* adding LABOR sampling
* add ladies and pladies samplers
* fix compile error after rebase
* add reference for ladies sampler
* Improve ladies implementation.
* weighted labor sampling initial implementation draft
fix indentation and small bug in ladies script
* importance_sampling currently doesn't work with weights
* fix weighted importance sampling
* move labor example into its own folder
* lint fixes
* Improve documentation
* remove examples from the main PR
* fix linting by not using c++17 features
* fix documentation of labor_sampler.py
* update documentation for labor.py
* reformat the labor.py file with black
* fix linting errors
* replace exception use with if
* fix typo in error comment
* fixing win64 build for ci
* fixing weighted implementation, works now.
* fix bug in the weighted case and importance_sampling==0
* address part of the reviews
* remove unused code paths from cuda
* remove unused code path from cpu side
* remove extra features of labor making use of random seed.
* fix exclude_edges bug
* remove pcg and seed logic from cpu implementation, seed logic should still work for cuda.
* minor style change
* refactor CPU implementation, take out the importance_sampling probability computation into a function.
* improve CUDAWorkspaceAllocator
* refactor importance_sampling part out to a function
* minor optimization
* fix linting issue
* Revert "remove pcg and seed logic from cpu implementation, seed logic should still work for cuda."
This reverts commit c250e07ac6d7e13f57e79e8a2c2f098d777378c2.
* Revert "remove extra features of labor making use of random seed."
This reverts commit 7f99034353080308f4783f27d9a08bea343fb796.
* fix the documentation
* disable NIDs
* improve the documentation in the code
* use the stream argument in pcg32 instead of skipping ahead t times, can discard the use of hashmap now since it is faster this way.
* fix linting issue
* address another round of reviews
* further optimize CPU LABOR sampling implementation
* fix linting error
* update the comment
* reformat
* rename and rephrase comment
* fix formatting according to new linting specs
* fix compile error due to renaming, fix linting.
* lint
* rename DGLHeteroGraph to DGLGraph to match master
* replace other occurrences of DGLHeteroGraph to DGLGraph
Co-authored-by: Muhammed Fatih BALIN <m.f.balin@gmail.com>
Co-authored-by: Kaan Sancak <kaansnck@gmail.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>
* * Added half_(), float_(), and double_() functions to DGLHeteroGraph, HeteroNodeDataView, and HeteroEdgeDataView, for converting floating-point tensor data to float16, float32, or float64 precision
* * Extracted out private functions for floating-point type conversion, to reduce code duplication
* * Added test for floating-point data conversion functions, half_(), float_(), and double_()
* * Moved half_(), float_(), and double_() functions from HeteroNodeDataView and HeteroEdgeDataView to Frame class
* * Updated test_float_cast() to use dgl.heterograph instead of dgl.graph
* Added to CONTRIBUTORS.md
* * Changed data type conversion to be deferred until the data is accessed, to avoid redundant conversions of data that isn't used.
* * Addressed issues flagged by linter
* * Worked around a bug in the old version of mxnet that's currently used for DGL testing
* * Only defer Column data type conversion if there is a pending device transfer or index sampling to be done. This is expected to be the desired behaviour based on discussions of a few use cases, as described in the comments.
* * Moved floating-point feature data conversion functions to dgl.transforms.functional
* Changed them from in-place behaviour to shallow copy (out-of-place) behaviour
* * Fixed linter issues
* * Removed lines that unintentionally added to_half, to_float, and to_double to DGLHeteroGraph
* Moved _init_api line to the end of the file again
* * Removed one of the two leading underscores from Frame.__astype_float, making it not fully private
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
* Based on issue #3436. Improving _SegmentCopyKernel s GPU utilization by switching to nonzero based thread assignment
* fixing lint issues
* Update cub for cuda 11.5 compatibility (#3468)
* fixing type mismatch
* tx guaranteed to be smaller than nnz. Hence removing last check
* minor: updating comment
* adding three unit tests for csr slice method to cover some corner cases
Co-authored-by: Abdurrahman Yasar <ayasar@nvidia.com>
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
* add gin model
* convert dataset.py to data_ont_the_fly way and put it into dgl.data module
* convert dataset.py to data_ont_the_fly way and put it into dgl.data module
python code checked
* modified document and reference TUDataset; checked python part and bypass cpp part due to error
* change tensor to numpy in dataset and transform in collate@Dataloader
* Change minor format issue
Change minor format issue
* moved logging; adjusted tqdm etc
* test basics
* batched graph & filter, mxnet filter fix
* frame and function; bugfix
* test graph adj and inc matrices
* fixing start = 0 for mxnet
* test index
* inplace update & line graph
* multi send recv
* more tests
* oops
* more tests
* removing old test files; readonly graphs for mxnet still kept
* modifying test scripts
* adding a placeholder for pytorch to reserve directory
* torch 0.4.1 compat fixes
* moving backend out of compute to avoid nose detection
* tests guide
* mx sparse-to-dense/sparse-to-numpy is buggy
* oops
* contribution guide for unit tests
* printing incmat
* printing dlpack
* small push
* typo
* fixing duplicate entries that causes undefined behavior
* move equal comparison to backend
Muhammed Fatih BALIN