Bump Treelite to 4.1.2 (#5814)

Treelite 4.1.2 contains important bug fixes such as: * dmlc/treelite#547 * dmlc/treelite#552 * dmlc/treelite#553 Authors: - Philip Hyunsu Cho (https://github.com/hcho3) Approvers: - Dante Gama Dessavre (https://github.com/dantegd) - Ray Douglass (https://github.com/raydouglass) URL: #5814
rapidsai · Apr 1, 2024 · 743123c · 743123c
1 parent 84989a5
commit 743123c
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Showing 10 changed files with 12 additions and 34 deletions.
diff --git a/conda/environments/all_cuda-118_arch-x86_64.yaml b/conda/environments/all_cuda-118_arch-x86_64.yaml
@@ -72,7 +72,7 @@ dependencies:
 - sphinx<6
 - statsmodels
 - sysroot_linux-64==2.17
-- treelite==4.0.0
+- treelite==4.1.2
 - umap-learn==0.5.3
 - pip:
   - dask-glm==0.3.0

diff --git a/conda/environments/all_cuda-122_arch-x86_64.yaml b/conda/environments/all_cuda-122_arch-x86_64.yaml
@@ -68,7 +68,7 @@ dependencies:
 - sphinx<6
 - statsmodels
 - sysroot_linux-64==2.17
-- treelite==4.0.0
+- treelite==4.1.2
 - umap-learn==0.5.3
 - pip:
   - dask-glm==0.3.0

diff --git a/conda/recipes/cuml/conda_build_config.yaml b/conda/recipes/cuml/conda_build_config.yaml
@@ -17,4 +17,4 @@ sysroot_version:
   - "=2.17"
 
 treelite_version:
-  - "=4.0.0"
+  - "=4.1.2"
diff --git a/conda/recipes/libcuml/conda_build_config.yaml b/conda/recipes/libcuml/conda_build_config.yaml
@@ -17,7 +17,7 @@ cmake_version:
   - ">=3.26.4"
 
 treelite_version:
-  - "=4.0.0"
+  - "=4.1.2"
 
 gtest_version:
   - ">=1.13.0"

diff --git a/cpp/cmake/thirdparty/get_treelite.cmake b/cpp/cmake/thirdparty/get_treelite.cmake
@@ -78,7 +78,7 @@ function(find_and_configure_treelite)
     rapids_export_find_package_root(BUILD Treelite [=[${CMAKE_CURRENT_LIST_DIR}]=] EXPORT_SET cuml-exports)
 endfunction()
 
-find_and_configure_treelite(VERSION     4.0.0
-                        PINNED_TAG  e878556d29336d2242fd926beb659b9dec41be3a
+find_and_configure_treelite(VERSION     4.1.2
+                        PINNED_TAG  454abc4bfe03e6e9d45155c15f74ae36d8c73111
                         EXCLUDE_FROM_ALL  ${CUML_EXCLUDE_TREELITE_FROM_ALL}
                         BUILD_STATIC_LIBS ${CUML_USE_TREELITE_STATIC})
diff --git a/dependencies.yaml b/dependencies.yaml
@@ -156,7 +156,7 @@ dependencies:
       - output_types: [conda, requirements, pyproject]
         packages:
           - cython>=3.0.0
-          - &treelite treelite==4.0.0
+          - &treelite treelite==4.1.2
       - output_types: conda
         packages:
           - &pylibraft_conda pylibraft==24.4.*

diff --git a/python/cuml/experimental/fil/fil.pyx b/python/cuml/experimental/fil/fil.pyx
@@ -22,7 +22,6 @@ import warnings
 from libcpp cimport bool
 from libc.stdint cimport uint32_t, uintptr_t
 
-from cuml.internals.import_utils import has_sklearn
 from cuml.common.device_selection import using_device_type
 from cuml.internals.input_utils import input_to_cuml_array
 from cuml.internals.safe_imports import (
@@ -967,16 +966,6 @@ class ForestInference(UniversalBase, CMajorInputTagMixin):
             For GPU execution, the RAFT handle containing the stream or stream
             pool to use during loading and inference.
         """
-        # TODO(hcho3): Remove this check when https://github.com/dmlc/treelite/issues/544 is fixed
-        if has_sklearn():
-            from sklearn.ensemble import (
-                HistGradientBoostingClassifier as HistGradientBoostingC,
-            )
-            from sklearn.ensemble import (
-                HistGradientBoostingRegressor as HistGradientBoostingR,
-            )
-            if isinstance(skl_model, (HistGradientBoostingR, HistGradientBoostingC)):
-                raise NotImplementedError("HistGradientBoosting estimators are not yet supported")
         tl_model = treelite.sklearn.import_model(skl_model)
         if default_chunk_size is None:
             default_chunk_size = threads_per_tree

diff --git a/python/cuml/fil/fil.pyx b/python/cuml/fil/fil.pyx
@@ -29,7 +29,6 @@ from libc.stdint cimport uintptr_t
 from libc.stdlib cimport free
 
 import cuml.internals
-from cuml.internals.import_utils import has_sklearn
 from cuml.internals.array import CumlArray
 from cuml.internals.base import Base
 from pylibraft.common.handle cimport handle_t
@@ -882,16 +881,6 @@ class ForestInference(Base,
         logger.warn("Treelite currently does not support float64 model"
                     " parameters. Accuracy may degrade slightly relative to"
                     " native sklearn invocation.")
-        # TODO(hcho3): Remove this check when https://github.com/dmlc/treelite/issues/544 is fixed
-        if has_sklearn():
-            from sklearn.ensemble import (
-                HistGradientBoostingClassifier as HistGradientBoostingC,
-            )
-            from sklearn.ensemble import (
-                HistGradientBoostingRegressor as HistGradientBoostingR,
-            )
-            if isinstance(skl_model, (HistGradientBoostingR, HistGradientBoostingC)):
-                raise NotImplementedError("HistGradientBoosting estimators are not yet supported")
         tl_model = tl_skl.import_model(skl_model)
         cuml_fm.load_from_treelite_model(
             model=tl_model,

diff --git a/python/cuml/tests/test_random_forest.py b/python/cuml/tests/test_random_forest.py
@@ -1327,7 +1327,7 @@ def test_rf_regressor_gtil_integration(tmpdir):
     X, y = X.astype(np.float32), y.astype(np.float32)
     clf = curfr(max_depth=3, random_state=0, n_estimators=10)
     clf.fit(X, y)
-    expected_pred = clf.predict(X).reshape((-1, 1))
+    expected_pred = clf.predict(X).reshape((-1, 1, 1))
 
     checkpoint_path = os.path.join(tmpdir, "checkpoint.tl")
     clf.convert_to_treelite_model().to_treelite_checkpoint(checkpoint_path)
@@ -1342,7 +1342,7 @@ def test_rf_binary_classifier_gtil_integration(tmpdir):
     X, y = X.astype(np.float32), y.astype(np.int32)
     clf = curfc(max_depth=3, random_state=0, n_estimators=10)
     clf.fit(X, y)
-    expected_pred = clf.predict_proba(X)
+    expected_pred = clf.predict_proba(X).reshape((-1, 1, 2))
 
     checkpoint_path = os.path.join(tmpdir, "checkpoint.tl")
     clf.convert_to_treelite_model().to_treelite_checkpoint(checkpoint_path)
@@ -1357,7 +1357,7 @@ def test_rf_multiclass_classifier_gtil_integration(tmpdir):
     X, y = X.astype(np.float32), y.astype(np.int32)
     clf = curfc(max_depth=3, random_state=0, n_estimators=10)
     clf.fit(X, y)
-    expected_prob = clf.predict_proba(X)
+    expected_prob = clf.predict_proba(X).reshape((X.shape[0], 1, -1))
 
     checkpoint_path = os.path.join(tmpdir, "checkpoint.tl")
     clf.convert_to_treelite_model().to_treelite_checkpoint(checkpoint_path)

diff --git a/python/pyproject.toml b/python/pyproject.toml
@@ -21,7 +21,7 @@ requires = [
     "pylibraft==24.4.*",
     "rmm==24.4.*",
     "scikit-build-core[pyproject]>=0.7.0",
-    "treelite==4.0.0",
+    "treelite==4.1.2",
 ] # This list was generated by `rapids-dependency-file-generator`. To make changes, edit ../dependencies.yaml and run `rapids-dependency-file-generator`.
 build-backend = "scikit_build_core.build"
 
@@ -66,7 +66,7 @@ dependencies = [
     "rapids-dask-dependency==24.4.*",
     "rmm==24.4.*",
     "scipy>=1.8.0",
-    "treelite==4.0.0",
+    "treelite==4.1.2",
 ] # This list was generated by `rapids-dependency-file-generator`. To make changes, edit ../dependencies.yaml and run `rapids-dependency-file-generator`.
 classifiers = [
     "Intended Audience :: Developers",