull request #431 from DerThorsten/master

Thorsten Beier (3):
      hotfix
      huthut
      Revert "huthut"

joergkappes (51):
      prototype for learnable functions with features
      add I/O for LPotts
      add LPotts IO-test and do bugfixes
      add directory structure for learning
      typos
      add interface for learnable functions
      start hammingloss
      prototypical implementation for loss and learning, befor adding unittests some interfaces need to be specified
      todos
      add dumydataset - untested
      syntax checking and bugfixes
      add typedef and make it larger
      add missing return value
      now this solver do grid search learning (todo: rename file)
      add couts
      write test for grid search learning(todo: rename this file)
      formating
      renaming
      comments
      Merge branch 'master' of https://github.com/joergkappes/opengm-learning
      add second test-dataset (with 3 parameters) and add it to greidsearch test
      change noise in datasets
      save and load datasets for learning
      add missing file for dataset-io
      make it compileable
      fix bug in deserialization of lpotts
      comment out test that does not stop
      change to new testmodels
      fix CMameFile for test
      bugfix
      update cmakelists
      add output
      first bugfixes for maxlikelihoodlearning - need more
      remove code from mll
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning
      refactor  WeightGradientFunctor
      reimplement mll
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning
      change to reimplemeted mll - test-learning and test-subgradient-ssvm fails
      update mll
      comment unet test out - jan/Thorsten plz check this
      add temperature to mll
      reduce test to shorter time
      add second dataset to mll test
      Typo in cmakelist
      some minor fixes
      Merge branch 'master' of https://bitbucket.org/jkappes/opengm-learning
      fix parameter rebind
      add Multicut
      add learning code (experimental)
      fix ambiguities in names

mschiegg (25):
      rename argument, add missing include
      rename gt to gts and add another dataset constructor
      add editable dataset and its python wrappers
      introduce default LossParameter
      remove unnecessary include
      bring dataset IO to python and link against HDF5
      changing id of sum_of_experts
      adding more safeguards
      sumOfExperts serialization still to be debugged
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      added loss serialization; test-dataset-io still fails for sum of experts
      sumOfBi...Experts serialization fixed
      breaks all tests. Revert "removed wrapped functions which will not work anyway..."
      breaks all tests. Revert "changed loss interface"
      remove obsolete test datasets
      remove obsolete learnable functions
      renamed sum_of_experts to lsum_of_experts for consistency
      make weights_ mutable to be able to deserialize with function functor
      Merge branch 'master' of github.com:joergkappes/opengm-learning
      colon missing
      implemented getLoss for dataset and almost brought it to python, still to be fixed: pyDataset
      python scripts to convert the pystruct pascal VOC dataset to openGM format and learn
      fix ifdef
      fixed python wrapping, with @Steffen-Wolf
      fixed loss return

opengm (2):
      Update README.md
      Merge pull request #399 from ilastikdev/structured_learning_2

-----------------------------------------------------------------------

No new revisions were added by this update.

-- 
Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/debian-science/packages/opengm.git



More information about the debian-science-commits mailing list