Forward-merge branch-23.10 to branch-23.12

.github/workflows/build.yaml

@@ -79,6 +79,7 @@ jobs:
       extra-repo: rapidsai/cugraph-ops
       extra-repo-sha: branch-23.12
       extra-repo-deploy-key: CUGRAPH_OPS_SSH_PRIVATE_DEPLOY_KEY
+      node_type: cpu32
   wheel-publish-pylibcugraph:
     needs: wheel-build-pylibcugraph
     secrets: inherit

.github/workflows/pr.yaml

@@ -88,6 +88,7 @@ jobs:
       extra-repo: rapidsai/cugraph-ops
       extra-repo-sha: branch-23.12
       extra-repo-deploy-key: CUGRAPH_OPS_SSH_PRIVATE_DEPLOY_KEY
+      node_type: cpu32
   wheel-tests-pylibcugraph:
     needs: wheel-build-pylibcugraph
     secrets: inherit

CHANGELOG.md

@@ -1,3 +1,97 @@
+# cuGraph 23.10.00 (11 Oct 2023)
+
+## 🚨 Breaking Changes
+
+- Rename `cugraph-nx` to `nx-cugraph` ([#3840](https://github.com/rapidsai/cugraph/pull/3840)) [@eriknw](https://github.com/eriknw)
+- Remove legacy betweenness centrality ([#3829](https://github.com/rapidsai/cugraph/pull/3829)) [@jnke2016](https://github.com/jnke2016)
+- Remove Deprecated Sampling Options ([#3816](https://github.com/rapidsai/cugraph/pull/3816)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- cuGraph-PyG Loader Improvements ([#3795](https://github.com/rapidsai/cugraph/pull/3795)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- Expose threshold in louvain ([#3792](https://github.com/rapidsai/cugraph/pull/3792)) [@ChuckHastings](https://github.com/ChuckHastings)
+- Fix ValueError Caused By Batches With No Samples ([#3789](https://github.com/rapidsai/cugraph/pull/3789)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- Update to Cython 3.0.0 ([#3716](https://github.com/rapidsai/cugraph/pull/3716)) [@vyasr](https://github.com/vyasr)
+
+## 🐛 Bug Fixes
+
+- Add wget to test_notebook dependencies ([#3918](https://github.com/rapidsai/cugraph/pull/3918)) [@raydouglass](https://github.com/raydouglass)
+- Increase dask-related timeouts for CI testing ([#3907](https://github.com/rapidsai/cugraph/pull/3907)) [@jnke2016](https://github.com/jnke2016)
+- Remove `dask_cudf` dataframe for the `_make_plc_graph` while creating `cugraph.Graph` ([#3895](https://github.com/rapidsai/cugraph/pull/3895)) [@VibhuJawa](https://github.com/VibhuJawa)
+- Adds logic to handle isolated vertices at python layer ([#3886](https://github.com/rapidsai/cugraph/pull/3886)) [@naimnv](https://github.com/naimnv)
+- Update Allocator Selection in cuGraph-DGL Example ([#3877](https://github.com/rapidsai/cugraph/pull/3877)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- Add file to update-version.sh ([#3870](https://github.com/rapidsai/cugraph/pull/3870)) [@raydouglass](https://github.com/raydouglass)
+- Fix torch seed in `cugraph-dgl` and `-pyg` tests for conv layers ([#3869](https://github.com/rapidsai/cugraph/pull/3869)) [@tingyu66](https://github.com/tingyu66)
+- MFG C++ code bug fix ([#3865](https://github.com/rapidsai/cugraph/pull/3865)) [@seunghwak](https://github.com/seunghwak)
+- Fix subtle memory leak in nbr_intersection primitive ([#3858](https://github.com/rapidsai/cugraph/pull/3858)) [@ChuckHastings](https://github.com/ChuckHastings)
+- Uses `conda mambabuild` rather than `mamba mambabuild` ([#3853](https://github.com/rapidsai/cugraph/pull/3853)) [@rlratzel](https://github.com/rlratzel)
+- Remove the assumption made on the client data's keys ([#3835](https://github.com/rapidsai/cugraph/pull/3835)) [@jnke2016](https://github.com/jnke2016)
+- Disable mg tests ([#3833](https://github.com/rapidsai/cugraph/pull/3833)) [@naimnv](https://github.com/naimnv)
+- Refactor python code for similarity algos to use latest CAPI ([#3828](https://github.com/rapidsai/cugraph/pull/3828)) [@naimnv](https://github.com/naimnv)
+- [BUG] Fix Batch Renumbering of Empty Batches ([#3823](https://github.com/rapidsai/cugraph/pull/3823)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- Temporarily disable the deletion of the dask dataframe ([#3814](https://github.com/rapidsai/cugraph/pull/3814)) [@jnke2016](https://github.com/jnke2016)
+- Fix OD shortest distance matrix computation test failures. ([#3813](https://github.com/rapidsai/cugraph/pull/3813)) [@seunghwak](https://github.com/seunghwak)
+- Use rapidsai/ci:cuda11.8.0-ubuntu22.04-py3.10 for docs build ([#3811](https://github.com/rapidsai/cugraph/pull/3811)) [@naimnv](https://github.com/naimnv)
+- Fix ValueError Caused By Batches With No Samples ([#3789](https://github.com/rapidsai/cugraph/pull/3789)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- Update `python_run_cugraph` in `dependencies.yaml` ([#3781](https://github.com/rapidsai/cugraph/pull/3781)) [@nv-rliu](https://github.com/nv-rliu)
+- Fixes `KeyError` for `get_two_hop_neighbors` when called with a small start vertices list ([#3778](https://github.com/rapidsai/cugraph/pull/3778)) [@rlratzel](https://github.com/rlratzel)
+
+## 📖 Documentation
+
+- Update the docstrings of the similarity algorithms ([#3817](https://github.com/rapidsai/cugraph/pull/3817)) [@jnke2016](https://github.com/jnke2016)
+
+## 🚀 New Features
+
+- WholeGraph Feature Store for cuGraph-PyG and cuGraph-DGL ([#3874](https://github.com/rapidsai/cugraph/pull/3874)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- similarity notebook to compare link prediction algos ([#3868](https://github.com/rapidsai/cugraph/pull/3868)) [@acostadon](https://github.com/acostadon)
+- adding dining preference dataset ([#3866](https://github.com/rapidsai/cugraph/pull/3866)) [@acostadon](https://github.com/acostadon)
+- Integrate C++ Renumbering and Compression ([#3841](https://github.com/rapidsai/cugraph/pull/3841)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- Sampling post processing functions to accelerate MFG creation. ([#3815](https://github.com/rapidsai/cugraph/pull/3815)) [@seunghwak](https://github.com/seunghwak)
+- [REVIEW] Add Pure DGL Dataloading benchmark ([#3660](https://github.com/rapidsai/cugraph/pull/3660)) [@VibhuJawa](https://github.com/VibhuJawa)
+
+## 🛠️ Improvements
+
+- nx-cugraph: handle louvain with isolated nodes ([#3897](https://github.com/rapidsai/cugraph/pull/3897)) [@eriknw](https://github.com/eriknw)
+- Pin `dask` and `distributed` for `23.10` release ([#3896](https://github.com/rapidsai/cugraph/pull/3896)) [@galipremsagar](https://github.com/galipremsagar)
+- Updates the source build docs to include libcugraphops as a build prerequisite ([#3893](https://github.com/rapidsai/cugraph/pull/3893)) [@rlratzel](https://github.com/rlratzel)
+- fixes force atlas to allow string as vertex names ([#3891](https://github.com/rapidsai/cugraph/pull/3891)) [@acostadon](https://github.com/acostadon)
+- Integrate renumbering and compression to `cugraph-dgl` to accelerate MFG creation ([#3887](https://github.com/rapidsai/cugraph/pull/3887)) [@tingyu66](https://github.com/tingyu66)
+- Enable weights for MG similarity algorithms ([#3879](https://github.com/rapidsai/cugraph/pull/3879)) [@jnke2016](https://github.com/jnke2016)
+- cuGraph-PyG MFG Creation and Conversion ([#3873](https://github.com/rapidsai/cugraph/pull/3873)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- Update image names ([#3867](https://github.com/rapidsai/cugraph/pull/3867)) [@AyodeAwe](https://github.com/AyodeAwe)
+- Update to clang 16.0.6. ([#3859](https://github.com/rapidsai/cugraph/pull/3859)) [@bdice](https://github.com/bdice)
+- Updates to build and test `nx-cugraph` wheel as part of CI and nightly workflows ([#3852](https://github.com/rapidsai/cugraph/pull/3852)) [@rlratzel](https://github.com/rlratzel)
+- Update `cugraph-dgl` conv layers to use improved graph class ([#3849](https://github.com/rapidsai/cugraph/pull/3849)) [@tingyu66](https://github.com/tingyu66)
+- Add entry point to tell NetworkX about nx-cugraph without importing it. ([#3848](https://github.com/rapidsai/cugraph/pull/3848)) [@eriknw](https://github.com/eriknw)
+- [IMP] Add ability to get batch size from the loader in cuGraph-PyG ([#3846](https://github.com/rapidsai/cugraph/pull/3846)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- Refactor legacy k truss ([#3843](https://github.com/rapidsai/cugraph/pull/3843)) [@jnke2016](https://github.com/jnke2016)
+- Use new `raft::compiled_static` targets ([#3842](https://github.com/rapidsai/cugraph/pull/3842)) [@divyegala](https://github.com/divyegala)
+- Rename `cugraph-nx` to `nx-cugraph` ([#3840](https://github.com/rapidsai/cugraph/pull/3840)) [@eriknw](https://github.com/eriknw)
+- Add cuGraph devcontainers ([#3838](https://github.com/rapidsai/cugraph/pull/3838)) [@trxcllnt](https://github.com/trxcllnt)
+- Enable temporarily disabled MG tests ([#3837](https://github.com/rapidsai/cugraph/pull/3837)) [@naimnv](https://github.com/naimnv)
+- Remove legacy betweenness centrality ([#3829](https://github.com/rapidsai/cugraph/pull/3829)) [@jnke2016](https://github.com/jnke2016)
+- Use `copy-pr-bot` ([#3827](https://github.com/rapidsai/cugraph/pull/3827)) [@ajschmidt8](https://github.com/ajschmidt8)
+- Update README.md ([#3826](https://github.com/rapidsai/cugraph/pull/3826)) [@lmeyerov](https://github.com/lmeyerov)
+- Adding metadata getter methods to datasets API ([#3821](https://github.com/rapidsai/cugraph/pull/3821)) [@nv-rliu](https://github.com/nv-rliu)
+- Unpin `dask` and `distributed` for `23.10` development ([#3818](https://github.com/rapidsai/cugraph/pull/3818)) [@galipremsagar](https://github.com/galipremsagar)
+- Remove Deprecated Sampling Options ([#3816](https://github.com/rapidsai/cugraph/pull/3816)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- [REVIEW] Cugraph dgl block improvements ([#3810](https://github.com/rapidsai/cugraph/pull/3810)) [@VibhuJawa](https://github.com/VibhuJawa)
+- Simplify wheel build scripts and allow alphas of RAPIDS dependencies ([#3809](https://github.com/rapidsai/cugraph/pull/3809)) [@vyasr](https://github.com/vyasr)
+- Allow cugraph-nx to run networkx tests for nx versions 3.0, 3.1, and 3.2 ([#3808](https://github.com/rapidsai/cugraph/pull/3808)) [@eriknw](https://github.com/eriknw)
+- Add `louvain_communities` to cugraph-nx ([#3803](https://github.com/rapidsai/cugraph/pull/3803)) [@eriknw](https://github.com/eriknw)
+- Adds missing copyright and license text to __init__.py package files ([#3799](https://github.com/rapidsai/cugraph/pull/3799)) [@rlratzel](https://github.com/rlratzel)
+- cuGraph-PyG Loader Improvements ([#3795](https://github.com/rapidsai/cugraph/pull/3795)) [@alexbarghi-nv](https://github.com/alexbarghi-nv)
+- Adds updates to build wheel and conda packages for `cugraph-nx` ([#3793](https://github.com/rapidsai/cugraph/pull/3793)) [@rlratzel](https://github.com/rlratzel)
+- Expose threshold in louvain ([#3792](https://github.com/rapidsai/cugraph/pull/3792)) [@ChuckHastings](https://github.com/ChuckHastings)
+- Allow models to use a lightweight sparse structure ([#3782](https://github.com/rapidsai/cugraph/pull/3782)) [@tingyu66](https://github.com/tingyu66)
+- Clean-up old testing conventions in `test_ecg.py` ([#3779](https://github.com/rapidsai/cugraph/pull/3779)) [@nv-rliu](https://github.com/nv-rliu)
+- Calling `dataset.get_edgelist()` returns a copy of an edge list instead of global ([#3777](https://github.com/rapidsai/cugraph/pull/3777)) [@nv-rliu](https://github.com/nv-rliu)
+- Update dgl benchmarks ([#3775](https://github.com/rapidsai/cugraph/pull/3775)) [@VibhuJawa](https://github.com/VibhuJawa)
+- Forward-merge branch-23.08 to branch-23.10 ([#3774](https://github.com/rapidsai/cugraph/pull/3774)) [@nv-rliu](https://github.com/nv-rliu)
+- Migrate upstream models to `cugraph-pyg` ([#3763](https://github.com/rapidsai/cugraph/pull/3763)) [@tingyu66](https://github.com/tingyu66)
+- Branch 23.10 merge 23.08 ([#3743](https://github.com/rapidsai/cugraph/pull/3743)) [@vyasr](https://github.com/vyasr)
+- Update to Cython 3.0.0 ([#3716](https://github.com/rapidsai/cugraph/pull/3716)) [@vyasr](https://github.com/vyasr)
+- Testing util improvements and refactoring ([#3705](https://github.com/rapidsai/cugraph/pull/3705)) [@betochimas](https://github.com/betochimas)
+- Add new cugraph-nx package (networkx backend using pylibcugraph) ([#3614](https://github.com/rapidsai/cugraph/pull/3614)) [@eriknw](https://github.com/eriknw)
+- New mtmg API for integration ([#3521](https://github.com/rapidsai/cugraph/pull/3521)) [@ChuckHastings](https://github.com/ChuckHastings)
+
 # cuGraph 23.08.00 (9 Aug 2023)
 
 ## 🚨 Breaking Changes

ci/test_python.sh

@@ -68,7 +68,7 @@ pushd python/cugraph/cugraph
 DASK_WORKER_DEVICES="0" \
 DASK_DISTRIBUTED__SCHEDULER__WORKER_TTL="1000s" \
 DASK_DISTRIBUTED__COMM__TIMEOUTS__CONNECT="1000s" \
-DASK_CUDA_WAIT_WORKERS_MIN_TIMEOUT=20 \
+DASK_CUDA_WAIT_WORKERS_MIN_TIMEOUT="1000s" \
 pytest \
   -v \
   --benchmark-disable \
@@ -203,8 +203,11 @@ if [[ "${RAPIDS_CUDA_VERSION}" == "11.8.0" ]]; then
       --channel pytorch \
       --channel nvidia \
       'pyg=2.3' \
-      'pytorch>=2.0' \
-      'pytorch-cuda>=11.8'
+      'pytorch=2.0.0' \
+      'pytorch-cuda=11.8'
+
+    # Install pyg dependencies (which requires pip)
+    pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.0.0+cu118.html
 
     rapids-mamba-retry install \
       --channel "${CPP_CHANNEL}" \

ci/test_wheel.sh

@@ -24,6 +24,6 @@ else
     RAPIDS_DATASET_ROOT_DIR=`pwd`/datasets \
     DASK_DISTRIBUTED__SCHEDULER__WORKER_TTL="1000s" \
     DASK_DISTRIBUTED__COMM__TIMEOUTS__CONNECT="1000s" \
-    DASK_CUDA_WAIT_WORKERS_MIN_TIMEOUT=20 \
+    DASK_CUDA_WAIT_WORKERS_MIN_TIMEOUT="1000s" \
     python -m pytest ./python/${package_name}/${python_package_name}/tests
 fi

conda/environments/all_cuda-118_arch-x86_64.yaml

@@ -75,5 +75,6 @@ dependencies:
 - sphinxcontrib-websupport
 - ucx-proc=*=gpu
 - ucx-py==0.35.*
+- wget
 - wheel
 name: all_cuda-118_arch-x86_64

conda/environments/all_cuda-120_arch-x86_64.yaml

@@ -74,5 +74,6 @@ dependencies:
 - sphinxcontrib-websupport
 - ucx-proc=*=gpu
 - ucx-py==0.35.*
+- wget
 - wheel
 name: all_cuda-120_arch-x86_64

dependencies.yaml

@@ -453,6 +453,9 @@ dependencies:
         packages:
           - ipython
           - notebook>=0.5.0
+      - output_types: [conda]
+        packages:
+          - wget
   test_python_common:
     common:
       - output_types: [conda, pyproject]

python/cugraph-pyg/cugraph_pyg/data/cugraph_store.py

@@ -819,8 +819,8 @@ def _get_renumbered_edge_groups_from_sample(
           before this one to get the noi_index.
 
         Example Input: Series({
-                'sources': [0, 5, 11, 3],
-                'destinations': [8, 2, 3, 5]},
+                'majors': [0, 5, 11, 3],
+                'minors': [8, 2, 3, 5]},
                 'edge_type': [1, 3, 5, 14]
             }),
             {
@@ -865,24 +865,22 @@ def _get_renumbered_edge_groups_from_sample(
                     index=cupy.asarray(id_table),
                 ).sort_index()
 
-                # Renumber the sources using binary search
+                # Renumber the majors using binary search
                 # Step 1: get the index of the new id
                 ix_r = torch.searchsorted(
                     torch.as_tensor(id_map.index.values, device="cuda"),
-                    torch.as_tensor(sampling_results.sources.values, device="cuda"),
+                    torch.as_tensor(sampling_results.majors.values, device="cuda"),
                 )
                 # Step 2: Go from id indices to actual ids
                 row_dict[t_pyg_type] = torch.as_tensor(id_map.values, device="cuda")[
                     ix_r
                 ]
 
-                # Renumber the destinations using binary search
+                # Renumber the minors using binary search
                 # Step 1: get the index of the new id
                 ix_c = torch.searchsorted(
                     torch.as_tensor(id_map.index.values, device="cuda"),
-                    torch.as_tensor(
-                        sampling_results.destinations.values, device="cuda"
-                    ),
+                    torch.as_tensor(sampling_results.minors.values, device="cuda"),
                 )
                 # Step 2: Go from id indices to actual ids
                 col_dict[t_pyg_type] = torch.as_tensor(id_map.values, device="cuda")[
@@ -897,7 +895,7 @@ def _get_renumbered_edge_groups_from_sample(
                         "new_id": cupy.arange(dst_id_table.shape[0]),
                     }
                 ).set_index("dst")
-                dst = dst_id_map["new_id"].loc[sampling_results.destinations]
+                dst = dst_id_map["new_id"].loc[sampling_results.minors]
                 col_dict[t_pyg_type] = torch.as_tensor(dst.values, device="cuda")
 
                 src_id_table = noi_index[src_type]
@@ -907,7 +905,7 @@ def _get_renumbered_edge_groups_from_sample(
                         "new_id": cupy.arange(src_id_table.shape[0]),
                     }
                 ).set_index("src")
-                src = src_id_map["new_id"].loc[sampling_results.sources]
+                src = src_id_map["new_id"].loc[sampling_results.majors]
                 row_dict[t_pyg_type] = torch.as_tensor(src.values, device="cuda")
 
         else:
@@ -929,12 +927,12 @@ def _get_renumbered_edge_groups_from_sample(
                 else:  # CSC
                     dst_type, _, src_type = pyg_can_edge_type
 
-                # Get the de-offsetted destinations
+                # Get the de-offsetted minors
                 dst_num_type = self._numeric_vertex_type_from_name(dst_type)
-                destinations = torch.as_tensor(
-                    sampling_results.destinations.iloc[ix].values, device="cuda"
+                minors = torch.as_tensor(
+                    sampling_results.minors.iloc[ix].values, device="cuda"
                 )
-                destinations -= self.__vertex_type_offsets["start"][dst_num_type]
+                minors -= self.__vertex_type_offsets["start"][dst_num_type]
 
                 # Create the col entry for this type
                 dst_id_table = noi_index[dst_type]
@@ -944,15 +942,15 @@ def _get_renumbered_edge_groups_from_sample(
                     .rename(columns={"index": "new_id"})
                     .set_index("dst")
                 )
-                dst = dst_id_map["new_id"].loc[cupy.asarray(destinations)]
+                dst = dst_id_map["new_id"].loc[cupy.asarray(minors)]
                 col_dict[pyg_can_edge_type] = torch.as_tensor(dst.values, device="cuda")
 
-                # Get the de-offsetted sources
+                # Get the de-offsetted majors
                 src_num_type = self._numeric_vertex_type_from_name(src_type)
-                sources = torch.as_tensor(
-                    sampling_results.sources.iloc[ix].values, device="cuda"
+                majors = torch.as_tensor(
+                    sampling_results.majors.iloc[ix].values, device="cuda"
                 )
-                sources -= self.__vertex_type_offsets["start"][src_num_type]
+                majors -= self.__vertex_type_offsets["start"][src_num_type]
 
                 # Create the row entry for this type
                 src_id_table = noi_index[src_type]
@@ -962,7 +960,7 @@ def _get_renumbered_edge_groups_from_sample(
                     .rename(columns={"index": "new_id"})
                     .set_index("src")
                 )
-                src = src_id_map["new_id"].loc[cupy.asarray(sources)]
+                src = src_id_map["new_id"].loc[cupy.asarray(majors)]
                 row_dict[pyg_can_edge_type] = torch.as_tensor(src.values, device="cuda")
 
         return row_dict, col_dict