Pydvl

This is our first β release! We have worked hard to deliver improvements across
the board, with a focus on documentation and usability. We have also reworked
the internals of the `influence` module, improved parallelism and handling of
randomness.

Added

- Implemented solving the Hessian equation via spectral low-rank approximation
[PR 365](https://github.com/aai-institute/pyDVL/pull/365)
- Enabled parallel computation for Leave-One-Out values
[PR 406](https://github.com/aai-institute/pyDVL/pull/406)
- Added more abbreviations to documentation
[PR 415](https://github.com/aai-institute/pyDVL/pull/415)
- Added seed to functions from `pydvl.utils.numeric`, `pydvl.value.shapley` and
`pydvl.value.semivalues`. Introduced new type `Seed` and conversion function
`ensure_seed_sequence`.
[PR 396](https://github.com/aai-institute/pyDVL/pull/396)
- Added `batch_size` parameter to `compute_banzhaf_semivalues`,
`compute_beta_shapley_semivalues`, `compute_shapley_semivalues` and
`compute_generic_semivalues`.
[PR 428](https://github.com/aai-institute/pyDVL/pull/428)
- Added classwise Shapley as proposed by (Schoch et al. 2021)
[https://arxiv.org/abs/2211.06800]
[PR 338](https://github.com/aai-institute/pyDVL/pull/338)

Changed

- Replaced sphinx with mkdocs for documentation. Major overhaul of documentation
[PR 352](https://github.com/aai-institute/pyDVL/pull/352)
- Made ray an optional dependency, relying on joblib as default parallel backend
[PR 408](https://github.com/aai-institute/pyDVL/pull/408)
- Decoupled `ray.init` from `ParallelConfig`
[PR 373](https://github.com/aai-institute/pyDVL/pull/383)
- **Breaking Changes**
- Signature change: return information about Hessian inversion from
`compute_influence_factors`
[PR 375](https://github.com/aai-institute/pyDVL/pull/376)
- Major changes to IF interface and functionality. Foundation for a framework
abstraction for IF computation.
[PR 278](https://github.com/aai-institute/pyDVL/pull/278)
[PR 394](https://github.com/aai-institute/pyDVL/pull/394)
- Renamed `semivalues` to `compute_generic_semivalues`
[PR 413](https://github.com/aai-institute/pyDVL/pull/413)
- New `joblib` backend as default instead of ray. Simplify MapReduceJob.
[PR 355](https://github.com/aai-institute/pyDVL/pull/355)
- Bump torch dependency for influence package to 2.0
[PR 365](https://github.com/aai-institute/pyDVL/pull/365)

Fixed

- Fixes to parallel computation of generic semi-values: properly handle all
samplers and stopping criteria, irrespective of parallel backend.
[PR 372](https://github.com/aai-institute/pyDVL/pull/372)
- Optimises memory usage in IF calculation
[PR 375](https://github.com/aai-institute/pyDVL/pull/376)
- Fix adding valuation results with overlapping indices and different lengths
[PR 370](https://github.com/aai-institute/pyDVL/pull/370)
- Fixed bugs in conjugate gradient and `linear_solve`
[PR 358](https://github.com/aai-institute/pyDVL/pull/358)
- Fix installation of dev requirements for Python3.10
[PR 382](https://github.com/aai-institute/pyDVL/pull/382)
- Improvements to IF documentation
[PR 371](https://github.com/aai-institute/pyDVL/pull/371)

- Fix parsing keyword arguments of `compute_semivalues` dispatch function
[PR 333](https://github.com/aai-institute/pyDVL/pull/333)
- Create new `RayExecutor` class based on the concurrent.futures API,
use the new class to fix an issue with Truncated Monte Carlo Shapley
(TMCS) starting too many processes and dying, plus other small changes
[PR 329](https://github.com/aai-institute/pyDVL/pull/329)
- Fix creation of GroupedDataset objects using the `from_arrays`
and `from_sklearn` class methods
[PR 324](https://github.com/aai-institute/pyDVL/pull/334)
- Fix release job not triggering on CI when a new tag is pushed
[PR 331](https://github.com/aai-institute/pyDVL/pull/331)
- Added alias `ApproShapley` from Castro et al. 2009 for permutation Shapley
[PR 332](https://github.com/aai-institute/pyDVL/pull/332)

- Fixes in `ValuationResult`: bugs around data names, semantics of
`empty()`, new method `zeros()` and normalised random values
[PR 327](https://github.com/aai-institute/pyDVL/pull/327)
- **New method**: Implements generalised semi-values for data valuation,
including Data Banzhaf and Beta Shapley, with configurable sampling strategies
[PR 319](https://github.com/aai-institute/pyDVL/pull/319)
- Adds kwargs parameter to `from_array` and `from_sklearn` Dataset and
GroupedDataset class methods
[PR 316](https://github.com/aai-institute/pyDVL/pull/316)
- PEP-561 conformance: added `py.typed`
[PR 307](https://github.com/aai-institute/pyDVL/pull/307)
- Removed default non-negativity constraint on least core subsidy
and added instead a `non_negative_subsidy` boolean flag.
Renamed `options` to `solver_options` and pass it as dict.
Change default least-core solver to SCS with 10000 max_iters.
[PR 304](https://github.com/aai-institute/pyDVL/pull/304)
- Cleanup: removed unnecessary decorator `unpackable`
[PR 233](https://github.com/aai-institute/pyDVL/pull/233)
- Stopping criteria: fixed problem with `StandardError` and enable proper
composition of index convergence statuses. Fixed a bug with `n_jobs` in
`truncated_montecarlo_shapley`.
[PR 300](https://github.com/aai-institute/pyDVL/pull/300) and
[PR 305](https://github.com/aai-institute/pyDVL/pull/305)
- Shuffling code around to allow for simpler user imports, some cleanup and
documentation fixes.
[PR 284](https://github.com/aai-institute/pyDVL/pull/284)
- **Bug fix**: Warn instead of raising an error when `n_iterations`
is less than the size of the dataset in Monte Carlo Least Core
[PR 281](https://github.com/aai-institute/pyDVL/pull/281)

- Fixed parallel and antithetic Owen sampling for Shapley values. Simplified
and extended tests.
[PR 267](https://github.com/aai-institute/pyDVL/pull/267)
- Added `Scorer` class for a cleaner interface. Fixed minor bugs around
Group-Testing Shapley, added more tests and switched to cvxpy for the solver.
[PR 264](https://github.com/aai-institute/pyDVL/pull/264)
- Generalised stopping criteria for valuation algorithms. Improved classes
`ValuationResult` and `Status` with more operations. Some minor issues fixed.
[PR 252](https://github.com/aai-institute/pyDVL/pull/250)
- Fixed a bug whereby `compute_shapley_values` would only spawn one process when
using `n_jobs=-1` and Monte Carlo methods.
[PR 270](https://github.com/aai-institute/pyDVL/pull/270)
- Bugfix in `RayParallelBackend`: wrong semantics for `kwargs`.
[PR 268](https://github.com/aai-institute/pyDVL/pull/268)
- Splitting of problem preparation and solution in Least-Core computation.
Umbrella function for LC methods.
[PR 257](https://github.com/aai-institute/pyDVL/pull/257)
- Operations on `ValuationResult` and `Status` and some cleanup
[PR 248](https://github.com/aai-institute/pyDVL/pull/248)
- **Bug fix and minor improvements**: Fixes bug in TMCS with remote Ray cluster,
raises an error for dummy sequential parallel backend with TMCS, clones model
inside `Utility` before fitting by default, with flag `clone_before_fit`
to disable it, catches all warnings in `Utility` when `show_warnings` is
`False`. Adds Miner and Gloves toy games utilities
[PR 247](https://github.com/aai-institute/pyDVL/pull/247)

- GH action to mark issues as stale
[PR 201](https://github.com/aai-institute/pyDVL/pull/201)
- Disabled caching of Utility values as well as repeated evaluations by default
[PR 211](https://github.com/aai-institute/pyDVL/pull/211)
- Test and officially support Python version 3.9 and 3.10
[PR 208](https://github.com/aai-institute/pyDVL/pull/208)
- **Breaking change:** Introduces a class ValuationResult to gather and inspect
results from all valuation algorithms
[PR 214](https://github.com/aai-institute/pyDVL/pull/214)
- Fixes bug in Influence calculation with multidimensional input and adds new
example notebook
[PR 195](https://github.com/aai-institute/pyDVL/pull/195)
- **Breaking change**: Passes the input to `MapReduceJob` at initialization,
removes `chunkify_inputs` argument from `MapReduceJob`, removes `n_runs`
argument from `MapReduceJob`, calls the parallel backend's `put()` method for
each generated chunk in `_chunkify()`, renames ParallelConfig's `num_workers`
attribute to `n_local_workers`, fixes a bug in `MapReduceJob`'s chunkification
when `n_runs` >= `n_jobs`, and defines a sequential parallel backend to run
all jobs in the current thread
[PR 232](https://github.com/aai-institute/pyDVL/pull/232)
- **New method**: Implements exact and monte carlo Least Core for data valuation,
adds `from_arrays()` class method to the `Dataset` and `GroupedDataset`
classes, adds `extra_values` argument to `ValuationResult`, adds
`compute_removal_score()` and `compute_random_removal_score()` helper functions
[PR 237](https://github.com/aai-institute/pyDVL/pull/237)
- **New method**: Group Testing Shapley for valuation, from _Jia et al. 2019_
[PR 240](https://github.com/aai-institute/pyDVL/pull/240)
- Fixes bug in ray initialization in `RayParallelBackend` class
[PR 239](https://github.com/aai-institute/pyDVL/pull/239)
- Implements "Egalitarian Least Core", adds [cvxpy](https://www.cvxpy.org/) as a
dependency and uses it instead of scipy as optimizer
[PR 243](https://github.com/aai-institute/pyDVL/pull/243)

- Simplified and fixed powerset sampling and testing
[PR 181](https://github.com/aai-institute/pyDVL/pull/181)
- Simplified and fixed publishing to PyPI from CI
[PR 183](https://github.com/aai-institute/pyDVL/pull/183)
- Fixed bug in release script and updated contributing docs.
[PR 184](https://github.com/aai-institute/pyDVL/pull/184)
- Added Pull Request template
[PR 185](https://github.com/aai-institute/pyDVL/pull/185)
- Modified Pull Request template to automatically link PR to issue
[PR 186](https://github.com/aai-institute/pyDVL/pull/186)
- First implementation of Owen Sampling, squashed scores, better testing
[PR 194](https://github.com/aai-institute/pyDVL/pull/194)
- Improved documentation on caching, Shapley, caveats of values, bibtex
[PR 194](https://github.com/aai-institute/pyDVL/pull/194)
- **Breaking change:** Rearranging of modules to accommodate for new methods
[PR 194](https://github.com/aai-institute/pyDVL/pull/194)