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[CI] Use latest RAPIDS; Pandas 2.0 compatibility fix (#10175)

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* [CI] Update RAPIDS to latest stable

* [CI] Use rapidsai stable channel; fix syntax errors in Dockerfile.gpu

* Don't combine astype() with loc()

* Work around https://github.com/dmlc/xgboost/issues/10181

* Fix formatting

* Fix test

---------

Co-authored-by: hcho3 <hcho3@users.noreply.github.com>
Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
github-actions[bot]
2024-04-15 13:38:53 -07:00
committed by GitHub
parent 6e5c335cea
commit 2925cebdca
5 changed files with 18 additions and 17 deletions
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2
tests/buildkite/conftest.sh
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@@ -24,7 +24,7 @@ set -x
CUDA_VERSION=11.8.0
NCCL_VERSION=2.16.5-1
RAPIDS_VERSION=24.02
RAPIDS_VERSION=24.04
SPARK_VERSION=3.4.0
JDK_VERSION=8
R_VERSION=4.3.2

8
tests/ci_build/Dockerfile.gpu
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@@ -21,14 +21,14 @@ ENV PATH=/opt/mambaforge/bin:$PATH
# Create new Conda environment with cuDF, Dask, and cuPy
RUN \
conda install -c conda-forge mamba && \
mamba create -n gpu_test -c rapidsai-nightly -c rapidsai -c nvidia -c conda-forge -c defaults \
export NCCL_SHORT_VER=$(echo "$NCCL_VERSION_ARG" | cut -d "-" -f 1) && \
mamba create -y -n gpu_test -c rapidsai -c nvidia -c conda-forge \
python=3.10 cudf=$RAPIDS_VERSION_ARG* rmm=$RAPIDS_VERSION_ARG* cudatoolkit=$CUDA_VERSION_ARG \
nccl>=$(cut -d "-" -f 1 << $NCCL_VERSION_ARG) \
"nccl>=${NCCL_SHORT_VER}" \
dask=2024.1.1 \
dask-cuda=$RAPIDS_VERSION_ARG* dask-cudf=$RAPIDS_VERSION_ARG* cupy \
numpy pytest pytest-timeout scipy scikit-learn pandas matplotlib wheel python-kubernetes urllib3 graphviz hypothesis \
pyspark>=3.4.0 cloudpickle cuda-python && \
"pyspark>=3.4.0" cloudpickle cuda-python && \
mamba clean --all && \
conda run --no-capture-output -n gpu_test pip install buildkite-test-collector

9
tests/python-gpu/test_from_cudf.py
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@@ -71,15 +71,6 @@ def _test_from_cudf(DMatrixT):
assert dtrain.num_col() == 1
assert dtrain.num_row() == 5
# Boolean is not supported.
X_boolean = cudf.DataFrame({"x": cudf.Series([True, False])})
with pytest.raises(Exception):
dtrain = DMatrixT(X_boolean)
y_boolean = cudf.DataFrame({"x": cudf.Series([True, False, True, True, True])})
with pytest.raises(Exception):
dtrain = DMatrixT(X_boolean, label=y_boolean)
def _test_cudf_training(DMatrixT):
import pandas as pd