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Merge branch 'branch-23.12-rs-ds-refactor' of https://github.com/nv-r…
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…liu/cugraph into branch-23.12-rs-ds-refactor
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rlratzel committed Nov 18, 2023
2 parents aea91f1 + 16ba391 commit 7067cb0
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Showing 13 changed files with 163 additions and 57 deletions.
2 changes: 1 addition & 1 deletion .github/workflows/build.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@ on:
default: nightly

concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
group: ${{ github.workflow }}-${{ github.ref }}-${{ github.event_name }}
cancel-in-progress: true

jobs:
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31 changes: 15 additions & 16 deletions ci/test_python.sh
Original file line number Diff line number Diff line change
Expand Up @@ -197,27 +197,26 @@ if [[ "${RAPIDS_CUDA_VERSION}" == "11.8.0" ]]; then
conda activate test_cugraph_pyg
set -u

# Install pytorch
# Will automatically install built dependencies of cuGraph-PyG
rapids-mamba-retry install \
--force-reinstall \
--channel pyg \
--channel "${CPP_CHANNEL}" \
--channel "${PYTHON_CHANNEL}" \
--channel pytorch \
--channel nvidia \
'pyg=2.3' \
'pytorch=2.0.0' \
'pytorch-cuda=11.8'
--channel pyg \
--channel rapidsai-nightly \
"cugraph-pyg" \
"pytorch>=2.0,<2.1" \
"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 "${CPP_CHANNEL}" \
--channel "${PYTHON_CHANNEL}" \
libcugraph \
pylibcugraph \
pylibcugraphops \
cugraph \
cugraph-pyg
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-print-env

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2 changes: 1 addition & 1 deletion conda/recipes/cugraph-pyg/meta.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@ requirements:
- cupy >=12.0.0
- cugraph ={{ version }}
- pylibcugraphops ={{ minor_version }}
- pyg >=2.3,<2.4
- pyg >=2.3,<2.5

tests:
imports:
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5 changes: 5 additions & 0 deletions cpp/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -153,6 +153,11 @@ rapids_cpm_init()
# lags behind.
###

# Need to make sure rmm is found before cuco so that rmm patches the libcudacxx
# directory to be found by cuco.
include(${rapids-cmake-dir}/cpm/rmm.cmake)
rapids_cpm_rmm(BUILD_EXPORT_SET cugraph-exports
INSTALL_EXPORT_SET cugraph-exports)
# Putting this before raft to override RAFT from pulling them in.
include(cmake/thirdparty/get_libcudacxx.cmake)
include(${rapids-cmake-dir}/cpm/cuco.cmake)
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4 changes: 2 additions & 2 deletions dependencies.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -497,9 +497,9 @@ dependencies:
- output_types: [conda]
packages:
- cugraph==23.12.*
- pytorch==2.0
- pytorch>=2.0
- pytorch-cuda==11.8
- pyg=2.3.1=*torch_2.0.0*cu118*
- pyg>=2.4.0

depends_on_rmm:
common:
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4 changes: 2 additions & 2 deletions python/cugraph-pyg/conda/cugraph_pyg_dev_cuda-118.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -13,13 +13,13 @@ dependencies:
- cugraph==23.12.*
- pandas
- pre-commit
- pyg=2.3.1=*torch_2.0.0*cu118*
- pyg>=2.4.0
- pylibcugraphops==23.12.*
- pytest
- pytest-benchmark
- pytest-cov
- pytest-xdist
- pytorch-cuda==11.8
- pytorch==2.0
- pytorch>=2.0
- scipy
name: cugraph_pyg_dev_cuda-118
12 changes: 9 additions & 3 deletions python/cugraph-pyg/cugraph_pyg/data/cugraph_store.py
Original file line number Diff line number Diff line change
Expand Up @@ -210,7 +210,10 @@ class EXPERIMENTAL__CuGraphStore:
def __init__(
self,
F: cugraph.gnn.FeatureStore,
G: Union[Dict[str, Tuple[TensorType]], Dict[str, int]],
G: Union[
Dict[Tuple[str, str, str], Tuple[TensorType]],
Dict[Tuple[str, str, str], int],
],
num_nodes_dict: Dict[str, int],
*,
multi_gpu: bool = False,
Expand Down Expand Up @@ -744,7 +747,7 @@ def _subgraph(self, edge_types: List[tuple] = None) -> cugraph.MultiGraph:

def _get_vertex_groups_from_sample(
self, nodes_of_interest: TensorType, is_sorted: bool = False
) -> dict:
) -> Dict[str, torch.Tensor]:
"""
Given a tensor of nodes of interest, this
method a single dictionary, noi_index.
Expand Down Expand Up @@ -808,7 +811,10 @@ def _get_sample_from_vertex_groups(

def _get_renumbered_edge_groups_from_sample(
self, sampling_results: cudf.DataFrame, noi_index: dict
) -> Tuple[dict, dict]:
) -> Tuple[
Dict[Tuple[str, str, str], torch.Tensor],
Tuple[Dict[Tuple[str, str, str], torch.Tensor]],
]:
"""
Given a cudf (NOT dask_cudf) DataFrame of sampling results and a dictionary
of non-renumbered vertex ids grouped by vertex type, this method
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48 changes: 30 additions & 18 deletions python/cugraph-pyg/cugraph_pyg/loader/cugraph_node_loader.py
Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,7 @@

import os
import re
import warnings

import cupy
import cudf
Expand Down Expand Up @@ -159,23 +160,34 @@ def __init__(
if batch_size is None or batch_size < 1:
raise ValueError("Batch size must be >= 1")

self.__directory = tempfile.TemporaryDirectory(dir=directory)
self.__directory = (
tempfile.TemporaryDirectory() if directory is None else directory
)

if isinstance(num_neighbors, dict):
raise ValueError("num_neighbors dict is currently unsupported!")

renumber = (
True
if (
(len(self.__graph_store.node_types) == 1)
and (len(self.__graph_store.edge_types) == 1)
if "renumber" in kwargs:
warnings.warn(
"Setting renumbering manually could result in invalid output,"
" please ensure you intended to do this."
)
renumber = kwargs.pop("renumber")
else:
renumber = (
True
if (
(len(self.__graph_store.node_types) == 1)
and (len(self.__graph_store.edge_types) == 1)
)
else False
)
else False
)

bulk_sampler = BulkSampler(
batch_size,
self.__directory.name,
self.__directory
if isinstance(self.__directory, str)
else self.__directory.name,
self.__graph_store._subgraph(edge_types),
fanout_vals=num_neighbors,
with_replacement=replace,
Expand Down Expand Up @@ -219,7 +231,13 @@ def __init__(
)

bulk_sampler.flush()
self.__input_files = iter(os.listdir(self.__directory.name))
self.__input_files = iter(
os.listdir(
self.__directory
if isinstance(self.__directory, str)
else self.__directory.name
)
)

def __next__(self):
from time import perf_counter
Expand Down Expand Up @@ -423,9 +441,6 @@ def __next__(self):
sampler_output.edge,
)
else:
if self.__graph_store.order == "CSR":
raise ValueError("CSR format incompatible with CSC output")

out = filter_cugraph_store_csc(
self.__feature_store,
self.__graph_store,
Expand All @@ -437,11 +452,8 @@ def __next__(self):

# Account for CSR format in cuGraph vs. CSC format in PyG
if self.__coo and self.__graph_store.order == "CSC":
for node_type in out.edge_index_dict:
out[node_type].edge_index[0], out[node_type].edge_index[1] = (
out[node_type].edge_index[1],
out[node_type].edge_index[0],
)
for edge_type in out.edge_index_dict:
out[edge_type].edge_index = out[edge_type].edge_index.flip(dims=[0])

out.set_value_dict("num_sampled_nodes", sampler_output.num_sampled_nodes)
out.set_value_dict("num_sampled_edges", sampler_output.num_sampled_edges)
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Original file line number Diff line number Diff line change
Expand Up @@ -120,7 +120,7 @@ def test_get_edge_index(graph, edge_index_type, dask_client):
G[et][0] = dask_cudf.from_cudf(cudf.Series(G[et][0]), npartitions=1)
G[et][1] = dask_cudf.from_cudf(cudf.Series(G[et][1]), npartitions=1)

cugraph_store = CuGraphStore(F, G, N, multi_gpu=True)
cugraph_store = CuGraphStore(F, G, N, order="CSC", multi_gpu=True)

for pyg_can_edge_type in G:
src, dst = cugraph_store.get_edge_index(
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54 changes: 51 additions & 3 deletions python/cugraph-pyg/cugraph_pyg/tests/test_cugraph_loader.py
Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@

import cudf
import cupy
import numpy as np

from cugraph_pyg.loader import CuGraphNeighborLoader
from cugraph_pyg.loader import BulkSampleLoader
Expand All @@ -27,6 +28,8 @@
from cugraph.gnn import FeatureStore
from cugraph.utilities.utils import import_optional, MissingModule

from typing import Dict, Tuple

torch = import_optional("torch")
torch_geometric = import_optional("torch_geometric")
trim_to_layer = import_optional("torch_geometric.utils.trim_to_layer")
Expand All @@ -40,7 +43,11 @@


@pytest.mark.skipif(isinstance(torch, MissingModule), reason="torch not available")
def test_cugraph_loader_basic(karate_gnn):
def test_cugraph_loader_basic(
karate_gnn: Tuple[
FeatureStore, Dict[Tuple[str, str, str], np.ndarray], Dict[str, int]
]
):
F, G, N = karate_gnn
cugraph_store = CuGraphStore(F, G, N, order="CSR")
loader = CuGraphNeighborLoader(
Expand All @@ -66,7 +73,11 @@ def test_cugraph_loader_basic(karate_gnn):


@pytest.mark.skipif(isinstance(torch, MissingModule), reason="torch not available")
def test_cugraph_loader_hetero(karate_gnn):
def test_cugraph_loader_hetero(
karate_gnn: Tuple[
FeatureStore, Dict[Tuple[str, str, str], np.ndarray], Dict[str, int]
]
):
F, G, N = karate_gnn
cugraph_store = CuGraphStore(F, G, N, order="CSR")
loader = CuGraphNeighborLoader(
Expand Down Expand Up @@ -342,7 +353,7 @@ def test_cugraph_loader_e2e_coo():
@pytest.mark.skipif(isinstance(torch, MissingModule), reason="torch not available")
@pytest.mark.skipif(not HAS_TORCH_SPARSE, reason="torch-sparse not available")
@pytest.mark.parametrize("framework", ["pyg", "cugraph-ops"])
def test_cugraph_loader_e2e_csc(framework):
def test_cugraph_loader_e2e_csc(framework: str):
m = [2, 9, 99, 82, 9, 3, 18, 1, 12]
x = torch.randint(3000, (256, 256)).to(torch.float32)
F = FeatureStore()
Expand Down Expand Up @@ -442,3 +453,40 @@ def test_cugraph_loader_e2e_csc(framework):
x = x.narrow(dim=0, start=0, length=s - num_sampled_nodes[1])

assert list(x.shape) == [1, 1]


@pytest.mark.skipif(isinstance(torch, MissingModule), reason="torch not available")
@pytest.mark.parametrize("directory", ["local", "temp"])
def test_load_directory(
karate_gnn: Tuple[
FeatureStore, Dict[Tuple[str, str, str], np.ndarray], Dict[str, int]
],
directory: str,
):
if directory == "local":
local_dir = tempfile.TemporaryDirectory(dir=".")

cugraph_store = CuGraphStore(*karate_gnn)
cugraph_loader = CuGraphNeighborLoader(
(cugraph_store, cugraph_store),
torch.arange(8, dtype=torch.int64),
2,
num_neighbors=[8, 4, 2],
random_state=62,
replace=False,
directory=None if directory == "temp" else local_dir.name,
batches_per_partition=1,
)

it = iter(cugraph_loader)
next_batch = next(it)
assert next_batch is not None

if directory == "local":
assert len(os.listdir(local_dir.name)) == 4

count = 1
while next(it, None) is not None:
count += 1

assert count == 4
2 changes: 1 addition & 1 deletion python/cugraph-pyg/cugraph_pyg/tests/test_cugraph_store.py
Original file line number Diff line number Diff line change
Expand Up @@ -113,7 +113,7 @@ def test_get_edge_index(graph, edge_index_type):
G[et][0] = cudf.Series(G[et][0])
G[et][1] = cudf.Series(G[et][1])

cugraph_store = CuGraphStore(F, G, N)
cugraph_store = CuGraphStore(F, G, N, order="CSC")

for pyg_can_edge_type in G:
src, dst = cugraph_store.get_edge_index(
Expand Down
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