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Merge release/0.8.1 back into develop for release 0.8.1 (mckinsey#96)
* Hotfix/0.4.3 (mckinsey#7) - Address broken links and grammar * Fix documentation links in README (mckinsey#2) * Fix links in README * library -> libraries * Fix github link in docs * Clean up grammar and consistency in documentation (mckinsey#4) * Clean up grammar and consistency in `README` files * Add esses, mostly * Reword feature description to not appear automatic * Update docs/source/05_resources/05_faq.md Co-Authored-By: Ben Horsburgh <benhorsburgh@outlook.com> Co-authored-by: Ben Horsburgh <benhorsburgh@outlook.com> * hotfix/0.4.3: fix broken links Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> * Release/0.5.0 * Plotting now backed by pygraphviz. This allows: * More powerful layout manager * Cleaner fully customisable theme * Out-the-box styling for different node and edge types * Can now get subgraphs from StructureModel containing a specific node * Bugfix to resolve issue when fitting CPDs with some missing states in data * Minor documentation fixes and improvements * Release/0.6.0 * Release/0.7.0 (mckinsey#57) * Added plottting tutorial to the documentation * Updated `viz.draw` syntax in tutorial notebooks * Bugfix on notears lasso (`from_numpy_lasso` and `from_pandas_lasso`) where the non-negativity constraint was not being set * Added DAG-based synthetic data generator for mixed types (binary, categorical, continuous) using a linear SEM approach. * Unpinned some requirements * Release/0.8.0 (mckinsey#80) * Merge back to develop * Simplifying viz.draw syntax in tutorial notebook (mckinsey#46) * Add non negativity constraint in numpy lasso (mckinsey#41) * Add plotting tutorial to the documentation (mckinsey#47) * Unpin some requirements * Mixed type data generation (mckinsey#55) Added DAG-based synthetic data generator for mixed types (binary, categorical, continuous) using a linear SEM approach. * Merge back to develop (mckinsey#59) * Pytorch NOTEARS (mckinsey#63) * NoTears as ScoreSolver * refactor continuous solver * adding attribute to access weight matrix * refactoring continuous solver * Adding fit_lasso method * add data_gen_continuous.py and tests (mckinsey#38) * add data_gen.py * rename * wrap SM * move data_gen_continous, create test * more coverage * test fixes * move discrete sem to another file * node list dupe check test * ValueError tests * replace dag and sem functions with Ben's verions * add Ben's tests * fix fstring * to_numpy_array coverage * Ben's comments * remove unreachable ValueError for coverage * remove unused fixture * remove redundant test * remove extensions Co-Authored-By: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * docstring Co-Authored-By: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * docstring Co-Authored-By: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * docs Co-Authored-By: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * doc Co-Authored-By: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * rename file, g_dag rename to sm * add new tests for equal weights * docstring * steve docstring, leq fix * steve comments + docstrings Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * Adding check input and removing some inner functions * Removing attribute original_ndarray * Aligning from pandas with new implementation * Adding tests for fit_lasso * More tests for lasso * wrapping tabu params in a dict * Aligning tests with new tabu params * Aligning from_pandas with new tabu_params * Adding fit_intercept option to _fit method * Adding scaling option * fixing lasso tests * Adding a test for fit_intercept * scaling option only with mean * Correction in lasso bounds * Fix typos * Remove duplicated bounds function * adding comments * add torch files from xunzheng * add from_numpy_torch function that works like from_numpy_lasso * lint * add requirements * add debug functionality * add visual debug test * add license * allow running as main for viz, comments * move to contrib * make multi layer work a bit better * add comment for multi layer * use polynomial dag constraint for better speed comparison * revert unnecessary changes to keep PR lean * revert unnecessary changes to keep PR lean * revert unnecessary changes to keep PR lean * fixes * refactor * Integrated tests * Checkpoint * Refactoring * Finished initial refactoring * All tests passed * Cleaning * Git add testing * Get adjacency matrix * Done cleaning * Revert change to original notears * Revert change to original structuremodel * Revert change to pylintrc * Undo deletion * Apply suggestions from Zain Co-authored-by: Zain Patel <zain.patel@quantumblack.com> * Addressed Zain comments * Migrated from_numpy * Delete contrib test * Migrated w_threshold * Some linting * Change to None * Undo deletion * List comprehension * Refactoring scipy and remove scipy optimiser * Refactoring * Refactoring * Refactoring complete * change from np to torch tensor * More refactoring * Remove hnew equal to None * Refactor again and remove commented line * Minor change * change to params * Addressing Philip's comment * Add property * Add fc2 property weights * Change to weights * Docstring * Linting * Linting completed * Add gpu code * Add gpu to from_numpy and from_pandas * cuda 0 run out of memory * Debugging * put 5 * debugging gpu * shift to inner loop * debugging not in place * Use cada instead of to * Support both interfaces * Benchmarking gpu * Minor fix * correct import path for test * change gpu from 5 to 1 * Debugging * Debugging * Experimenting * Linting * Remove hidden layer and gpu * Linting * Testing and linting * Correct pytorch to torch * Add init zeros * Change weight threshold to 0.25 * Revert requirements.txt * Update release.md * Address coments * Corrected release.md * fc1 to adjacency Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> Co-authored-by: LiseDiagneQB <60981366+LiseDiagneQB@users.noreply.github.com> Co-authored-by: Casey Juanxi Li <50737712+caseyliqb@users.noreply.github.com> Co-authored-by: qbphilip <philip.pilgerstorfer@quantumblack.com> Co-authored-by: Zain Patel <zain.patel@quantumblack.com> * Pinned sphinx-auto-doc-typehints (mckinsey#66) * Corrected a spelling/grammar mistake (mckinsey#55) * Fix/lint (mckinsey#73) * Hotfix/0.4.3 (mckinsey#7) - Address broken links and grammar * Fix documentation links in README (mckinsey#2) * Fix links in README * library -> libraries * Fix github link in docs * Clean up grammar and consistency in documentation (mckinsey#4) * Clean up grammar and consistency in `README` files * Add esses, mostly * Reword feature description to not appear automatic * Update docs/source/05_resources/05_faq.md Co-Authored-By: Ben Horsburgh <benhorsburgh@outlook.com> Co-authored-by: Ben Horsburgh <benhorsburgh@outlook.com> * hotfix/0.4.3: fix broken links Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> * Release/0.5.0 * Plotting now backed by pygraphviz. This allows: * More powerful layout manager * Cleaner fully customisable theme * Out-the-box styling for different node and edge types * Can now get subgraphs from StructureModel containing a specific node * Bugfix to resolve issue when fitting CPDs with some missing states in data * Minor documentation fixes and improvements * Release/0.6.0 * Release/0.7.0 (mckinsey#57) * Added plottting tutorial to the documentation * Updated `viz.draw` syntax in tutorial notebooks * Bugfix on notears lasso (`from_numpy_lasso` and `from_pandas_lasso`) where the non-negativity constraint was not being set * Added DAG-based synthetic data generator for mixed types (binary, categorical, continuous) using a linear SEM approach. * Unpinned some requirements * black * pin pytorch version * pin pytorch version Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> * Structure learning regressor (mckinsey#68) * initial commit (local copy-paste) * fixed minor comments * minor bugfix * impute from children inital commit * bugfixes and method option * auto thresholding * autothreshold and bugfix * make threshold removal explicit * add l1 argument * remove child imputation * feat importance fix and tabu logic * moved threshold till dag * restructure with base class * coef mask * recipe * enable bias fitting * persist bias as node attribute * allow fit_intercept * minor PR comment fixes * minor comment adjustment * test coverage and l1 clarification * recipe * minor test fixes * more tests * full test coverage * revove python 3.5/3.6 unsupported import * add normalization option * idiomatic typing * correct pylint errors * update some tests * more typeing updates * more pylint requirements * more pylint disable * python 3.5 support * try to get to work with 3.5 * full coverage and 3.5 support * remove base class to pass test * remove unneeded supression * black formatting changes * remove unused import * pytlint supression * minor reformat change * isort fix * better defensive programming * fix unittests * docstring update * do Raises docstring properly * action SWE suggestions * hotfixes * minor update * minor black formatting change * final merge checkbox * fix end of file * Data Gen root node initialisation fix (mckinsey#72) * Hotfix/0.4.3 (mckinsey#7) - Address broken links and grammar * Fix documentation links in README (mckinsey#2) * Fix links in README * library -> libraries * Fix github link in docs * Clean up grammar and consistency in documentation (mckinsey#4) * Clean up grammar and consistency in `README` files * Add esses, mostly * Reword feature description to not appear automatic * Update docs/source/05_resources/05_faq.md Co-Authored-By: Ben Horsburgh <benhorsburgh@outlook.com> Co-authored-by: Ben Horsburgh <benhorsburgh@outlook.com> * hotfix/0.4.3: fix broken links Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> * Release/0.5.0 * Plotting now backed by pygraphviz. This allows: * More powerful layout manager * Cleaner fully customisable theme * Out-the-box styling for different node and edge types * Can now get subgraphs from StructureModel containing a specific node * Bugfix to resolve issue when fitting CPDs with some missing states in data * Minor documentation fixes and improvements * Release/0.6.0 * Release/0.7.0 (mckinsey#57) * Added plottting tutorial to the documentation * Updated `viz.draw` syntax in tutorial notebooks * Bugfix on notears lasso (`from_numpy_lasso` and `from_pandas_lasso`) where the non-negativity constraint was not being set * Added DAG-based synthetic data generator for mixed types (binary, categorical, continuous) using a linear SEM approach. * Unpinned some requirements * fix for consinuous normal data * generalise across all dtypes * support fit_intercept * fixed many test errors * test logic fixes * lint test fixes * python 3.5 failure change * minor test bugfix * black * pin pytorch version * pin pytorch version * additional test parameter * black formatting * requested changes * test updates and docstring * black format change * disable too many lines * change * move recipe to tutorial folder * releaseMD changes Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> Co-authored-by: Philip Pilgerstorfer <34248114+qbphilip@users.noreply.github.com> Co-authored-by: qbphilip <philip.pilgerstorfer@quantumblack.com> * [1/2] Poisson data for data gen (mckinsey#61) * Hotfix/0.4.3 (mckinsey#7) - Address broken links and grammar * Fix documentation links in README (mckinsey#2) * Fix links in README * library -> libraries * Fix github link in docs * Clean up grammar and consistency in documentation (mckinsey#4) * Clean up grammar and consistency in `README` files * Add esses, mostly * Reword feature description to not appear automatic * Update docs/source/05_resources/05_faq.md Co-Authored-By: Ben Horsburgh <benhorsburgh@outlook.com> Co-authored-by: Ben Horsburgh <benhorsburgh@outlook.com> * hotfix/0.4.3: fix broken links Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> * Release/0.5.0 * Plotting now backed by pygraphviz. This allows: * More powerful layout manager * Cleaner fully customisable theme * Out-the-box styling for different node and edge types * Can now get subgraphs from StructureModel containing a specific node * Bugfix to resolve issue when fitting CPDs with some missing states in data * Minor documentation fixes and improvements * Release/0.6.0 * Release/0.7.0 (mckinsey#57) * Added plottting tutorial to the documentation * Updated `viz.draw` syntax in tutorial notebooks * Bugfix on notears lasso (`from_numpy_lasso` and `from_pandas_lasso`) where the non-negativity constraint was not being set * Added DAG-based synthetic data generator for mixed types (binary, categorical, continuous) using a linear SEM approach. * Unpinned some requirements * refactor & docstring * remove unused helper object * add data gen to init * make test more robust * add count data and test, use logs for poisson samples for stability * fix tests * duplicate fixtures * remove unused fixtures * refactor data_generators into package with core and wrappers * move wrapper to test_wrapper * variable name change bugfix * fix tests Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> Co-authored-by: angeldrothqb <angel.droth@quantumblack.com> * [2/2] Nonlinear Data gen (mckinsey#60) * Hotfix/0.4.3 (mckinsey#7) - Address broken links and grammar * Fix documentation links in README (mckinsey#2) * Fix links in README * library -> libraries * Fix github link in docs * Clean up grammar and consistency in documentation (mckinsey#4) * Clean up grammar and consistency in `README` files * Add esses, mostly * Reword feature description to not appear automatic * Update docs/source/05_resources/05_faq.md Co-Authored-By: Ben Horsburgh <benhorsburgh@outlook.com> Co-authored-by: Ben Horsburgh <benhorsburgh@outlook.com> * hotfix/0.4.3: fix broken links Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> * Release/0.5.0 * Plotting now backed by pygraphviz. This allows: * More powerful layout manager * Cleaner fully customisable theme * Out-the-box styling for different node and edge types * Can now get subgraphs from StructureModel containing a specific node * Bugfix to resolve issue when fitting CPDs with some missing states in data * Minor documentation fixes and improvements * Release/0.6.0 * Release/0.7.0 (mckinsey#57) * Added plottting tutorial to the documentation * Updated `viz.draw` syntax in tutorial notebooks * Bugfix on notears lasso (`from_numpy_lasso` and `from_pandas_lasso`) where the non-negativity constraint was not being set * Added DAG-based synthetic data generator for mixed types (binary, categorical, continuous) using a linear SEM approach. * Unpinned some requirements * refactor & docstring * remove unused helper object * add data gen to init * make test more robust * add count data and test, use logs for poisson samples for stability * add nonlinear * fix tests * duplicate fixtures * remove unused fixtures * refactor data_generators into package with core and wrappers * move wrapper to test_wrapper * add nonlinear to init * change order in all * change release.md * root node fix on core + count * nonlinear support to wrappers * docstring update * bugfix and reproducability fix * many tests and test updates * poiss bugfix and test fix * moar test coverage * categorical dataframe test coverage * full test coverage and linting * fix linting and fstring * black reformat * fix unused pylint argument * pytest fix * FINAL linting fix * Fix stuff (mckinsey#75) CircleCI fixes Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> Co-authored-by: angeldrothqb <angel.droth@quantumblack.com> Co-authored-by: Zain Patel <zain.patel@quantumblack.com> * update black version (mckinsey#76) * fix black * Fix/check for NA or Infinity when notears is used (mckinsey#54) * update scipy version (mckinsey#77) * add DYNOTEARS implementation (mckinsey#50) Adds DYNOTEARS and corresponding data generator (for testing) * Pytorch NOTEARS extension - Non-Linear/Hidden Layer (mckinsey#65) * NoTears as ScoreSolver * refactor continuous solver * adding attribute to access weight matrix * refactoring continuous solver * Adding fit_lasso method * add data_gen_continuous.py and tests (mckinsey#38) * add data_gen.py * rename * wrap SM * move data_gen_continous, create test * more coverage * test fixes * move discrete sem to another file * node list dupe check test * ValueError tests * replace dag and sem functions with Ben's verions * add Ben's tests * fix fstring * to_numpy_array coverage * Ben's comments * remove unreachable ValueError for coverage * remove unused fixture * remove redundant test * remove extensions Co-Authored-By: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * docstring Co-Authored-By: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * docstring Co-Authored-By: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * docs Co-Authored-By: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * doc Co-Authored-By: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * rename file, g_dag rename to sm * add new tests for equal weights * docstring * steve docstring, leq fix * steve comments + docstrings Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> * Adding check input and removing some inner functions * Removing attribute original_ndarray * Aligning from pandas with new implementation * Adding tests for fit_lasso * More tests for lasso * wrapping tabu params in a dict * Aligning tests with new tabu params * Aligning from_pandas with new tabu_params * Adding fit_intercept option to _fit method * Adding scaling option * fixing lasso tests * Adding a test for fit_intercept * scaling option only with mean * Correction in lasso bounds * Fix typos * Remove duplicated bounds function * adding comments * add torch files from xunzheng * add from_numpy_torch function that works like from_numpy_lasso * lint * add requirements * add debug functionality * add visual debug test * add license * allow running as main for viz, comments * move to contrib * make multi layer work a bit better * add comment for multi layer * use polynomial dag constraint for better speed comparison * revert unnecessary changes to keep PR lean * revert unnecessary changes to keep PR lean * revert unnecessary changes to keep PR lean * fixes * refactor * Integrated tests * Checkpoint * Refactoring * Finished initial refactoring * All tests passed * Cleaning * Git add testing * Get adjacency matrix * Done cleaning * Revert change to original notears * Revert change to original structuremodel * Revert change to pylintrc * Undo deletion * Apply suggestions from Zain Co-authored-by: Zain Patel <zain.patel@quantumblack.com> * Addressed Zain comments * Migrated from_numpy * Delete contrib test * Migrated w_threshold * Some linting * Change to None * Undo deletion * List comprehension * Refactoring scipy and remove scipy optimiser * Refactoring * Refactoring * Refactoring complete * change from np to torch tensor * More refactoring * Remove hnew equal to None * Refactor again and remove commented line * Minor change * change to params * Addressing Philip's comment * Add property * Add fc2 property weights * Change to weights * Docstring * Linting * Linting completed * Add gpu code * Add gpu to from_numpy and from_pandas * cuda 0 run out of memory * Debugging * put 5 * debugging gpu * shift to inner loop * debugging not in place * Use cada instead of to * Support both interfaces * Benchmarking gpu * Minor fix * correct import path for test * change gpu from 5 to 1 * Debugging * Debugging * Experimenting * Linting * Remove hidden layer and gpu * Linting * Testing and linting * Correct pytorch to torch * Add init zeros * Change weight threshold to 0.25 * Revert requirements.txt * Add hidden layer * small refactor * directional adj * minor edits * fix bias issues * breaking changes update to the interface * typo * new regressor regularisation interface * update forward method * forward(X) predictions work * working! * bugfix data normalisation * some fixes * average regularisation and adj calc at end * give credit! Co-authored-by: Philip Pilgerstorfer <34248114+qbphilip@users.noreply.github.com> * loc lin docstring update Co-authored-by: Philip Pilgerstorfer <34248114+qbphilip@users.noreply.github.com> * docstring + fc1/fc2 name updates * moar docstring updates * more minor updates * remove normalize option * plotting util * rename to DAGRegressor * rename and checks * more util functions * fix bias * fix bias with no intercept * fix linear adj * add tests * minor fix * minor fixes * extend interface to bias * differentialte coef_ and feature_imporances * seperate bias element * tests * more test coverage * nonlinear test coverage * test hotfix * more test coverage * test requirements update * more test coverage * formatting changes * final pylint change * more linting * more bestpractice structuring * more minor fixes * FINAL linting updates * actual last change * update to reg defaults, additions to the tutorial * nonlinear regularisation updates * regressor tutorial * almost finishing touches * gradient based h function! * soft clamp and coef feature importance seperation * small api update, closer to batchnorm * docstring updates * stronger soft clamping * gradient L1 rather than L2 * fcpos neg removal, gradient optim * revert back to create_graph=True for 2nd derivative * remove print and test fix * black reformatting * new black version * full test coverage * isort fix * pylint fix * first layer h(W) for speed optimization * fix batch norm system * add nonlinear test * test hotfix * black reformat * isort fix * remove X requirement from h_func * regressor tutorial final commit and black update * LayerNorm replacement Co-authored-by: Philip Pilgerstorfer <34248114+qbphilip@users.noreply.github.com> * major changes * add standardization * minort changes * fix tests * rename reg parameters * linting * test coverage, docstting * check array for infs * fix isinstance to base type * fix isort, add test coverage * new tutorial * docstring fix Co-authored-by: Zain Patel <zain.patel@quantumblack.com> * test string match Co-authored-by: Zain Patel <zain.patel@quantumblack.com> * assert improvement Co-authored-by: Zain Patel <zain.patel@quantumblack.com> * SWE suggestions * minor bugfix * more test fixing Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> Co-authored-by: LiseDiagneQB <60981366+LiseDiagneQB@users.noreply.github.com> Co-authored-by: Casey Juanxi Li <50737712+caseyliqb@users.noreply.github.com> Co-authored-by: qbphilip <philip.pilgerstorfer@quantumblack.com> Co-authored-by: Zain Patel <zain.patel@quantumblack.com> Co-authored-by: angeldrothqb <angel.droth@quantumblack.com> Co-authored-by: angeldrothqb <67913551+angeldrothqb@users.noreply.github.com> Co-authored-by: Philip Pilgerstorfer <34248114+qbphilip@users.noreply.github.com> * release.md, version bump, docs Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> Co-authored-by: GabrielAzevedoFerreiraQB <57528979+GabrielAzevedoFerreiraQB@users.noreply.github.com> Co-authored-by: Philip Pilgerstorfer <34248114+qbphilip@users.noreply.github.com> Co-authored-by: stevelersl <55385183+SteveLerQB@users.noreply.github.com> Co-authored-by: LiseDiagneQB <60981366+LiseDiagneQB@users.noreply.github.com> Co-authored-by: Casey Juanxi Li <50737712+caseyliqb@users.noreply.github.com> Co-authored-by: qbphilip <philip.pilgerstorfer@quantumblack.com> Co-authored-by: Zain Patel <zain.patel@quantumblack.com> Co-authored-by: KING-SID <sidhantbendre22@gmail.com> Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> Co-authored-by: Jebq <jb.oger2312@gmail.com> * release.MD * version bump * Update causalnex/structure/pytorch/dist_type/_base.py Co-authored-by: Zain Patel <zain.patel@quantumblack.com> * Update causalnex/structure/pytorch/dist_type/__init__.py Co-authored-by: Zain Patel <zain.patel@quantumblack.com> Co-authored-by: Ben Horsburgh <Ben.Horsburgh@quantumblack.com> Co-authored-by: Zain Patel <30357972+mzjp2@users.noreply.github.com> Co-authored-by: Nikos Tsaousis <tsanikgr@users.noreply.github.com> Co-authored-by: Deepyaman Datta <deepyaman.datta@utexas.edu> Co-authored-by: Philip Pilgerstorfer <34248114+qbphilip@users.noreply.github.com> Co-authored-by: GabrielAzevedoFerreiraQB <57528979+GabrielAzevedoFerreiraQB@users.noreply.github.com> Co-authored-by: stevelersl <55385183+SteveLerQB@users.noreply.github.com> Co-authored-by: LiseDiagneQB <60981366+LiseDiagneQB@users.noreply.github.com> Co-authored-by: Casey Juanxi Li <50737712+caseyliqb@users.noreply.github.com> Co-authored-by: qbphilip <philip.pilgerstorfer@quantumblack.com> Co-authored-by: Zain Patel <zain.patel@quantumblack.com> Co-authored-by: KING-SID <sidhantbendre22@gmail.com> Co-authored-by: Jebq <jb.oger2312@gmail.com>
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