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Recent Releases of autopytorch

autopytorch - v0.2.1

  • [FIX] ADD forecasting init design to pip data files by @dengdifan in https://github.com/automl/Auto-PyTorch/pull/459
  • checks for time series dataset split by @dengdifan in https://github.com/automl/Auto-PyTorch/pull/464
  • [FIX] Numerical stability scaling for timeseries forecasting tasks by @dengdifan in https://github.com/automl/Auto-PyTorch/pull/467
  • [FIX] pipeline options in fit_pipeline by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/466
  • [FIX] results management and visualisation with missing test data by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/465
  • [ADD] Robustly refit models in final ensemble in parallel by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/471

Full Changelog: https://github.com/automl/Auto-PyTorch/compare/v0.2...0.2.1

- Python
Published by ravinkohli almost 4 years ago

autopytorch - Version 0.2

What's Changed

  • Fix 361 by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/367
  • [ADD] Test evaluator by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/368
  • [fix] Hotfix debug no training in simple intensifier by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/370
  • [fix] Change int to np.int32 for the ndarray dtype specification by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/371
  • [ADD] variance thresholding by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/373
  • [ADD] scalers from autosklearn by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/372
  • [FIX] Remove redundant categorical imputation by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/375
  • [feat] Add coalescer by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/376
  • Fix: keyword arguments to submit by @eddiebergman in https://github.com/automl/Auto-PyTorch/pull/384
  • [FIX] Datamanager in memory by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/382
  • [feat] Add new task inference for APT by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/386
  • [fix] Update the SMAC version by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/388
  • [ADD] dataset compression by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/387
  • [refactor] Fix SparseMatrixType --> spmatrix and add ispandas by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/397
  • [ADD] feature preprocessors from autosklearn by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/378
  • [feat] Add str to autoPyTorchEnum by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/405
  • [ADD] Subsampling Dataset by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/398
  • fix dist twine check for github by @dengdifan in https://github.com/automl/Auto-PyTorch/pull/439
  • Time series forecasting by @dengdifan in https://github.com/automl/Auto-PyTorch/pull/434
  • fit updates in gluonts by @dengdifan in https://github.com/automl/Auto-PyTorch/pull/445
  • docs for forecasting task by @dengdifan in https://github.com/automl/Auto-PyTorch/pull/443
  • [ADD] Allow users to pass feat types to tabular validator by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/441
  • [RELEASE] Changes for release v0.2 by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/446
  • [FIX] Documentation and docker workflow file by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/449
  • [ADD] change log for release by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/450
  • [RELEASE] Release v0.2 by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/448

New Contributors

  • @dengdifan made their first contribution in https://github.com/automl/Auto-PyTorch/pull/439

Full Changelog: https://github.com/automl/Auto-PyTorch/compare/v0.1.1...v0.2

- Python
Published by ravinkohli almost 4 years ago

autopytorch -

What's Changed

  • fixed README by @urbanmatthias in https://github.com/automl/Auto-PyTorch/pull/1
  • Update develop branch to 0.0.2 release by @LMZimmer in https://github.com/automl/Auto-PyTorch/pull/17
  • set fill value to max of full dataset + 1 by @jonathanburns in https://github.com/automl/Auto-PyTorch/pull/36
  • Include missing files in sdist by @thatch in https://github.com/automl/Auto-PyTorch/pull/47
  • sort value range sets before adding as hyperparameter by @ntnguyen-dev in https://github.com/automl/Auto-PyTorch/pull/43
  • Image classification full cs by @dwoiwode in https://github.com/automl/Auto-PyTorch/pull/73
  • Document formatting by @daikikatsuragawa in https://github.com/automl/Auto-PyTorch/pull/64
  • Allow specifying the network type in include by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/78
  • Search space update by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/80
  • Network Cleanup by @bastiscode in https://github.com/automl/Auto-PyTorch/pull/81
  • Make sure the performance of pipeline is at least 0.8 by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/82
  • Refactor development docs by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/83
  • Feature preprocessors, Loss strategies by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/86
  • Handling Input to auto pytorch by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/89
  • Adding tabular regression pipeline by @bastiscode in https://github.com/automl/Auto-PyTorch/pull/85
  • FIX weighted loss issue by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/94
  • Reduce Deadlock Probability by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/84
  • handle nans in categorical columns by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/118
  • Pre fetch openml data for pytest by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/112
  • Embedding layer by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/91
  • Fixes to address automlbenchmark problems by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/126
  • Bug fix in Test API by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/129
  • Refactoring base dataset by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/105
  • move to a minimization problem by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/113
  • FIX_123 by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/133
  • Adds more examples to customise AutoPyTorch. by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/124
  • [Feat] Better traditional pipeline cutoff time by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/141
  • Hyperparameter Search Space updates now with constant and include ability by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/146
  • [Bug] Fix random halt problems on traditional pipelines by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/147
  • Run history traditional by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/121
  • [FIX] Enables backend to track the num run by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/162
  • [Doc] First push of the developer documentation by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/127
  • Refactoring base dataset splitting functions by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/106
  • [Fix] Refactor development reproducibility by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/172
  • [ADD] Extra visualization example by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/189
  • [Fix] docs links by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/201
  • [Refactor] Use the backend implementation from automl common by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/185
  • [DOC] Adds documentation to the abstract evaluator by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/160
  • [FIX] Update Readme by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/208
  • Reduce run time of the test by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/205
  • [refactor] Getting dataset properties from the dataset object by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/164
  • Change ubuntu version in docs workflow by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/237
  • Add dist check worflow by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/238
  • [feature] Greedy Portfolio by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/200
  • [ADD] Forkserver as default multiprocessing strategy by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/223
  • [ADD] Get incumbent config by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/175
  • [ADD] Coverage calculation by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/224
  • [ADD] Pytest schedule by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/234
  • [fix] Dropout bug fix by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/247
  • [FIX] Fixes for Tabular Regression by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/235
  • [doc] Add the bug fix information for ipython user by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/254
  • [ADD] Enable long running regression by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/251
  • [MAINT] Drop 3.6 python support by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/258
  • [ADD] Stricter checks mypy by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/240
  • [feat] Add flexible step-wise LR scheduler with minimum changes by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/256
  • Enable python 3.9 by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/264
  • Fixes problems with weighted cross-entropy by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/263
  • [Fix] long running regression by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/272
  • [Fix] budget allocation to enable runtime/epoch as budget by @franchuterivera in https://github.com/automl/Auto-PyTorch/pull/271
  • [fix] Be able to display error messages in additional info as it is by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/225
  • [ADD] Add column transformer by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/305
  • [FIX] Minor Fixes by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/306
  • [Add] Dockerfile by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/314
  • [style] Remove prefix typing and adapt to google style doc by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/307
  • [ADD] Missing Batchnorm by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/317
  • [feat] Update automl_common and add setup.py for submodule by @nabenabe0928 in https://github.com/automl/Auto-PyTorch/pull/324
  • [FIX] Additional metrics during training by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/316
  • [ADD] Update developer documentation by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/320
  • [FIX] remove .pth for early stopping by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/321
  • [Add] documentation and example for parallel computation by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/322
  • [ADD] Documentation for data validation and preprocessing by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/323
  • [ADD] documentation for pipelines and steps by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/329
  • Final changes for v0.1.0 by @ravinkohli in https://github.com/automl/Auto-PyTorch/pull/341

New Contributors

  • @urbanmatthias made their first contribution in https://github.com/automl/Auto-PyTorch/pull/1
  • @jonathanburns made their first contribution in https://github.com/automl/Auto-PyTorch/pull/36
  • @thatch made their first contribution in https://github.com/automl/Auto-PyTorch/pull/47
  • @ntnguyen-dev made their first contribution in https://github.com/automl/Auto-PyTorch/pull/43
  • @dwoiwode made their first contribution in https://github.com/automl/Auto-PyTorch/pull/73
  • @daikikatsuragawa made their first contribution in https://github.com/automl/Auto-PyTorch/pull/64
  • @bastiscode made their first contribution in https://github.com/automl/Auto-PyTorch/pull/81

Full Changelog: https://github.com/automl/Auto-PyTorch/compare/v0.0.2...v0.1.1

- Python
Published by ravinkohli over 4 years ago

autopytorch -

The first pre-alpha of Auto-PyTorch supporting image data

- Python
Published by mlindauer over 6 years ago