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

* [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 #10181 * Fix formatting * Fix test --------- Co-authored-by: hcho3 <hcho3@users.noreply.github.com> Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
dmlc · Apr 15, 2024 · 2925ceb · 2925ceb
1 parent 6e5c335
commit 2925ceb
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Showing 5 changed files with 18 additions and 17 deletions.
diff --git a/python-package/xgboost/data.py b/python-package/xgboost/data.py
@@ -909,9 +909,19 @@ def _transform_cudf_df(
     enable_categorical: bool,
 ) -> Tuple[ctypes.c_void_p, list, Optional[FeatureNames], Optional[FeatureTypes]]:
     try:
-        from cudf.api.types import is_categorical_dtype
+        from cudf.api.types import is_bool_dtype, is_categorical_dtype
     except ImportError:
         from cudf.utils.dtypes import is_categorical_dtype
+        from pandas.api.types import is_bool_dtype
+
+    # Work around https://github.com/dmlc/xgboost/issues/10181
+    if _is_cudf_ser(data):
+        if is_bool_dtype(data.dtype):
+            data = data.astype(np.uint8)
+    else:
+        data = data.astype(
+            {col: np.uint8 for col in data.select_dtypes(include="bool")}
+        )
 
     if _is_cudf_ser(data):
         dtypes = [data.dtype]

diff --git a/python-package/xgboost/testing/__init__.py b/python-package/xgboost/testing/__init__.py
@@ -429,8 +429,8 @@ def make_categorical(
     categories = np.arange(0, n_categories)
     for col in df.columns:
         if rng.binomial(1, cat_ratio, size=1)[0] == 1:
-            df.loc[:, col] = df[col].astype("category")
-            df.loc[:, col] = df[col].cat.set_categories(categories)
+            df[col] = df[col].astype("category")
+            df[col] = df[col].cat.set_categories(categories)
 
     if sparsity > 0.0:
         for i in range(n_features):

diff --git a/tests/buildkite/conftest.sh b/tests/buildkite/conftest.sh
@@ -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

diff --git a/tests/ci_build/Dockerfile.gpu b/tests/ci_build/Dockerfile.gpu
@@ -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
 

diff --git a/tests/python-gpu/test_from_cudf.py b/tests/python-gpu/test_from_cudf.py
@@ -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