- Use std::uint64_t instead of size_t to avoid implementation-defined type.
- Rename to bst_idx_t, to account for other types of indexing.
- Small cleanup to the base header.
* [coll] Pass context to various functions.
In the future, the `Context` object would be required for collective operations, this PR
passes the context object to some required functions to prepare for swapping out the
implementation.
- Pass context from booster to DMatrix.
- Use context instead of integer for `n_threads`.
- Check the consistency configuration for `max_bin`.
- Test for all combinations of initialization options.
Added some more tests for the learner and fit_stump, for both column-wise distributed learning and vertical federated learning.
Also moved the `IsRowSplit` and `IsColumnSplit` methods from the `DMatrix` to the `MetaInfo` since in some places we only have access to the `MetaInfo`. Added a new convenience method `IsVerticalFederatedLearning`.
Some refactoring of the testing fixtures.
* Intoducing Column Wise Hist Building
* linting
* more linting
* bug fixing
* Removing column samping optimization for a while to simplify the review process.
* linting
* Removing unnecessary changes
* Use DispatchBinType in hist_util.cc
* Adding force_read_by column flag to buildhist. Adding tests for column wise buiilhist.
* Introducing new dispatcher for compile time flags in hist building
* fixing bug with using of DispatchBinType
* Fixing building
* Merging with master branch
Co-authored-by: dmitry.razdoburdin <drazdobu@jfldaal005.jf.intel.com>
Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
- Use `bst_bin_t` in batch param constructor.
- Use `StringView` to avoid `std::string` when appropriate.
- Avoid using `MetaInfo` in quantile constructor to limit the scope of parameter.
* Implement GK sketching on GPU.
* Strong tests on quantile building.
* Handle sparse dataset by binary searching the column index.
* Hypothesis test on dask.
* Extract interaction constraints from split evaluator.
The reason for doing so is mostly for model IO, where num_feature and interaction_constraints are copied in split evaluator. Also interaction constraint by itself is a feature selector, acting like column sampler and it's inefficient to bury it deep in the evaluator chain. Lastly removing one another copied parameter is a win.
* Enable inc for approx tree method.
As now the implementation is spited up from evaluator class, it's also enabled for approx method.
* Removing obsoleted code in colmaker.
They are never documented nor actually used in real world. Also there isn't a single test for those code blocks.
* Unifying the types used for row and column.
As the size of input dataset is marching to billion, incorrect use of int is subject to overflow, also singed integer overflow is undefined behaviour. This PR starts the procedure for unifying used index type to unsigned integers. There's optimization that can utilize this undefined behaviour, but after some testings I don't see the optimization is beneficial to XGBoost.
