* * Added "exclude_self" and "output_batch" options to knn_graph and segmented_knn_graph
* Updated out-of-date comments on remove_edges and remove_self_loop, since they now preserve batch information
* * Changed defaults on new knn_graph and segmented_knn_graph function parameters, for compatibility; pytorch/test_geometry.py was failing
* * Added test to ensure dgl.remove_self_loop function correctly updates batch information
* * Added new knn_graph and segmented_knn_graph parameters to dgl.nn.KNNGraph and dgl.nn.SegmentedKNNGraph
* * Formatting
* * Oops, I missed the one in segmented_knn_graph when I fixed the similar thing in knn_graph
* * Fixed edge case handling when invalid k specified, since it still needs to be handled consistently for tests to pass
* Fixed context of batch info, since it must match the context of the input position data for remove_self_loop to succeed
* * Fixed batch info resulting from knn_graph when output_batch is true, for case of 3D input tensor, representing multiple segments
* * Added testing of new exclude_self and output_batch parameters on knn_graph and segmented_knn_graph, and their wrappers, KNNGraph and SegmentedKNNGraph, into the test_knn_cuda test
* * Added doc comments for new parameters
* * Added correct handling for uncommon case of k or more coincident points when excluding self edges in knn_graph and segmented_knn_graph
* Added test cases for more than k coincident points
* * Updated doc comments for output_batch parameters for clarity
* * Linter formatting fixes
* * Extracted out common function for test_knn_cpu and test_knn_cuda, to add the new test cases to test_knn_cpu
* * Rewording in doc comments
* * Removed output_batch parameter from knn_graph and segmented_knn_graph, in favour of always setting the batch information, except in knn_graph if x is a 2D tensor
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
* [Feature] extend sort_csr/csc_by_tag to edge
* fix test ffailure in tensorflow
* refine sorting by edges
* fix docstring
* remove unnecessary mem
Co-authored-by: Xin Yao <xiny@nvidia.com>
* * Workaround for graph data saving/loading compatibility problem in Column class. There may be more places in DGL with the same issue, due to using Python serialization, instead of a more cohesive, comprehensive strategy. This is just a local fix.
* Add checking for non-empty states
* Add unit test
* Handle the case of columns without storage
Co-authored-by: ndickson <ndickson@nvidia.com>
Co-authored-by: Xin Yao <xiny@nvidia.com>
* Update nccl communicator for when NCCL is missing
* Use static_cast
* Add doc string
* Fix whitespace
* Resrtict unit test to GPU runs
Co-authored-by: Xin Yao <xiny@nvidia.com>
* Explicitly unpin tensoradapter allocated arrays
* Undo unrelated change
* Add unit test
* update unit test
* add pinned_by_dgl flag to NDArray::Container
* use dgl.ndarray for holding the pinning status
* update multi-gpu uva inference
* reinterpret cast NDArray::Container* to DLTensor* in MoveAsDLTensor
* update unpin column and examples
* add unit test for unpin column
Co-authored-by: Dominique LaSalle <dlasalle@nvidia.com>
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
* add argument reorder=False for citation_graph
* add description of the argument reorder
* add reordered/un_reordered save_path
* add version number postfix
Co-authored-by: Mufei Li <mufeili1996@gmail.com>
* * Added specialization of cublasGemm function for `__half` type, to try to address https://github.com/dmlc/dgl/issues/3988
* * Added USE_FP16 guard
* * Added test cases to test_segment_mm, to test newly-added FP16 specialization of cublasGemm
* * Replaced for loop in test_segment_mm with pytest.mark.parametrize, as recommended
Co-authored-by: Xin Yao <xiny@nvidia.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>
* Disable pinning non-contiguous memory
* Prevent views from being converted for write
* Fix linting
* Add unit tests
* Improve error message for users
* Switch to pytest function
* exclude mxnet and tensorflow from inplace pinning
* Add skip
* Restrict to pytorch backend
* Use backend to retrieve device
* Fix capitalization in decorator
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
* Add failing unit test
* Fix negative sampler edge types
* fix test
* oops
* revert
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>
* enable uva for pinsage sampler
* unit test
* modify some checks on the python side
* remove legacy random walk code
* update unit test
* update unit test
* fix unit test
* adjust checks
* move some checks to c++
* move max_nodes check to cuda kernel
* fix ci for tf
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
* fix uva sampling with features
* fix
* add is_listlike function to distinguish strings from sequence
* fix
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
* [Fix] be able to parse ids if numeric and non-numeric values are used together
* add required package info and cache note into docstring
* duplicate node id is not allowed
* WIP: TypedLinear and new RelGraphConv
* wip
* further simplify RGCN
* a bunch of tweak for performance; add basic cpu support
* update on segmm
* wip: segment.cu
* new backward kernel works
* fix a bunch of bugs in kernel; leave idx_a for future
* add nn test for typed_linear
* rgcn nn test
* bugfix in corner case; update RGCN README
* doc
* fix cpp lint
* fix lint
* fix ut
* wip: hgtconv; presorted flag for rgcn
* hgt code and ut; WIP: some fix on reorder graph
* better typed linear init
* fix ut
* fix lint; add docstring
* [Feature] support non-numeric node_id/src_id/dst_id/graph_id and rename CSVDataset
* change return value when iterate dataset
* refine data_parser
* force reload
ndickson-nvidia