diff --git a/README.md b/README.md
index 857406075e0..c8fc07d5ae2 100644
--- a/README.md
+++ b/README.md
@@ -64,7 +64,6 @@ That's it. NetworkX now leverages cuGraph for accelerated graph algorithms.
- [libcugraph (C/C++/CUDA)](./readme_pages/libcugraph.md)
- [nx-cugraph](https://rapids.ai/nx-cugraph/)
- [cugraph-service](./readme_pages/cugraph_service.md)
- - [cugraph-ops](./readme_pages/cugraph_ops.md)
- API Docs
- Python
- [Python Nightly](https://docs.rapids.ai/api/cugraph/nightly/)
diff --git a/build.sh b/build.sh
index 756045461dd..645a2459e73 100755
--- a/build.sh
+++ b/build.sh
@@ -331,7 +331,7 @@ if hasArg docs || hasArg all; then
${CMAKE_VERBOSE_OPTION}
fi
- for PROJECT in libcugraphops libwholegraph; do
+ for PROJECT in libwholegraph; do
XML_DIR="${REPODIR}/docs/cugraph/${PROJECT}"
rm -rf "${XML_DIR}"
mkdir -p "${XML_DIR}"
diff --git a/ci/build_docs.sh b/ci/build_docs.sh
index 2d7e90da8d0..1c90f5b243f 100755
--- a/ci/build_docs.sh
+++ b/ci/build_docs.sh
@@ -46,14 +46,13 @@ rapids-mamba-retry install \
"cugraph-service-server=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
"cugraph-service-client=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
"libcugraph_etl=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
- "pylibcugraphops=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
"pylibwholegraph=${RAPIDS_VERSION_MAJOR_MINOR}.*" \
'pytorch>=2.3' \
"cuda-version=${CONDA_CUDA_VERSION}"
export RAPIDS_DOCS_DIR="$(mktemp -d)"
-for PROJECT in libcugraphops libwholegraph; do
+for PROJECT in libwholegraph; do
rapids-logger "Download ${PROJECT} xml_tar"
TMP_DIR=$(mktemp -d)
export XML_DIR_${PROJECT^^}="$TMP_DIR"
diff --git a/ci/release/update-version.sh b/ci/release/update-version.sh
index 9aff2ec2711..a73745f2c0e 100755
--- a/ci/release/update-version.sh
+++ b/ci/release/update-version.sh
@@ -57,12 +57,10 @@ DEPENDENCIES=(
dask-cuda
dask-cudf
libcudf
- libcugraphops
libraft
libraft-headers
librmm
pylibcugraph
- pylibcugraphops
pylibwholegraph
pylibraft
pyraft
diff --git a/conda/environments/all_cuda-118_arch-x86_64.yaml b/conda/environments/all_cuda-118_arch-x86_64.yaml
index 9fdba6e5970..e9f6842e8b8 100644
--- a/conda/environments/all_cuda-118_arch-x86_64.yaml
+++ b/conda/environments/all_cuda-118_arch-x86_64.yaml
@@ -44,7 +44,6 @@ dependencies:
- pre-commit
- pydantic
- pydata-sphinx-theme
-- pylibcugraphops==25.2.*,>=0.0.0a0
- pylibraft==25.2.*,>=0.0.0a0
- pylibwholegraph==25.2.*,>=0.0.0a0
- pytest
diff --git a/conda/environments/all_cuda-125_arch-x86_64.yaml b/conda/environments/all_cuda-125_arch-x86_64.yaml
index a64e0f481d5..13e102862ab 100644
--- a/conda/environments/all_cuda-125_arch-x86_64.yaml
+++ b/conda/environments/all_cuda-125_arch-x86_64.yaml
@@ -49,7 +49,6 @@ dependencies:
- pre-commit
- pydantic
- pydata-sphinx-theme
-- pylibcugraphops==25.2.*,>=0.0.0a0
- pylibraft==25.2.*,>=0.0.0a0
- pylibwholegraph==25.2.*,>=0.0.0a0
- pytest
diff --git a/dependencies.yaml b/dependencies.yaml
index 821ed7a6a84..93983a1a29b 100644
--- a/dependencies.yaml
+++ b/dependencies.yaml
@@ -333,7 +333,6 @@ dependencies:
- nbsphinx
- numpydoc
- pydata-sphinx-theme
- - pylibcugraphops==25.2.*,>=0.0.0a0
- recommonmark
- sphinx-copybutton
- sphinx-markdown-tables
diff --git a/docs/cugraph/source/api_docs/cugraph-ops/c_cpp/index.rst b/docs/cugraph/source/api_docs/cugraph-ops/c_cpp/index.rst
deleted file mode 100644
index 39dae955ef3..00000000000
--- a/docs/cugraph/source/api_docs/cugraph-ops/c_cpp/index.rst
+++ /dev/null
@@ -1,2 +0,0 @@
-cugraph-ops C++ API Reference
-=============================
diff --git a/docs/cugraph/source/api_docs/cugraph-ops/index.rst b/docs/cugraph/source/api_docs/cugraph-ops/index.rst
deleted file mode 100644
index 0f6a6c937d3..00000000000
--- a/docs/cugraph/source/api_docs/cugraph-ops/index.rst
+++ /dev/null
@@ -1,11 +0,0 @@
-cugraph-ops API reference
-=========================
-
-This page provides a list of all publicly accessible modules, methods and classes through `pylibcugraphops.*` namespace.
-
-.. toctree::
- :maxdepth: 2
- :caption: API Documentation
-
- python/index
- c_cpp/index
diff --git a/docs/cugraph/source/api_docs/cugraph-ops/python/dimenet.rst b/docs/cugraph/source/api_docs/cugraph-ops/python/dimenet.rst
deleted file mode 100644
index 6fadcc57b22..00000000000
--- a/docs/cugraph/source/api_docs/cugraph-ops/python/dimenet.rst
+++ /dev/null
@@ -1,24 +0,0 @@
-=================
-Dimenet operators
-=================
-
-.. currentmodule:: pylibcugraphops
-
-Radial Basis Functions
-----------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- dimenet.radial_basis_fwd
- dimenet.radial_basis_bwd
- dimenet.radial_basis_bwd_bwd
-
-Edge-to-Edge Aggregation
--------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- dimenet.agg_edge_to_edge_fwd
- dimenet.agg_edge_to_edge_bwd
- dimenet.agg_edge_to_edge_bwd2_grad
- dimenet.agg_edge_to_edge_bwd2_main
diff --git a/docs/cugraph/source/api_docs/cugraph-ops/python/graph_types.rst b/docs/cugraph/source/api_docs/cugraph-ops/python/graph_types.rst
deleted file mode 100644
index 141d40393a5..00000000000
--- a/docs/cugraph/source/api_docs/cugraph-ops/python/graph_types.rst
+++ /dev/null
@@ -1,34 +0,0 @@
-===========
-Graph types
-===========
-
-.. currentmodule:: pylibcugraphops
-
-
-CSC Graph
------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- make_csc
-
-Heterogenous CSC Graph
-----------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- make_csc_hg
-
-Bipartite Graph
------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- make_bipartite_csc
-
-Heterogenous Bipartite Graph
-----------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- make_bipartite_csc_hg
diff --git a/docs/cugraph/source/api_docs/cugraph-ops/python/index.rst b/docs/cugraph/source/api_docs/cugraph-ops/python/index.rst
deleted file mode 100644
index fb25f2fa005..00000000000
--- a/docs/cugraph/source/api_docs/cugraph-ops/python/index.rst
+++ /dev/null
@@ -1,13 +0,0 @@
-cugraph-ops Python API reference
-================================
-
-This page provides a list of all publicly accessible modules, methods and classes through `pylibcugraphops.*` namespace.
-
-.. toctree::
- :maxdepth: 2
- :caption: API Documentation
-
- graph_types
- operators
- dimenet
- pytorch
diff --git a/docs/cugraph/source/api_docs/cugraph-ops/python/operators.rst b/docs/cugraph/source/api_docs/cugraph-ops/python/operators.rst
deleted file mode 100644
index 8b5efd7aa36..00000000000
--- a/docs/cugraph/source/api_docs/cugraph-ops/python/operators.rst
+++ /dev/null
@@ -1,109 +0,0 @@
-=============================
-Operators for Message-Passing
-=============================
-
-.. currentmodule:: pylibcugraphops
-
-Simple Neighborhood Aggregator (SAGEConv)
------------------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.agg_simple_n2n_fwd
- operators.agg_simple_n2n_bwd
- operators.agg_simple_e2n_fwd
- operators.agg_simple_e2n_bwd
- operators.agg_simple_n2n_e2n_fwd
- operators.agg_simple_n2n_e2n_bwd
-
- operators.agg_concat_n2n_fwd
- operators.agg_concat_n2n_bwd
- operators.agg_concat_e2n_fwd
- operators.agg_concat_e2n_bwd
- operators.agg_concat_n2n_e2n_fwd
- operators.agg_concat_n2n_e2n_bwd
-
-
-Weighted Neighborhood Aggregation
----------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.agg_weighted_n2n_fwd
- operators.agg_weighted_n2n_bwd
- operators.agg_concat_weighted_n2n_fwd
- operators.agg_concat_weighted_n2n_bwd
-
-Heterogenous Aggregator using Basis Decomposition (RGCNConv)
-------------------------------------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.agg_hg_basis_n2n_post_fwd
- operators.agg_hg_basis_n2n_post_bwd
-
-Graph Attention (GATConv/GATv2Conv)
------------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.mha_gat_n2n_fwd_bf16_fp32
- operators.mha_gat_n2n_fwd_fp16_fp32
- operators.mha_gat_n2n_fwd_fp32_fp32
- operators.mha_gat_n2n_bwd_bf16_bf16_bf16_fp32
- operators.mha_gat_n2n_bwd_bf16_bf16_fp32_fp32
- operators.mha_gat_n2n_bwd_bf16_fp32_fp32_fp32
- operators.mha_gat_n2n_bwd_fp16_fp16_fp16_fp32
- operators.mha_gat_n2n_bwd_fp16_fp16_fp32_fp32
- operators.mha_gat_n2n_bwd_fp16_fp32_fp32_fp32
- operators.mha_gat_n2n_bwd_fp32_fp32_fp32_fp32
- operators.mha_gat_n2n_efeat_fwd_bf16_fp32
- operators.mha_gat_n2n_efeat_fwd_fp16_fp32
- operators.mha_gat_n2n_efeat_fwd_fp32_fp32
- operators.mha_gat_n2n_efeat_bwd_bf16_bf16_bf16_fp32
- operators.mha_gat_n2n_efeat_bwd_bf16_bf16_fp32_fp32
- operators.mha_gat_n2n_efeat_bwd_bf16_fp32_fp32_fp32
- operators.mha_gat_n2n_efeat_bwd_fp16_fp16_fp16_fp32
- operators.mha_gat_n2n_efeat_bwd_fp16_fp16_fp32_fp32
- operators.mha_gat_n2n_efeat_bwd_fp16_fp32_fp32_fp32
- operators.mha_gat_n2n_efeat_bwd_fp32_fp32_fp32_fp32
-
- operators.mha_gat_v2_n2n_fwd
- operators.mha_gat_v2_n2n_bwd
- operators.mha_gat_v2_n2n_efeat_fwd
- operators.mha_gat_v2_n2n_efeat_bwd
-
-Transformer-like Graph Attention (TransformerConv)
---------------------------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.mha_gat_v2_n2n_fwd
- operators.mha_gat_v2_n2n_bwd
- operators.mha_gat_v2_n2n_efeat_fwd
- operators.mha_gat_v2_n2n_efeat_bwd
-
-Directional Message-Passing (DMPNN)
------------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.agg_dmpnn_e2e_fwd
- operators.agg_dmpnn_e2e_bwd
-
-Update Edges: Concatenation or Sum of Edge and Node Features
-------------------------------------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.update_efeat_e2e_concat_fwd
- operators.update_efeat_e2e_concat_bwd
-
- operators.update_efeat_e2e_sum_fwd
- operators.update_efeat_e2e_sum_bwd
-
- operators.update_efeat_e2e_concat_fwd
- operators.update_efeat_e2e_concat_bwd
-
- operators.update_efeat_e2e_sum_fwd
- operators.update_efeat_e2e_sum_bwd
diff --git a/docs/cugraph/source/api_docs/cugraph-ops/python/pytorch.rst b/docs/cugraph/source/api_docs/cugraph-ops/python/pytorch.rst
deleted file mode 100644
index d2074df15b0..00000000000
--- a/docs/cugraph/source/api_docs/cugraph-ops/python/pytorch.rst
+++ /dev/null
@@ -1,36 +0,0 @@
-==========================
-PyTorch Autograd Wrappers
-==========================
-
-.. currentmodule:: pylibcugraphops.pytorch
-
-Simple Neighborhood Aggregator (SAGEConv)
------------------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.agg_concat_n2n
-
-Graph Attention (GATConv/GATv2Conv)
------------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.mha_gat_n2n
- operators.mha_gat_v2_n2n
-
-Heterogenous Aggregator using Basis Decomposition (RGCNConv)
-------------------------------------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.agg_hg_basis_n2n_post
-
-
-Update Edges: Concatenation or Sum of Edge and Node Features
-------------------------------------------------------------
-.. autosummary::
- :toctree: ../../api/ops
-
- operators.update_efeat_e2e
- operators.update_efeat_e2e
diff --git a/docs/cugraph/source/api_docs/index.rst b/docs/cugraph/source/api_docs/index.rst
index c4b90b5794d..a3cae3468e5 100644
--- a/docs/cugraph/source/api_docs/index.rst
+++ b/docs/cugraph/source/api_docs/index.rst
@@ -24,7 +24,6 @@ Graph Neural Networks API Documentation
cugraph-dgl/cugraph_dgl.rst
cugraph-pyg/cugraph_pyg.rst
- cugraph-ops/index.rst
wholegraph/index.rst
Additional Graph Packages API Documentation
diff --git a/docs/cugraph/source/conf.py b/docs/cugraph/source/conf.py
index 66bc3137fba..5c1b812435b 100644
--- a/docs/cugraph/source/conf.py
+++ b/docs/cugraph/source/conf.py
@@ -222,7 +222,6 @@ def setup(app):
breathe_projects = {
'libcugraph': os.environ['XML_DIR_LIBCUGRAPH'],
- 'libcugraphops': os.environ['XML_DIR_LIBCUGRAPHOPS'],
'libwholegraph': os.environ['XML_DIR_LIBWHOLEGRAPH']
}
diff --git a/docs/cugraph/source/graph_support/cugraphops_support.rst b/docs/cugraph/source/graph_support/cugraphops_support.rst
deleted file mode 100644
index 96b13f62a9c..00000000000
--- a/docs/cugraph/source/graph_support/cugraphops_support.rst
+++ /dev/null
@@ -1,10 +0,0 @@
-==================
-cugraphops Support
-==================
-
-cugraph-ops aims to be a low-level, framework agnostic library providing commonly used computational primitives for GNNs and other graph operations.
-
-.. toctree::
- :maxdepth: 3
-
- https://github.com/rapidsai/cugraph/blob/branch-24.06/readme_pages/cugraph_ops.md
diff --git a/docs/cugraph/source/graph_support/gnn_support.rst b/docs/cugraph/source/graph_support/gnn_support.rst
index 639b657c64d..71586621608 100644
--- a/docs/cugraph/source/graph_support/gnn_support.rst
+++ b/docs/cugraph/source/graph_support/gnn_support.rst
@@ -8,5 +8,4 @@ Graph Neural Network Support
PyG_support.md
DGL_support.md
- cugraphops_support.rst
wholegraph_support.md
diff --git a/docs/cugraph/source/wholegraph/installation/container.md b/docs/cugraph/source/wholegraph/installation/container.md
index 6aac53cf88f..4068ead27b2 100644
--- a/docs/cugraph/source/wholegraph/installation/container.md
+++ b/docs/cugraph/source/wholegraph/installation/container.md
@@ -21,7 +21,7 @@ RUN pip3 install -U py
RUN pip3 install Cython setuputils3 scikit-build nanobind pytest-forked pytest
```
-To run GNN applications, you may also need cuGraphOps, DGL and/or PyG libraries to run the GNN layers.
+To run GNN applications, you may also need DGL and/or PyG libraries to run the GNN layers.
You may refer to [DGL](https://www.dgl.ai/pages/start.html) or [PyG](https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html)
For example, to install DGL, you may need to add:
diff --git a/python/cugraph/cugraph/tests/sampling/test_random_walks.py b/python/cugraph/cugraph/tests/sampling/test_random_walks.py
index 9c94e036683..76ceb478518 100644
--- a/python/cugraph/cugraph/tests/sampling/test_random_walks.py
+++ b/python/cugraph/cugraph/tests/sampling/test_random_walks.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2020-2023, NVIDIA CORPORATION.:
+# Copyright (c) 2020-2024, NVIDIA CORPORATION.:
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
@@ -222,7 +222,6 @@ def test_random_walks_invalid_max_dept(graph_file, directed, max_depth):
@pytest.mark.sg
-@pytest.mark.cugraph_ops
@pytest.mark.parametrize("graph_file", SMALL_DATASETS)
@pytest.mark.parametrize("directed", DIRECTED_GRAPH_OPTIONS)
def test_random_walks_coalesced(graph_file, directed):
@@ -246,7 +245,6 @@ def test_random_walks_coalesced(graph_file, directed):
@pytest.mark.sg
-@pytest.mark.cugraph_ops
@pytest.mark.parametrize("graph_file", SMALL_DATASETS)
@pytest.mark.parametrize("directed", DIRECTED_GRAPH_OPTIONS)
def test_random_walks_padded_0(graph_file, directed):
@@ -271,7 +269,6 @@ def test_random_walks_padded_0(graph_file, directed):
@pytest.mark.sg
-@pytest.mark.cugraph_ops
def test_random_walks_padded_1():
max_depth = random.randint(2, 10)
@@ -294,7 +291,6 @@ def test_random_walks_padded_1():
@pytest.mark.sg
-@pytest.mark.cugraph_ops
@pytest.mark.parametrize("graph_file", SMALL_DATASETS)
def test_random_walks_nx(graph_file):
G = graph_file.get_graph(create_using=cugraph.Graph(directed=True))
diff --git a/python/cugraph/cugraph/tests/sampling/test_random_walks_mg.py b/python/cugraph/cugraph/tests/sampling/test_random_walks_mg.py
index 34eeb2902f8..96b34c638b5 100644
--- a/python/cugraph/cugraph/tests/sampling/test_random_walks_mg.py
+++ b/python/cugraph/cugraph/tests/sampling/test_random_walks_mg.py
@@ -203,7 +203,6 @@ def input_graph(request):
@pytest.mark.mg
-@pytest.mark.cugraph_ops
def test_dask_mg_random_walks(dask_client, input_graph):
path_data, seeds, max_depth = calc_random_walks(input_graph)
df_G = input_graph.input_df.compute().reset_index(drop=True)
diff --git a/python/cugraph/cugraph/tests/sampling/test_uniform_neighbor_sample.py b/python/cugraph/cugraph/tests/sampling/test_uniform_neighbor_sample.py
index ad0dbe77f7d..65687a1a227 100644
--- a/python/cugraph/cugraph/tests/sampling/test_uniform_neighbor_sample.py
+++ b/python/cugraph/cugraph/tests/sampling/test_uniform_neighbor_sample.py
@@ -130,7 +130,6 @@ def simple_unweighted_input_expected_output(request):
# Tests
# =============================================================================
@pytest.mark.sg
-@pytest.mark.cugraph_ops
def test_uniform_neighbor_sample_simple(input_combo):
G = input_combo["Graph"]
@@ -229,7 +228,6 @@ def test_uniform_neighbor_sample_simple(input_combo):
@pytest.mark.sg
-@pytest.mark.cugraph_ops
@pytest.mark.parametrize("directed", IS_DIRECTED)
def test_uniform_neighbor_sample_tree(directed):
@@ -301,7 +299,6 @@ def test_uniform_neighbor_sample_tree(directed):
@pytest.mark.sg
-@pytest.mark.cugraph_ops
def test_uniform_neighbor_sample_unweighted(simple_unweighted_input_expected_output):
test_data = simple_unweighted_input_expected_output
@@ -322,7 +319,6 @@ def test_uniform_neighbor_sample_unweighted(simple_unweighted_input_expected_out
@pytest.mark.sg
-@pytest.mark.cugraph_ops
@pytest.mark.parametrize("return_offsets", [True, False])
@pytest.mark.parametrize("include_hop_column", [True, False])
def test_uniform_neighbor_sample_edge_properties(return_offsets, include_hop_column):
diff --git a/python/cugraph/cugraph/tests/sampling/test_uniform_neighbor_sample_mg.py b/python/cugraph/cugraph/tests/sampling/test_uniform_neighbor_sample_mg.py
index 4a85b49a66e..6343b0ff9f3 100644
--- a/python/cugraph/cugraph/tests/sampling/test_uniform_neighbor_sample_mg.py
+++ b/python/cugraph/cugraph/tests/sampling/test_uniform_neighbor_sample_mg.py
@@ -131,7 +131,6 @@ def input_combo(request):
# Tests
# =============================================================================
@pytest.mark.mg
-@pytest.mark.cugraph_ops
def test_mg_uniform_neighbor_sample_simple(dask_client, input_combo):
dg = input_combo["MGGraph"]
@@ -220,7 +219,6 @@ def test_mg_uniform_neighbor_sample_simple(dask_client, input_combo):
@pytest.mark.mg
-@pytest.mark.cugraph_ops
@pytest.mark.parametrize("directed", IS_DIRECTED)
def test_mg_uniform_neighbor_sample_tree(dask_client, directed):
@@ -286,7 +284,6 @@ def test_mg_uniform_neighbor_sample_tree(dask_client, directed):
@pytest.mark.mg
@pytest.mark.skipif(is_single_gpu(), reason="FIXME: MG test fails on single-GPU")
-@pytest.mark.cugraph_ops
def test_mg_uniform_neighbor_sample_unweighted(dask_client):
df = cudf.DataFrame(
{
@@ -321,7 +318,6 @@ def test_mg_uniform_neighbor_sample_unweighted(dask_client):
@pytest.mark.mg
@pytest.mark.skipif(is_single_gpu(), reason="FIXME: MG test fails on single-GPU")
-@pytest.mark.cugraph_ops
def test_mg_uniform_neighbor_sample_ensure_no_duplicates(dask_client):
# See issue #2760
# This ensures that the starts are properly distributed
@@ -347,7 +343,6 @@ def test_mg_uniform_neighbor_sample_ensure_no_duplicates(dask_client):
@pytest.mark.mg
-@pytest.mark.cugraph_ops
@pytest.mark.parametrize("return_offsets", [True, False])
def test_uniform_neighbor_sample_edge_properties(dask_client, return_offsets):
n_workers = len(dask_client.scheduler_info()["workers"])
diff --git a/python/pylibcugraph/pylibcugraph/tests/test_uniform_neighbor_sample.py b/python/pylibcugraph/pylibcugraph/tests/test_uniform_neighbor_sample.py
index ffa90731483..4dafeb19032 100644
--- a/python/pylibcugraph/pylibcugraph/tests/test_uniform_neighbor_sample.py
+++ b/python/pylibcugraph/pylibcugraph/tests/test_uniform_neighbor_sample.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2022-2023, NVIDIA CORPORATION.
+# Copyright (c) 2022-2024, NVIDIA CORPORATION.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
@@ -183,7 +183,6 @@ def test_neighborhood_sampling_cudf(
)
-@pytest.mark.cugraph_ops
def test_neighborhood_sampling_large_sg_graph(gpubenchmark):
"""
Use a large SG graph and set input args accordingly to test/benchmark
diff --git a/python/pylibcugraph/pytest.ini b/python/pylibcugraph/pytest.ini
index d5ade9f4836..8ca4e198441 100644
--- a/python/pylibcugraph/pytest.ini
+++ b/python/pylibcugraph/pytest.ini
@@ -12,7 +12,4 @@
# limitations under the License.
[pytest]
-markers =
- cugraph_ops: Tests requiring cugraph-ops
-
addopts = --tb=native
diff --git a/readme_pages/CONTRIBUTING.md b/readme_pages/CONTRIBUTING.md
index ffe1ef1831b..01d5f263624 100644
--- a/readme_pages/CONTRIBUTING.md
+++ b/readme_pages/CONTRIBUTING.md
@@ -1,5 +1,5 @@
# Contributing to cuGraph
-cuGraph, for the most part, is an open-source project where we encourage community involvement. The cugraph-ops package is the expection being a closed-source package.
+cuGraph, for the most part, is an open-source project where we encourage community involvement.
There are multiple ways to be involved and contribute to the cuGraph community, the top paths are listed below:
diff --git a/readme_pages/cugraph_ops.md b/readme_pages/cugraph_ops.md
deleted file mode 100644
index 7bd4ac55185..00000000000
--- a/readme_pages/cugraph_ops.md
+++ /dev/null
@@ -1,17 +0,0 @@
-
-
- 
-
-
-CuGraphOps
-
-Cugraph-ops is a closed-source library that is composed of highly optimized and
-performant primitives associated with GNNs and related graph
-operations, such as training, sampling and inference.
-
-
-This is how cuGraphOps fits into the cuGraph ecosystem
-
-
- 
-