Upgrade CI to onnx==1.16.0 (#689)

* upgrade to onnx==1.16.0 Signed-off-by: Xavier Dupre <[email protected]> * doc Signed-off-by: Xavier Dupre <[email protected]> * black Signed-off-by: Xavier Dupre <[email protected]> * black Signed-off-by: Xavier Dupre <[email protected]> * fix opset Signed-off-by: Xavier Dupre <[email protected]> --------- Signed-off-by: Xavier Dupre <[email protected]>
onnx · Apr 3, 2024 · a105247 · a105247
1 parent b1e1068
commit a105247
Show file tree

Hide file tree

Showing 9 changed files with 62 additions and 46 deletions.
diff --git a/.azure-pipelines/linux-conda-CI.yml b/.azure-pipelines/linux-conda-CI.yml
@@ -15,10 +15,10 @@ jobs:
   strategy:
     matrix:
 
-      Python311-1150-RT117-xgb2-lgbm40:
+      Python311-1160-RT1171-xgb2-lgbm40:
         python.version: '3.11'
-        ONNX_PATH: 'onnx==1.15.0'
-        ONNXRT_PATH: 'onnxruntime==1.17'
+        ONNX_PATH: 'onnx==1.16.0'
+        ONNXRT_PATH: 'onnxruntime==1.17.1'
         COREML_PATH: NONE
         lightgbm.version: '>=4.0'
         xgboost.version: '>=2'

diff --git a/.azure-pipelines/win32-conda-CI.yml b/.azure-pipelines/win32-conda-CI.yml
@@ -15,61 +15,61 @@ jobs:
   strategy:
     matrix:
 
-      Python311-1150-RT117:
+      Python311-1160-RT1171:
         python.version: '3.11'
-        ONNX_PATH: 'onnx==1.15.0'
-        ONNXRT_PATH: 'onnxruntime==1.17'
+        ONNX_PATH: 'onnx==1.16.0'
+        ONNXRT_PATH: 'onnxruntime==1.17.1'
         COREML_PATH: NONE
         numpy.version: ''
-        xgboost.version: '2.0.2'
+        xgboost.version: '>=2.0'
 
       Python311-1150-RT1163:
         python.version: '3.11'
         ONNX_PATH: 'onnx==1.15.0'
         ONNXRT_PATH: 'onnxruntime==1.16.3'
         COREML_PATH: NONE
         numpy.version: ''
-        xgboost.version: '2.0.2'
+        xgboost.version: '==2.0.2'
 
       Python311-1150-RT1162:
         python.version: '3.11'
         ONNX_PATH: 'onnx==1.15.0'
         ONNXRT_PATH: 'onnxruntime==1.16.2'
         COREML_PATH: NONE
         numpy.version: ''
-        xgboost.version: '2.0.2'
+        xgboost.version: '==2.0.2'
 
       Python311-1141-RT1162:
         python.version: '3.11'
         ONNX_PATH: 'onnx==1.14.1'
         ONNXRT_PATH: 'onnxruntime==1.16.2'
         COREML_PATH: NONE
         numpy.version: ''
-        xgboost.version: '1.7.5'
+        xgboost.version: '==1.7.5'
 
       Python310-1141-RT1151:
         python.version: '3.10'
         ONNX_PATH: 'onnx==1.14.1'
         ONNXRT_PATH: 'onnxruntime==1.15.1'
         COREML_PATH: NONE
         numpy.version: ''
-        xgboost.version: '1.7.5'
+        xgboost.version: '==1.7.5'
 
       Python310-1141-RT1140:
         python.version: '3.10'
         ONNX_PATH: 'onnx==1.14.1'
         ONNXRT_PATH: onnxruntime==1.14.0
         COREML_PATH: NONE
         numpy.version: ''
-        xgboost.version: '1.7.5'
+        xgboost.version: '==1.7.5'
 
       Python39-1141-RT1140:
         python.version: '3.9'
         ONNX_PATH: 'onnx==1.14.1'
         ONNXRT_PATH: onnxruntime==1.14.0
         COREML_PATH: NONE
         numpy.version: ''
-        xgboost.version: '1.7.5'
+        xgboost.version: '==1.7.5'
 
     maxParallel: 3
 
@@ -96,7 +96,7 @@ jobs:
       call activate py$(python.version)
       python -m pip install --upgrade scikit-learn
       python -m pip install --upgrade lightgbm
-      python -m pip install "xgboost==$(xgboost.version)"
+      python -m pip install "xgboost$(xgboost.version)"
     displayName: 'Install scikit-learn'
 
   - script: |

diff --git a/.github/workflows/black-ruff.yml b/.github/workflows/black-ruff.yml
@@ -5,7 +5,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v2
-      - uses: psf/black@193ee766ca496871f93621d6b58d57a6564ff81b  # stable 23.7.0
+      - uses: psf/black@e42f1ffbe159018c8e887f775c0fd7b51b3cf787  # stable 24.3.0
         with:
           options: "--diff --check"
           src: "."

diff --git a/CHANGELOGS.md b/CHANGELOGS.md
@@ -2,6 +2,8 @@
 
 ## 1.13.0 (development)
 
+* Handle issue with binary classifier setting output to [N,1] vs [N,2],
+  [#681](https://github.com/onnx/onnxmltools/pull/681)
 * Add missing dependency onnxconverter_common, fix multi regression with xgboost,
   [#679](https://github.com/onnx/onnxmltools/pull/679),
   fixes issues [No module named 'onnxconverter_common'](https://github.com/onnx/onnxmltools/issues/673),

diff --git a/onnxmltools/convert/coreml/operator_converters/TreeEnsemble.py b/onnxmltools/convert/coreml/operator_converters/TreeEnsemble.py
@@ -45,9 +45,9 @@ def convert_tree_ensemble_model(scope, operator, container):
         op_type = "TreeEnsembleClassifier"
         prefix = "class"
         nodes = raw_model.treeEnsembleClassifier.treeEnsemble.nodes
-        attrs[
-            "base_values"
-        ] = raw_model.treeEnsembleClassifier.treeEnsemble.basePredictionValue
+        attrs["base_values"] = (
+            raw_model.treeEnsembleClassifier.treeEnsemble.basePredictionValue
+        )
         attrs["post_transform"] = get_onnx_tree_post_transform(
             raw_model.treeEnsembleClassifier.postEvaluationTransform
         )
@@ -72,12 +72,12 @@ def convert_tree_ensemble_model(scope, operator, container):
         op_type = "TreeEnsembleRegressor"
         prefix = "target"
         nodes = raw_model.treeEnsembleRegressor.treeEnsemble.nodes
-        attrs[
-            "base_values"
-        ] = raw_model.treeEnsembleRegressor.treeEnsemble.basePredictionValue
-        attrs[
-            "n_targets"
-        ] = raw_model.treeEnsembleRegressor.treeEnsemble.numPredictionDimensions
+        attrs["base_values"] = (
+            raw_model.treeEnsembleRegressor.treeEnsemble.basePredictionValue
+        )
+        attrs["n_targets"] = (
+            raw_model.treeEnsembleRegressor.treeEnsemble.numPredictionDimensions
+        )
         attrs["post_transform"] = get_onnx_tree_post_transform(
             raw_model.treeEnsembleRegressor.postEvaluationTransform
         )

diff --git a/onnxmltools/convert/sparkml/ops_input_output.py b/onnxmltools/convert/sparkml/ops_input_output.py
@@ -134,12 +134,16 @@ def build_io_name_map():
             lambda model: [model.getOrDefault("predictionCol")],
         ),
         "pyspark.ml.feature.ImputerModel": (
-            lambda model: model.getOrDefault("inputCols")
-            if model.isSet("inputCols")
-            else [model.getOrDefault("inputCol")],
-            lambda model: model.getOrDefault("outputCols")
-            if model.isSet("outputCols")
-            else [model.getOrDefault("outputCol")],
+            lambda model: (
+                model.getOrDefault("inputCols")
+                if model.isSet("inputCols")
+                else [model.getOrDefault("inputCol")]
+            ),
+            lambda model: (
+                model.getOrDefault("outputCols")
+                if model.isSet("outputCols")
+                else [model.getOrDefault("outputCol")]
+            ),
         ),
         "pyspark.ml.feature.MaxAbsScalerModel": (
             lambda model: [model.getOrDefault("inputCol")],
@@ -177,20 +181,28 @@ def build_io_name_map():
             ],
         ),
         "pyspark.ml.feature.OneHotEncoderModel": (
-            lambda model: model.getOrDefault("inputCols")
-            if model.isSet("inputCols")
-            else [model.getOrDefault("inputCol")],
-            lambda model: model.getOrDefault("outputCols")
-            if model.isSet("outputCols")
-            else [model.getOrDefault("outputCol")],
+            lambda model: (
+                model.getOrDefault("inputCols")
+                if model.isSet("inputCols")
+                else [model.getOrDefault("inputCol")]
+            ),
+            lambda model: (
+                model.getOrDefault("outputCols")
+                if model.isSet("outputCols")
+                else [model.getOrDefault("outputCol")]
+            ),
         ),
         "pyspark.ml.feature.StringIndexerModel": (
-            lambda model: model.getOrDefault("inputCols")
-            if model.isSet("inputCols")
-            else [model.getOrDefault("inputCol")],
-            lambda model: model.getOrDefault("outputCols")
-            if model.isSet("outputCols")
-            else [model.getOrDefault("outputCol")],
+            lambda model: (
+                model.getOrDefault("inputCols")
+                if model.isSet("inputCols")
+                else [model.getOrDefault("inputCol")]
+            ),
+            lambda model: (
+                model.getOrDefault("outputCols")
+                if model.isSet("outputCols")
+                else [model.getOrDefault("outputCol")]
+            ),
         ),
         "pyspark.ml.feature.VectorAssembler": (
             lambda model: model.getOrDefault("inputCols"),

diff --git a/onnxmltools/convert/xgboost/shape_calculators/Classifier.py b/onnxmltools/convert/xgboost/shape_calculators/Classifier.py
@@ -27,7 +27,7 @@ def calculate_xgboost_classifier_output_shapes(operator):
     objective = params["objective"]
     n_estimators = get_n_estimators_classifier(xgb_node, params, js_trees)
     num_class = params.get("num_class", None)
-    
+
     if objective == "binary:logistic":
         ncl = 2
     elif num_class is not None:

diff --git a/pyproject.toml b/pyproject.toml
@@ -10,10 +10,10 @@ exclude = [
 # Same as Black.
 line-length = 95
 
-[tool.ruff.mccabe]
+[tool.ruff.lint.mccabe]
 max-complexity = 10
 
-[tool.ruff.per-file-ignores]
+[tool.ruff.lint.per-file-ignores]
 "**/__init__.py" = ["F401"]
 "onnxmltools/convert/coreml/operator_converters/GLMClassifier.py" = ["E501"]
 "onnxmltools/convert/coreml/operator_converters/SVC.py" = ["E501"]

diff --git a/tests/xgboost/test_xgboost_issues.py b/tests/xgboost/test_xgboost_issues.py
@@ -41,7 +41,9 @@ def xgbregressor_shape_calculator(operator):
         initial_type = [("float_input", FloatTensorType([None, X.shape[1]]))]
 
         # Convert XGBoost model to ONNX
-        onnx_model = convert_sklearn(model, initial_types=initial_type, target_opset=12)
+        onnx_model = convert_sklearn(
+            model, initial_types=initial_type, target_opset={"": 12, "ai.onnx.ml": 3}
+        )
         self.assertIn("dim_value: 2", str(onnx_model.graph.output))
 
         sess = onnxruntime.InferenceSession(